>>Hello, everyone. Welcome to the cubes presentation of the 80, but startup showcases MarTech is the focus. And this is all about the emerging cloud scale customer experience. This is season two, episode three of the ongoing series covering the exciting, fast growing startups from the cloud AWS ecosystem to talk about the future and what's available now, where are the actions? I'm your host John fur. Today. We joined by Cub alumni, Jerry Chen partner at Greylock ventures. Jerry. Great to see you. Thanks for coming on, >>John. Thanks for having me back. I appreciate you welcome there for season two. Uh, as a, as a guest star, >><laugh>, you know, Hey, you know, season two, it's not a one and done it's continued coverage. We, we got the episodic, uh, cube flicks model going >>Here. Well, you know, congratulations, the, the coverage on this ecosystem around AWS has been impressive, right? I think you and I have talked a long time about AWS and the ecosystem building. It just continues to grow. And so the coverage you did last season, all the events of this season is, is pretty amazing from the data security to now marketing. So it's, it's great to >>Watch. And 12 years now, the cube been running. I remember 2013, when we first met you in the cube, we just left VMware just getting into the venture business. And we were just riffing the next 80. No one really kind of knew how big it would be. Um, but we were kinda riffing on. We kind of had a sense now it's happening. So now you start to see every vertical kind of explode with the right digital transformation and disruption where you see new incumbents. I mean, new Newton brands get replaced the incumbent old guard. And now in MarTech, it's ripe for, for disruption because web two has gone on to web 2.5, 3, 4, 5, um, cookies are going away. You've got more governance and privacy challenges. There's a slew of kind of ad tech baggage, but yet lots of new data opportunities. Jerry, this is a huge, uh, thing. What's your take on this whole MarTech cloud scale, uh, >>Market? I, I think, I think to your point, John, that first the trends are correct and the bad and the good or good old days, the battle days MarTech is really about your webpage. And then email right there. There's, there's the emails, the only channel and the webpage was only real estate and technology to care about fast forward, you know, 10 years you have webpages, mobile apps, VR experiences, car experiences, your, your, your Alexa home experiences. Let's not even get to web three web 18, whatever it is. Plus you got text messages, WhatsApp, messenger, email, still great, et cetera. So I think what we've seen is both, um, explosion and data, uh, explosion of channel. So sources of data have increases and the fruits of the data where you can reach your customers from text, email, phone calls, etcetera have exploded too. So the previous generation created big company responses, Equa, you know, that exact target that got acquired by Oracle or, or, um, Salesforce, and then companies like, um, you know, MailChimp that got acquired as well, but into it, you're seeing a new generation companies for this new stack. So I, I think it's exciting. >>Yeah. And you mentioned all those things about the different channels and stuff, but the key point is now the generation shifts going on, not just technical generation, uh, and platform and tools, it's the people they're younger. They don't do email. They have, you know, proton mail accounts, zillion Gmail accounts, just to get the freebie. Um, they're like, they're, they'll do subscriptions, but not a lot. So the generational piece on the human side is huge. Okay. And then you got the standards, bodies thrown away, things like cookies. Sure. So all this is makes it for a complicated, messy situation. Um, so out of this has to come a billion dollar startup in my mind, >>I, I think multiple billion dollars, but I think you're right in the sense that how we want engage with the company branch, either consumer brands or business brands, no one wants to pick a phone anymore. Right? Everybody wants to either chat or DM people on Twitter. So number one, the, the way we engage is different, both, um, where both, how like chat or phone, but where like mobile device, but also when it's the moment when we need to talk to a company or brand be it at the store, um, when I'm shopping in real life or in my car or at the airport, like we want to reach the brands, the brands wanna reach us at the point of decision, the point of support, the point of contact. And then you, you layer upon that the, the playing field, John of privacy security, right? All these data silos in the cloud, the, the, the, the game has changed and become even more complicated with the startup. So the startups are gonna win. Will do, you know, the collect, all the data, make us secure in private, but then reach your customers when and where they want and how they want it. >>So I gotta ask you, because you had a great podcast just this week, published and snowflake had their event going on the data cloud, there's a new kind of SAS platform vibe going on. You're starting to see it play out. Uh, and one of the things I, I noticed on your podcast with the president of Hashi Corp, who was on people should listen to that podcast. It's on gray matter, which is the Greylocks podcast, uh, plug for you guys. He mentioned he mentions the open source dynamic, right? Sure. And, and I like what he, things, he said, he said, software business has changed forever. It's my words. Now he said infrastructure, but I'm saying software in general, more broader infrastructure and software as a category is all open source. One game over no debate. Right. You agree? >>I, I think you said infrastructure specifically starts at open source, but I would say all open source is one more or less because open source is in every bit of software. Right? And so from your operating system to your car, to your mobile phone, open source, not necessarily as a business model or, or, or whatever, we can talk about that. But open source as a way to build software distribute, software consume software has one, right? It is everywhere. So regardless how you make money on it, how you build software, an open source community ha has >>One. Okay. So let's just agree. That's cool. I agree with that. Let's take it to the next level. I'm a company starting a company to sell to big companies who pay. I gotta have a proprietary advantage. There's gotta be a way. And there is, I know you've talked about it, but I have my opinion. There is needs to be a way to be proprietary in a way that allows for that growth, whether it's integration, it's not gonna be on software license or maybe support or new open source model. But how does startups in the MarTech this area in general, when they disrupt or change the category, they gotta get value creation going. What's your take on, on building. >>You can still build proprietary software on top of open source, right? So there's many companies out there, um, you know, in a company called rock set, they've heavily open source technology like Rock's DB under the hood, but they're running a cloud database. That's proprietary snowflake. You talk about them today. You know, it's not open source technology company, but they use open source software. I'm sure in the hoods, but then there's open source companies, data break. So let's not confus the two, you can still build proprietary software. There's just components of open source, wherever we go. So number one is you can still build proprietary IP. Number two, you can get proprietary data sources, right? So I think increasingly you're seeing companies fight. I call this systems intelligence, right, by getting proprietary data, to train your algorithms, to train your recommendations, to train your applications, you can still collect data, um, that other competitors don't have. >>And then it can use the data differently, right? The system of intelligence. And then when you apply the system intelligence to the end user, you can create value, right? And ultimately, especially marketing tech, the highest level, what we call the system of engagement, right? If, if the chat bot the mobile UI, the phone, the voice app, etcetera, if you own the system of engagement, be a slack, or be it, the operating system for a phone, you can also win. So still multiple levels to play John in multiple ways to build proprietary advantage. Um, just gotta own system record. Yeah. System intelligence, system engagement. Easy, right? Yeah. >>Oh, so easy. Well, the good news is the cloud scale and the CapEx funded there. I mean, look at Amazon, they've got a ton of open storage. You mentioned snowflake, but they're getting a proprietary value. P so I need to ask you MarTech in particular, that means it's a data business, which you, you pointed out and we agree. MarTech will be about the data of the workflows. How do you get those workflows what's changing and how these companies are gonna be building? What's your take on it? Because it's gonna be one of those things where it might be the innovation on a source of data, or how you handle two parties, ex handling encrypted data sets. I don't know. Maybe it's a special encryption tool, so we don't know what it is. What's your what's, what's your outlook on this area? >>I, I, I think that last point just said is super interesting, super genius. It's integration or multiple data sources. So I think either one, if it's a data business, do you have proprietary data? Um, one number two with the data you do have proprietary, not how do you enrich the data and do you enrich the data with, uh, a public data set or a party data set? So this could be cookies. It could be done in Brad street or zoom info information. How do you enrich the data? Number three, do you have machine learning models or some other IP that once you collected the data, enriched the data, you know, what do you do with the data? And then number four is once you have, um, you know, that model of the data, the customer or the business, what do you deal with it? Do you email, do you do a tax? >>Do you do a campaign? Do you upsell? Do you change the price dynamically in our customers? Do you serve a new content on your website? So I think that workflow to your point is you can start from the same place, what to do with the data in between and all the, on the out the side of this, this pipeline is where a MarTech company can have then. So like I said before, it was a website to an email go to website. You know, we have a cookie fill out a form. Yeah. I send you an email later. I think now you, you can't just do a website to email, it's a website plus mobile apps, plus, you know, in real world interaction to text message, chat, phone, call Twitter, a whatever, you know, it's >>Like, it's like, they're playing checkers in web two and you're talking 3d chess. <laugh>, I mean, there's a level, there's a huge gap between what's coming. And this is kind of interesting because now you mentioned, you know, uh, machine learning and data, and AI is gonna factor into all this. You mentioned, uh, you know, rock set. One of your portfolios has under the hood, you know, open source and then use proprietary data and cloud. Okay. That's a configuration, that's an architecture, right? So architecture will be important in terms of how companies posture in this market, cuz MarTech is ripe for innovation because it's based on these old technologies, but there's tons of workflows, but you gotta have the data. Right. And so if I have the best journey map from a client that goes to a website, but then they go and they do something in the organic or somewhere else. If I don't have that, what good is it? It's like a blind spot. >>Correct. So I think you're seeing folks with the data BS, snowflake or data bricks, or an Amazon that S three say, Hey, come to my data cloud. Right. Which, you know, Snowflake's advertising, Amazon will say the data cloud is S3 because all your data exists there anyway. So you just, you know, live on S3 data. Bricks will say, S3 is great, but only use Amazon tools use data bricks. Right. And then, but on top of that, but then you had our SaaS companies like Oracle, Salesforce, whoever, and say, you know, use our qua Marketo, exact target, you know, application as a system record. And so I think you're gonna have a battle between, do I just work my data in S3 or where my data exists or gonna work my data, some other application, like a Marketo Ella cloud Z target, um, or, you know, it could be a Twilio segment, right. Was combination. So you'll have this battle between these, these, these giants in the cloud, easy, the castles, right. Versus, uh, the, the, the, the contenders or the, or the challengers as we call >>'em. Well, great. Always chat with the other. We always talk about castles in the cloud, which is your work that you guys put out, just an update on. So check out greylock.com. They have castles on the cloud, which is a great thesis on and a map by the way ecosystem. So you guys do a really good job props to Jerry and the team over at Greylock. Um, okay. Now I gotta ask kind of like the VC private equity sure. Market question, you know, evaluations. Uh, first of all, I think it's a great time to do a startup. So it's a good time to be in the VC business. I think the next two years, you're gonna find some nice gems, but also you gotta have that cleansing period. You got a lot of overvaluation. So what happened with the markets? So there's gonna be a lot of M and a. So the question is what are some of the things that you see as challenges for product teams in particular that might have that killer answer in MarTech, or might not have the runway if there's no cash, um, how do people partner in this modern era, cuz scale's a big deal, right? Mm-hmm <affirmative> you can measure everything. So you get the combination of a, a new kind of M and a market coming, a potential growth market for the right solution. Again, value's gotta be be there. What's your take on this market? >>I, I, I think you're right. Either you need runway, so cash to make it through, through this next, you know, two, three years, whatever you think the market Turmo is or two, you need scale, right? So if you're at a company of scale and you have enough data, you can probably succeed on your own. If not, if you're kind of in between or early to your point, either one focus, a narrower wedge, John, just like we say, just reduce the surface area. And next two years focus on solving one problem. Very, very well, or number two in this MarTech space, especially there's a lot of partnership and integration opportunities to create a complete solution together, to compete against kind of the incumbents. Right? So I think they're folks with the data, they're folks doing data, privacy, security, they're post focusing their workflow or marketing workflows. You're gonna see either one, um, some M and a, but I definitely can see a lot of Coopers in partnership. And so in the past, maybe you would say, I'm just raise another a hundred million dollars and do what you're doing today. You might say, look, instead of raising more money let's partner together or, or merge or find a solution. So I think people are gonna get creative. Yeah. Like said scarcity often is good. Yeah. I think forces a lot more focus and a lot more creativity. >>Yeah. That's a great point. I'm glad you brought that up up. Cause I didn't think you were gonna go there. I was gonna ask that biz dev activity is going to be really fundamental because runway combined with the fact that, Hey, you know, if you know, get real or you're gonna go under is a real issue. So now people become friends. They're like, okay, if we partner, um, it's clearly a good way to go if you can get there. So what advice would you give companies? Um, even most experienced, uh, founders and operators. This is a different market, right? It's a different kind of velocity, obviously architectural data. You mentioned some of those key things. What's the posture to partner. What's your advice? What's the combat man manual to kind of compete in this new biz dev world where some it's a make or break time, either get the funding, get the customers, which is how you get funding or you get a biz dev deal where you combine forces, uh, go to market together or not. What's your advice? >>I, I think that the combat manual is either you're partnering for one or two things, either one technology or two customers or sometimes both. So it would say which partnerships, youre doing for technology EG solution completers. Like you have, you know, this puzzle piece, I have this puzzle piece data and data privacy and let's work together. Um, or number two is like, who can help you with customers? And that's either a, I, they can be channel for you or, or vice versa or can share customers and you can actually go to market together and find customers jointly. So ideally you're partner for one, if not the other, sometimes both. And just figure out where in your life cycle do you need? Um, friends. >>Yeah. Great. My final question, Jerry, first of all, thanks for coming on and sharing your in insight as usual. Always. Awesome final question for the folks watching that are gonna be partnering and buying product and services from these startups. Um, there's a select few great ones here and obviously every other episode as well, and you've got a bunch you're investing in this, it's actually a good market for the ones that are lean companies that are lean and mean have value. And the cloud scale does provide that. So a lot of companies are getting it right, they're gonna break through. So they're clearly gonna be getting customers the buyer side, how should they be looking through the lens right now and looking at companies, what should they look for? Um, and they like to take chances with seeing that. So it's not so much, they gotta be vetted, but you know, how do they know the winners from the pretenders? >>You know, I, I think the customers are always smart. I think in the, in the, in the past in market market tech, especially they often had a budget to experiment with. I think you're looking now the customers, the buyer technologies are looking for a hard ROI, like a return on investment. And before think they might experiment more, but now they're saying, Hey, are you gonna help me save money or increase revenue or some hardcore metric that they care about? So I think, um, the startups that actually have a strong ROI, like save money or increased revenue and can like point empirically how they do that will, will, you know, rise to the top of, of the MarTech landscape. And customers will see that they're they're, the customers are smart, right? They're savvy buyers. They, they, they, they, they can smell good from bad and they're gonna see the strong >>ROI. Yeah. And the other thing too, I like to point out, I'd love to get your reaction real quick is a lot of the companies have DNA, any open source or they have some community track record where communities now, part of the vetting. I mean, are they real good people? >>Yeah. I, I think open stores, like you said, in the community in general, like especially all these communities that move on slack or discord or something else. Right. I think for sure, just going through all those forums, slack communities or discord communities, you can see what's a good product versus next versus bad. Don't go to like the other sites. These communities would tell you who's working. >>Well, we got a discord channel on the cube now had 14,000 members. Now it's down to six, losing people left and right. We need a moderator, um, to get on. If you know anyone on discord, anyone watching wants to volunteer to be the cube discord, moderator. Uh, we could use some help there. Love discord. Uh, Jerry. Great to see you. Thanks for coming on. What's new at Greylock. What's some of the things happening. Give a quick plug for the firm. When you guys working on, I know there's been some cool things happening, new investments, people moving. >>Yeah. Look we're we're Greylock partners, seed series a firm. I focus at enterprise software. I have a team with me that also does consumer investing as well as crypto investing like all firms. So, but we're we're seed series a occasionally later stage growth. So if you're interested, uh, FA me@jkontwitterorjgreylock.com. Thank you, John. >>Great stuff, Jerry. Thanks for coming on. This is the Cube's presentation of the, a startup showcase. MarTech is the series this time, emerging cloud scale customer experience where the integration and the data matters. This is season two, episode three of the ongoing series covering the hottest cloud startups from the ADWS ecosystem. Um, John farrier, thanks for watching.

>> Hello, everyone. Welcome to theCUBE presentation of the AWS startup showcase, market MarTech, emerging cloud scale customer experience. This is season two, episode three of the ongoing series covering the exciting startups from the AWS ecosystem. Talking about the data analytics, all the news and all the hot stories. I'm John Furrier your host of theCUBE. And today we're excited to be joined by Rachel Ostler, VP of product at Heap, Heap.io. Here to talk about from what, to why the future of digital insights. Great to see you, thanks for joining us today. >> Thanks for having me, John. Thanks for having me back. >> Well, we had a great conversation prior to the event here, a lot going on, you guys had acquired Auryc in an acquisition. You kind of teased that out last time. Talk about this, the news here, and why is it important? And first give a little setup on Heap and then the acquisition with Auryc. >> Yeah. So heap is a digital insights platform. So as you mentioned, it's all about analytics and so Heap really excels at helping you understand what your users and customers are doing in your digital application at scale. So when it comes to Auryc, what we really saw was a broken workflow. Maybe, I would even call it a broken market. Where a lot of customers had an analytics tool like Heap. So they're using Heap on one hand to figure out what is happening at scale with their users. But on the other hand, they were also using, like a session replay tool separately, to look at individual sessions and see exactly what was happening. And no one was very effective at using these tools together. They didn't connect at all. And so as a result, neither one of them could really be fully leveraged. And so with this acquisition, we're able to put these two tools together, so that users can both understand the what at scale, and then really see the why, immediately together in one place. >> You know, that I love that word why, because there's always that, you know, that famous motivational video on the internet, "you got to know your why", you know, it's very a motivational thing, but now you're getting more practicality. What and why is the, is the lens you want, right? So, I totally see that. And again, you can teased that out in our last interview we did. But I want to understand what's under the covers, under the acquisition. What was the big thesis behind it? Why the joint forces? What does this all mean? Why is this so important to understand this new, what and why and the acquisition specifically? >> Yeah, so let me give you example of a couple used cases, that's really helpful for understanding this. So imagine that you are a product manager or a, maybe a growth marketer, but you're someone who owns a digital experience. And what you're trying to do, of course, is make that digital experience amazing for your users so that they get value and that may mean that they're using it more, it may mean that new features are easily discoverable, that you can upsell things on your own. There's all sorts of different things that that may mean, but it's all about making it easy to use, discoverable, understandable, and as self-service as possible too. And so most of these digital builders, we call 'em digital builders sometimes. They are trying to figure out when the application is not working the way that it should be working, where people are getting stuck, where they're not getting the value and figure out how to fix that. And so, one really great used case is, I just want to understand in mass, like, let's say I have a flow, where are people dropping off? Right, so I see that I have a four step funnel and between step three and four people are dropping off. Heap is great for getting very detailed on exactly what action they're taking, where they're dropping off. But then the second you find what that action is, quantitatively, you want to watch it, you want to see what they did exactly before it. You want to see what they did after it. You want to understand why they're getting stuck. What they're confused at, are they mouthing over two things, like you kind of want to watch their session. And so what this acquisition allows us to do, is to put those things together seamlessly, you find the point in friction, you watch a bunch of examples, very easily. In the past, this would take you at least hours, if you could do it at all. And then in other used cases, the other direction. So there's the kind of, I think of it as the max to the min, and then there's the other direction as well. Like you have the, or maybe it's the macro to micro. You have the micro to macro, which is you have one user that had a problem. Maybe they send in a support ticket. Well, you can validate the problem. You can watch it in the session, but then you want to know, did this only happen to them? Did this happen to a lot of users? And this is really worth fixing, because all these customers are having the same problem. That's the micro to macro flow that you can do as well. >> Yeah. That's like, that's like the quantitative qualitative, the what and the why. I truly see the value there and I liked the way you explained that, good call out. The question I have for you, because a lot of people have these tools. "I got someone who does that." "I got someone over here that does the quantitative." "I don't need to have one company do it, or do I?" So the question I have for you, what does having a single partner or vendor, providing both the quantitative and the qualitative nails mean for your customers? >> So it's all because now it's immediate. So today with the two tools being separate, you may find something quantitatively. But then to, then to find the sessions that you want to watch that are relevant to that quantitative data point is very difficult. At least it takes hours to do so. And a lot of times people just give up and they don't bother. The other way is also true, you can watch sessions, you can watch as many sessions as you want, you can spend hours doing it, you may never find anything of interest, right? So it just ends up being something that users don't do. And actually we've interviewed a lot of customers, they have a lot of guilt about this. A lot of product managers feel like they should be spending all this time, but they just don't have the time to spend. And so it not only brings them together, but it brings them together with immediacy. So you can immediately find the issue, find exactly where it is and watch it. And this is a big deal, because, if you think about, I guess, like today's economic conditions, you don't have a lot of money to waste. You don't have a lot of time to waste. You have to be very impactful with what you're doing and with your spending of development resources. >> Yeah. And totally, and I think one of the things that immediacy is key, because it allows you to connect dots faster. And we have the aha moments all the time. If you miss that, the consequences can be quantified in a bad product experience and lost customers. So, totally see that. Zooming out now, I want to get your thoughts on this, cause you're bringing, we're going down this road of essentially every company is digital now, right? So digitization, digital transformation. What do you want to call it? Data is digital. This video is an experience. It's also data as well. You're talking, we're going to share this and people are going to experience that. So every website that's kind of old school is now becoming essentially a digital native application or eCommerce platform. All the things that were once preserved for the big guys, the hyper-scalers and the categories, the big budgets, now are coming down to every company. Every company is a digital company. What challenges do they have to transition from? I got a website, I got a marketing team. Now I got to look like a world class, product, eCommerce, multifaceted, application with developers, with change, with agility? >> Well, so I think that last thing you said is a really important part of it, the agility. So, these products, when you're going from a, just a website to a product, they're a lot more complex. Right? And so maybe I can give an example. We have a customer, it's an insurance company. So they have this online workflow. And if you can imagine signing up for insurance online, it's a pretty long complicated workflow. I mean, Hey, better to do it online than to have to call someone and wait on, you know, on the phone. And so it's a good experience, but it's still fraught with like opportunities of people getting stuck and never coming back. And so one of the things that Heap allowed this customer to do was figure out something that wasn't working in their workflow. And so if you think about traditional analytics tools, typically what you're doing is you're writing tracking code and you're saying, "Hey, I'm going to track this funnel, this process." And so maybe it has, you know, five different forms or pages that you have to go through. And so what you're doing when you track it is you say, did you submit the first one? Did you submit the second one? Did you submit the third one? So you know, like where they're falling off. You know where they're falling off, but you don't know why, you don't know which thing got them stuck because each one of these pages has multiple inputs and it has maybe multiple steps that you need to do. And so you're completely blind to exactly what's happening. Well, it turned out because Heap collects all this data, that on one of these pages where users were dropping off, it was because they were clicking on a FAQ, there was a link to a FAQ, and because this was a big company, the FAQ took them to a completely different application. Didn't know how to get back from there and they just lost people. And imagine if you are doing this with traditional means today, right? You don't have any visibility into what's happening on that page, you just know that they fell off. You might think about what do I do to fix this? How do I make this flow work better? And you might come up with a bunch of ideas. One of your ideas could be, let's break it into multiple pages. Maybe there's too much stuff on this page. One of your ideas may have been, let's try a FAQ. They're getting stuck, let's give them some more help. That would be a very bad idea, right? Because that was actually the reason why they were leaving and never coming back. So, the point I'm making is that, if you don't know exactly where people are getting stuck and you can't see exactly what is happening, then you're going to make a lot of very bad decisions. You're going to waste a lot of resources, trying things that make no sense. It is hard enough as a digital builder and all the product managers and growth marketers and marketers out there can attest to this, it's hard enough when you know exactly what the problem is to figure out a good solution. Right? That's still hard. But if you don't know the problem, it's impossible. >> Okay, so let's just level up, the bumper sticker now for the challenges are what? Decision making, what's the, stack rank the top three challenges from that. So it's being agile, right? So being very fast, because you're competing with a lot of companies right now. It's about making really good decisions and driving impact, right? So you have to have all the data that you need. You have to have the, the specific information about what's going on. Cause if you don't have it, you're going to decide to invest in things and you're not going to drive the impact that you want. >> So now you got the acquisition of Auryc and Auryc and you have the, this visibility to the customers that are building, investing, you mentioned, okay. As they invest, whether it's the digital product or new technology in R and D, what feedback have you guys seen from these investments, from these customers, what results have come out of it? Could you share any specific answers to the problems and challenges you have outlined, because you know, there's growth hackers could be failing cause of stupid little product mistakes that could have been avoided in the feedback, you know what I'm saying? So it's like, where can you, where are these challenges addressed and what are some of the results? >> Yeah, so, what we've seen with our customers is that when they are applying this data and doing this analysis on say workflows or goals that they're trying to accomplish, they've been able to move the needle quite a bit. And so, whether it is, you know, increasing conversion rates or whether it is making sure that they don't have, you know, drop off of trial signups or making sure that their customers are more engaged than before, when they know exactly where they're failing, it is much easier to make an investment and move the needle. >> Awesome. Well, let's move on to the next big topic, which I love, it's about data science and data engineering. You guys are a data company and I want to ask you specifically, how Heap uniquely is positioned to help companies succeed, where in the old big tech world, they're tightening the ropes on secure cookies, privacy, data sharing. At the same time, there's been an explosion in cloud scale data opportunities and new technologies. So it seems like a new level of, capability, is going to replace the old cookies, privacy and data sharing, which seem to be constricting or going away. How do you, what's your reaction to that? Can you share how Heap fits into this next generation and the current situation going on with the cookies and this privacy stuff. >> Yep, so it is really important in this world to be collecting data compliantly, right? And so what that means is, you don't want to be reliant on third party cookies. You want to be reliant on just first party information. You want to make sure that you don't collect any PII. Heap is built to do that from the ground up. We by default will not collect information, like what do people put into forms, right? Because that's a obvious source of PII. The other thing is that, there's just so much data. So you kind of alluded to this, with this idea of data science. So first of all, you're collecting data compliantly, you're making sure that you have all the data of what your user actions are doing, compliantly, but then it's so much data that it like, how do you know where to start? Right? You want to know, you want to get to that specific point that users are dropping off, but there's so many different options out there. And so that's where Heap is applying data science, to automatically find those points of friction and automatically surface them to users, so that you don't have to guess and check and constantly guess at what the problem is, but you can see it in the product surface right for you. >> You know, Rachel, that's a great point. I want to call that out because I think a lot of companies don't underestimate, they may underestimate what you said earlier, capturing in compliance way means, you're opting in to say, not to get the data, to unwind it later, figure it out. You're capturing it in a compliant way, which actually reduces the risk and operational technical debt you might have to deploy to get it fixed on compliance. Okay, that's one thing, I love that. I want to make sure people understand that value. That's a huge value, especially for people that don't have huge teams and diverse platforms or other data sources. The other thing you mentioned is owning their own data. And that first party data is a strategic advantage, mainly around personalization and targeted customer interaction. So the question is, with the new data, I own the data, you got the comp- capture with compliance. How do you do personalization and targeted customer interactions, at the same time while being compliant? It just seems, it seems like compliance is restrictive and kind of forecloses value, but open means you can personalization and targeted interactions. How do you guys connect the dots there by being compliant, but yet being valuable on the personalization and targeted? >> Well, it all depends on how the customer is managing their information, but imagine that you have a logged in user, well, you know, who the logged in user is, right? And so all we really need is an ID. Doesn't have, we don't need to know any of the user information. We just need an ID and then we can serve up the information about like, what have they done, if they've done these three actions, maybe that means that this particular offer would be interested to them. And so that information is available within Heap, for our customers to use it as they want to, with their users. >> So you're saying you can enable companies to own their data, be compliant and then manage it end to end from a privacy standpoint. >> Yes. >> That's got to be a top seller right there. >> Well, it's not just a top seller, it's a necessity. >> It's a must have. I mean, think about it. I mean, what are people, what are the, what are people who don't do this? What do they face? What's the alternative? If you don't keep, get the Heap going immediately, what's the alternative? I'm going through logs, I got to have to get request to forget my data. All these things are all going on, right? Is, what's the consequence of not doing this? >> Well, there's a couple consequences. So one is, and I kind of alluded to it earlier that, you're just, you're blind to what your users are doing, which means that you're making investments that may not make sense, right? So you can, you can decide to add all the cool features in the world, but if the customers don't perceive them as being valuable or don't find them or don't understand them, it doesn't, it doesn't serve your business. And so, this is one of like the rule number one of being a product manager, is you're trying to balance what your customers need, with what is also good for your business. And both of those have to be in place. So that's basically where you are, is that you'll be making investments that just won't be hitting the mark and you won't be moving the needle. And as I mentioned, it's more important now in this economic climate than ever to make sure that the investments you're making are targeted and impactful. >> Yeah and I think the other thing to point out, is that's a big backlash against the whole, Facebook, you're the product, you're getting used, the users being used for product, but you're, you guys have a way to make that happen in a way that's safe for the user. >> Yes. Safe and compliant. So look, we're all about making sure that we certainly don't get our customers into trouble and we recommend that they follow all compliance rules, because the last thing you want to be is on the, on the wrong side of a compliance officer. >> Well, there's also the user satisfaction problem of, and the fines. So a lot going on there, great product. I got to ask you real quick before we kind of wrap up here. What's the reaction been to the acquisition? Quantitative, qualitative. What's been the vibe? What are some, what are people saying about it? >> We've got a lot of interest. So, I mentioned earlier that this is really a broken workflow in the market. And when users see the two products working together, they just love it because they have not been able to leverage them being separate before. And so it just makes it so much easier for these digital builders to figure out, what do I invest in because they know exactly where people are having trouble. So it's been really great, we've had a lot of reach outs already asking us how they can use it, try it, not quite available yet. So it's going to be available later this summer, but great, great response so far. >> Awesome. Well, I love the opportunity. Love the conversation, I have to ask you now, looking forward, what does the future look like for companies taking advantage of your platform and tool? What can they expect in terms of R and D investments, area moves you're making? You're the head of product, you get the keys to the kingdom. What's the future look like? What's coming next? >> Yeah, so other than pulling the qual and the quant together, you actually hinted at it earlier when you're asking me about data science, but continuing to automate as much of the analysis as we can. So, first of all, analysis, analytics, it should be easy for everyone. So we're continue to invest in making it easy, but part of making it easy is, like we can automate analysis. We can, we can see that your website has a login page on it and build a funnel for you automatically. So that's some of the stuff that we're working on, is how do we both automate getting up to speed and getting that initial analysis done easily, without any work. And then also, how do we automate more complex analysis? So you have, typically a lot of companies have a data science team and they end up doing a lot of analysis, it's a little bit more complex. I'm not saying data science teams will go away, they will be around forever. There's tons of very complex analysis that they're probably not even getting time to do. We're going to start chipping away at that, so we can help product managers do more and more of that self-service and then free up the data science team to do even more interesting things. >> I really like how you use the word product managers, product builders, digital builders, because while I got you, I want to get your thought on this, because it's a real industry shift. You're talking about it directly here, about websites going to eCommerce, CMOs, a C-suite, they generally observe that websites are old technology, but not going away, because the next level abstraction builds on top of it. What's the new capabilities because for the CMOs and the C-suites and the product folks out there, they're not building webpages, they're building applications. So what is it about this new world that's different from the old web architecture? How would you talk to a CMO or a leader? And to, when they ask what's this new opportunity to take my website, cause maybe it's not enough traffic. People are consuming out in the organic, what's this new expectation and how, what does a new product manager environment look like, if it's not the web, so to speak? >> Well, there's a couple things. So one is, and you alluded to it a bit, like the websites are also getting more complex and you need to start thinking of your website as a product. Now it's, it may not be the product that you sell, but it is, well for eCommerce it's the place that you get access to the product, for B2B SaaS, it is the window to the product. It's a place where you can learn about the product. And you need to think about, not just like, what pieces of content are being used, but you need to understand the user flow, through the application. So that's how it's a lot more like a product. >> Rachel, thanks so much for coming on theCUBE here for this presentation, final word, put a plugin for the company. What are you guys up to? What are you looking for? Take a minute to explain kind of that, what's going on. How do people contact you with a great value proposition? Put a plugin for the company. >> Yeah, well, if you want to up level your product experience or website experience, you want to be able to drive impact quickly, try Heap. You can go to Heap.io, you can try it for free. We have a free trial, we have a free product even. And yeah, and then if you have any questions, you want to talk to a live person, you can do that too, at sales@Heap.io. >> Rachel, thanks so much. Customer-scale experiences with the cloud house league. This is the season two, episode three of the ongoing series. I'm John Furrier, your host. Thanks for watching. (upbeat music)

(gentle music) >> Hey everyone. Welcome to theCUBE's coverage of the AWS Startup Showcase. Season two, episode three. This is about MarTech, emerging cloud scale customer experience. This is our ongoing series that you know and love hopefully that feature a great number of AWS ecosystem partners. I'm your host, Lisa Martin. Got a great guest here from Branch. Michelle Lerner joins me, the senior director of business development. She's going to be talking about Branch but also about one of your favorite brands, Peet's, yep, the coffee place, and how they supercharged loyalty and app adoption with Branch. Michelle, it's great to have you on the program. >> Yeah. Great to be here. Thank you so much for having me. >> Tell us a little bit about Branch, what you guys do for the modern mobile marketer. >> Yeah, absolutely. So you can think about Branch as a mobile linking platform. So what that means is we offer a seamless deep linking experience and insightful campaign measurement across every single marketing channel and platform on mobile. We exist so that we can break down walled gardens to help our customers engage with their customers in the most optimal way across any device and from every marketing channel. Our products are specifically designed to help create an amazing user experience, but also provide full picture holistic downstream measurement across any paid, owned, and earned channels so that brands can actually see what's working. So what that really means is that we make it really easy to scale our links across every single marketing channel, which then route the users to the right place at any device through even past install so that they can get to the context that they expect for a seamless experience. We then provide that cross channel analytics back to the brand so that they could see what's working and they can make better business decisions. So kind of summing it up, our industry leading mobile linking actually powers those deep links, also supports that measurement so that brands can build a sophisticated experience that actually delight their users but also improve their metrics and conversion rates. >> Those two things that you said are key. We expected to be delighted with whatever experience we're having and we also want to make sure, and obviously, the brands want to make sure that they're doing that but also that from an attribution perspective, from a campaign conversion perspective, that they can really understand the right tactics and the right strategic elements that are driving those conversions. That's been a challenge for marketers for a long time. Speaking of challenges, we've all been living through significant challenges. There's no way to say it nicely. The last two years, every industry completely affected by the pandemic talk. We're going to talk about Peet's Coffee. And I want to understand some of the challenges that you saw in the quick service restaurant or QSR industry at large. Talk to me about those industry challenges and then we'll dig into the Peet's story. >> Yeah, absolutely. So obviously the pandemic changed so much in our lives whether it's going to work or commuting or taking our kids to school or even getting our morning coffee. So when you think about Peet's, specifically within the QSR industry, they knew that they needed to innovate in order to make sure that they could provide their customers with their daily cups of coffee in a really safe and effective way. So they thought really quickly on their feet, they engaged us at Branch to help launch their order ahead messaging across their online and offline channels. They really wanted to maintain their commitment to an excellent customer experience but in a way that obviously would be safe and effective. >> That was one of the things that I missed the very most in the very beginning of the pandemic was going to my local Peet's. I missed that experience. Talk me about, you mentioned the online and offline, I'm very familiar with the online as an app user, mobile app user, but what were some of the challenges that they were looking to Branch to resolve on the offline experiences? People were queuing outside or for those folks that were they trying to get folks to convert to using the mobile app that maybe weren't users already? What was that online and offline experience? What were some of the challenges they were looking to resolve? >> Yeah, absolutely. The modern marketer is really both, like you said, online and offline, there is a heavy focus within the app and Peet's kind of wanted to bridge those two by pushing users into the app to provide a better experience there. So what they ended up doing was they used our deep linking capabilities to seamlessly route their customers to their loyalty program and their rewards catalog and other menu offerings within the app so that they could actually get things done in real time, but also in real time was the ability to then measure across those different campaigns so that they had visibility, Peet's, into kind of the way that they could optimize that campaign performance but also still give that great experience to their users. And they actually saw higher loyalty adoption, order values, and attributed purchases when they were able to kind of see in real time where these users were converting. But another thing that we're actually seeing across the board and Peet's did a great job of this was leveraging Branch power QR codes where we are seeing like the rebirth of the QR code. They're back, they're here to stay. They actually used that across multiple channels. So they used it with their in-store signage. You might have even seen it on their to go cups, coffee cards that were handed out by baristas. They were all encouraging customers to go order ahead using the Peet's coffee app. But that was kind of just the beginning for them. The creation of unique links for those QR codes actually spread for them to create Branch links across everything from emails to ads on Instagram. So before long, most of Peet's retail marketing were actually Branch links just because of the ease of creation and reliability, but more so again, going back to that customer experience, it really provided that good experience for the customers to make sure that they were getting within the mobile app so that they can take action and order their coffee. Another way that Branch kind of bridges the different platforms is actually between mobile web and app. Peet used Branch Journeys and that's a product of ours. It's a way that they can convert their mobile web users into app users. So they used deferred deep links with the ultimate goal of then converting those users into high value app users. So the Peet's team actually tested different creative and interstitials across the mobile site which would then place those users into the key pages, like either the homepage or the store locator, or the menu pages within the app. So that also helped them kind of build up not just their mobile app order online but also their delivery business so they could hire new trials of seasonal beverages. They could pair them with a free delivery offering. So they knew that they were able to leverage that at scale across multiple initiatives. >> I love those kinds of stories where it's kind of like a land and expand where there was obviously a global massive problem. They saw that recognized our customers are still going to be is demanding. Maybe if not more than they were before with I want my coffee, I want it now, you mentioned real time. I think one of the things we learned during the pandemic is access to realtime data isn't a nice to have anymore. We expect it as consumers even in our business lives, but the ability to be able to measure, course correct, but then see, wow, this is driving average order value up, we're getting more folks using our mobile app, maybe using delivery. Let's expand the usage of Branch across what we're doing in marketing can really help transform our marketing organization and a business at the brand level. >> Absolutely. And it also helps predict that brand loyalty. Because like you said, we, as consumers expect that that brands are going to kind of follow us where we are in our life cycle as consumers and if you don't do that, then you're going to be left in the dust unfortunately. >> I think one of the memories that will always stick with me, Michelle, during the last couple years is that first cup of Peet's that I didn't have to make at home myself. Just finally getting the courage to go back in, use the app, go in there, but oh man, that was probably the best taste of coffee I probably will ever have. You mentioned some of the products, you mentioned Journeys, and that allows them to do AB testing, looking at different CTAs, being able to kind of course correct and adjust campaigns in real time. >> Yeah, absolutely. So Journeys, what it does is it's basically a banner or a full page interstitial that is populated on the mobile web. So if you go to let's say Peets.com, you could get served as a user, either different creative or depending on where you are, location wise, you could be in the store, maybe there's a promotion. So it's triggered by all these different targeting capabilities. And so what that does is it takes me as a user. I can click that and go into the app where, like we said before, we have higher order value, higher lifetime value of a customer. And all my credit card information is saved. It just makes it so much more seamless for me to convert as a user within the app. And obviously Peet's likes that as well because then their conversion rates are actually higher. There's also kind of fun ways to play around with it. So if I am already a loyal customer and I have the app, you probably would target different creative for me than you would for someone who doesn't have the app. So you could say, hey, download our app, get $5 off of your next mobile order. Things like that you could play around with and you can see really does help increase that loyalty. But actually they were able to take, they kind of are experimenting with the geotargeted journeys in different key markets with different Peet's. And actually it was helping ultimately get their reinstalls growing. So for customers who maybe had the app before but needed to reinstall it because now there's such a bigger focus, they saw it both on the acquisition and the re-engagement side as well. >> So Branch has been pretty transformative, not in my estimation to Peet's marketing, but to Peet's as a business I'm hearing absolutely customer loyalty, revenue obviously impacted, brand loyalty, brand reputation. These are things that really kind of boil up to the top of the organization. So we're not just talking about benefits to the marketing and the sales folks. This is the overall massive business outcomes that you guys are enabling organizations like Peet's to generate. >> Yeah, definitely. And that's kind of what we tell our customers when they come to Branch. We want them to think about what their overall business objectives are versus if you think just campaign by campaign, okay, that's fine. But ultimately what are we trying to achieve? How could we help the bottom line? And then how can we also kind of help integrate with other mobile marketing technology or the modern tech stack that they're using? How do we integrate into that and actually provide not just a seamless experience for their end user, but with their marketing orgs, their product orgs, whoever's kind of touching the business as well? >> Have you noticed along those lines in the last couple of years as things like customer delight, seamless experience, the ability to translate, if I start on my iPad and I go to my laptop and then I finish a transaction on my phone, have you noticed your customer conversations increasing up to the C-suite level? Is this much more of a broad organizational objective around we've got to make sure that we have a really strong digital user experience? >> Yeah, absolutely. Like we were talking about before, it really does help affect the bottom line when you're providing a great experience with Branch being a mobile linking platform, our links just work. We outperform everybody else in the space and it might sound like really simple, okay, a link is working getting me from point A to point B, but doing it the right way and being consistent actually will increase performance over time of all these campaigns. So it's just an addition to providing that experience, you're seeing those key business results every single time. >> Talk about attribution for a minute because I've been in marketing for a long time in the tech industry. And that's always one of the challenges is we want to know what lever did the customer pull that converted them from opportunity to a lead to whatnot? Talk about the ability for Branch from an attribution perspective to really tell those marketers and the organization exactly, tactically, down to the tactical level, this is what's working. This is what's not working. Even if it's a color combination for example. That science is critical. >> Yeah, absolutely. Because we are able to cover the entire marketing life cycle of that they're trying to reach their customers. We cover off on email. We have mobile web to app. We have organic, we have search. No matter what you can look at that purview under a Branch lens. So we are just providing not just the accurate attribution down to the post-install, what happens after that, but also a more holistic view of everything that's happening on mobile. So then you can stitch all that together and really look at which ones are actually performing so you could see exactly which campaigns attributed directly to what amount of spend or which campaigns helped us understand the true lifetime long term value of customers, let's say in this case who ordered delivery or pickup. So to the kind of customer persona, it really helped. And also they actually were able to see Peet's because of our attribution, they saw actually a four and a half time increase in attributed purchases at the peak of the pandemic. And even since then, they're still seeing a three times increase in monthly attributed purchases. So because they actually have the view across everything that they're doing, we're able to provide that insight. >> That insight is so critical these days, like we mentioned earlier talking about real time data. Well we expect the experiences to be real time. And I expect that when I go back on the app they're going to know what I ordered last time. Maybe I want that again. Maybe I want to be able to change that, but I want them to know enough about me in a non creepy way. Give me that seamless experience that I'm expecting because of course that drives me to come back over and over again and spend way too much money there which I'm guilty of, guilty as charged. >> Coffee is totally fine. >> Right? Thank you. Thank you so much for validating that. I appreciate that. But talk to me about, as we are kind of wrapping things up here, the brick and mortars, it was such a challenge globally, especially the mom and pops to be able to convert quickly and figure out how do we reach a digital audience? How do we get our customers to be loyal? What's some of the advice that you have for the brick and mortars or those quick service restaurants like Peet's who've been navigating this the last couple years now here we are in this interesting semi post pandemic I would like to believe world? >> Yeah, we're getting there slowly but surely, but yeah, it's really important for them to adapt as we kind of move into this semi post pandemic world, we're kind of in the middle of like a hybrid online, offline, are we in stores, are we ordering online? These brand and customer relationships are super complex. I think the mobile app is just one part of that. Customers really shouldn't have any problems getting from the content or item they're looking for, no matter if they're in the store, if they're in the app, if they're on the desktop, if they're checking their email, if they're perusing TikTok, the best customer relationships really are omnichannel in nature. So what I would say, the need for providing the stellar customer experience isn't going to go away. It's actually really key. Whether it's driving users from their mobile properties to the app, providing a great in-store experience, like the QR codes, customers are expecting a lot more than they did before the pandemic. So they're not really seeing these brand touch points as little silos. They're seeing one brand. So it really should feel like one brand you should speak to the customers as if it's one brand across every single device, channel, and platform, and really unify that experience for them. >> Absolutely. That's going to be I think for so many different brands, whether it's a brick and mortar QSR, that's going to be one of the defining competitive advantages. If they can give their end users a single brand experience across channels, and you mentioned TikTok, those channels are only going to grow. As are I think or expectations. I don't think anybody's going to go back to wanting less than they did two years ago, right? >> Absolutely. Absolutely. >> Well this has been great, Michelle, thank you so much for joining me, talking about Branch, what you guys are doing, mobile linking platform, mobile measurement platform, the deep links, what you were able to do with Peet's Coffee, a beloved brand since the 60s and so many others. We appreciate your insights, your time and the story that you shared. >> Thank you so much, Lisa. I hope you have a great rest of your day. >> You as well. For Michelle Lerner, I'm Lisa Martin. You're watching theCUBE's coverage of the AWS Showcase. Keep it right here. More great content coming up from theCUBE, the leader in live tech coverage. (gentle music)

(upbeat music) >> Welcome everyone to theCUBE's presentation of the AWS Startup Showcase. Topic is MarTech: Emerging Cloud-Scale Experience. This is season two, episode three of the ongoing series covering the exciting startups from the AWS ecosystem. Talk about their value proposition and their company and all the good stuff that's going on. I'm your host, John Furrier. And today we're excited to be joined by Manyam Mallela who's the co-founder and head of AI at Blueshift. Great to have you on here to talk about the Blueshift-Intelligent Customer Engagement, Made Simple. Thanks for joining us today. >> Thank you, John. Thank you for having me. >> So last time we did our intro video. We put it out in the web. Got great feedback. One of the things that we talked about, which is resonating out there in the viral Twitter sphere and in the thought leadership circles is this concept that you mentioned called 10X marketer. That idea that you have a solution that can provide 10X value. Kind of a riff on the 10X engineer in the DevOps cloud world. What does it mean? And how does someone get there? >> Yeah, fantastic. I think that's a great way to start our discussion. I think a lot of organizations, especially as of this current economic environment are looking to say, I have limited resources, limited budgets, how do I actually achieve digital and customer engagement that helps move the needle for my key metrics, whether it's average revenue per user, lifetime value of the user and frequent interactions. Above all, the more frequently a brand is able to interact with their customers, the better they understand them, the better they can actually engage them. And that usually leads to long term good outcomes for both customer and the brand and the organizations. So the way I see 10X marketer is that you need to have tools that give you that speed and agility without hindering your ability to activate any of the campaigns or experience that you want to create. And I see the roadblocks usually for many organizations, is that kind of threefold. One is your data silos. Usually data that is on your sites, does not talk to your app data, does not talk to your social data, does not talk to your CRM data and so forth. So how do I break those silos? The second is channel silos. I actually have customers who are only engaging on email or some are on email and mobile apps. Some are on email and mobile apps and maybe the OTT TV in a Roku or one of the connected TV experiences, or maybe in the future, another Web3 environments. How do I actually break those channel silos so that I get a comprehensive view of the customer and my marketing team can engage with all of them in respect to the channel? So break the channel silos. And the last part, what I call like some of the little talked about is I call the inside silo, which is that, not only do you need to have the data, but you also have to have a common language to share and talk about within your organizations. What are we learning from our customers? What do we translate our learning and insight on this common data platform or fabric into an action? And that requires the shared language of how do I actually know my customers and what do I do with them? Like either the inside silo as well. I think a lot of times organizations do get into this habit like each one speaks their own language, but they don't actually are talking the common language of what did we actually know about the real customer there. >> Yeah, and I think that's a great conversation because there's two, when you hear 10X marketer or 10X conversations, it implies a couple things. One is you're breaking an old way and bringing in something new. And the new is a force multiplier, in this case, 10X marketer. But this is the cloud scale so marketing executives, chiefs, staffs, chiefs of staffs of CMOs and their staffs. They want to get that scale. So marketing at scale is now the table stakes. Now budget constraints are there as well. So you're starting to see, okay, I need to do more with less. Now the big question comes up is ROI. So I want to have AI. I want to have all these force multipliers. What do I got to do with the old? How do I handle that? How do I bring the new in and operationalize it? And if that's the case, I'm making a change. So I have to ask you, what's your view on the ROI of AI marketing, because this is a key component 'cause you've got scale factor here. You've got to force multiplier opportunity. How do you get that ROI on the table? >> I think that as you rightly said, it's table stakes. And I think the ROI of AI marketing starts with one very key simple premise that today some of the tools allow you to do things one at a time. So I can actually say, "can I run this campaign today?" And you can scramble your team, hustle your way, get everybody involved and run that campaign. And then tomorrow I'd say like, Hey, I looked at the results. Can I do this again? And they're like, oh, we just asked for all of us to get that done. How do I do it tomorrow? How do I do it next week? How do I do it for every single week for the rest of the year? That's where I think the AI marketing is essentially taking your insight, taking your creativity, and creating a platform and a tool that allows you to run this every single day. And that's agility at scale. That is not only a scale of the customer base, but scale across time. And that AI-based automation is the key ROI piece for a lot of AI marketing practitioners. So Forrester, for example, did a comprehensive total economic impact study with our customers. And what they found out was actually the 781% ROI that they reported in that particular report is based on three key factors. One is being able to do experiences that are intelligent at scale, day in and day out. So do your targeting, do your recommendations. Not just one day, but do it every single day. And don't hold back yourself on being able to do that. >> I think they got to get the return. They got to get the sales too. This is the numbers. >> That's right. They actually have real dollars, real numbers attached to it. They have a calculator. You can actually go in and plug your own numbers and get what you might expect from your existing customer base. The second is that once you have a unified platform like ours, the 10X marketer that we're talking about is actually able to do more. It's sometimes actually, it's kind of counterintuitive to think that a smaller team does more. But in reality, what we have seen, that is the case. When you actually have the right tools, the smaller teams actually achieve more. And that's the redundant operations, conflicting insights that go away into something more coherent and comprehensive. And that's the second insight that they found. And the third is just having reporting and all of the things in one place means that you can amplify it. You can amplify it across your paid media channels. You can amplify it across your promotions programs and other partnerships that you're running. >> That's the key thing about platforms that people don't understand is that you have a platform and it enables a lot of value. In this case, force multiplier value. It enables more value than you pay for it. But the key is it enables customers to do things without a line of code, meaning it's a platform. They're innovating on top of it. And that's, I think, where the ROI comes in and this leads me where the next question is. I wanted to ask you is, not to throw a wet blanket on the MarTech industry, but I got to think of when I hear marketing automation, I kind of think old. I think old, inadequate antiquated technologies. I think email blasting and just some boring stuff that just gets siloed or it's bespoke from something else. Are marketing automation tools created equal? Does something like, what you guys are doing with SmartHub? Change that, and can you just talk about that 'cause it's not going to go away. It's just another level that's going to be abstracted away under the coverage. >> Yeah, great question. Certainly, email marketing has been practiced for two or three decades now and in some form or another. I think we went from essentially what people call list-based marketing. I have a list, let me keep blasting the same message to everybody and then hopefully something will come out of it. A little bit more of saying, then they can, okay, maybe now I have CRM database and can I do database marketing, which they will call like, "Hey, Hi John. Hi Manyam", which is the first name. And that's all they think will get the customer excited about because you'll call them by name, which is certainly helpful, but not enough. I think now what we call like, the new age that we live in is that we call it graph-based marketing. And the way we materialize that is that every single user is interacting with a brand with their offerings. So that this interaction graph that's happening across millions of customers, across thousands of content articles, videos, shows, products, items, and that graph actually has much richer knowledge of what the customer wants than the first names or list-based ones. So I think the next evolution of marketing automation, even though the industry has been there a while, there is a step change in what can actually be done at scale. And which is taking that interaction graph and making that a part of the experience for the customer, and that's what we enable. That's why we do think of that as a big step change from how people are being practicing list-based marketing. And within that, certainly there is a relation of curve as to how people approach AI marketing and they are in a different spectrum. Some people are still at list-based marketing. Some people are database marketing. And hopefully will move them to this new interaction graph-based marketing. >> Yeah and I think the context is key. I like how you bring up the graph angle on this because the graph databases imply there's a lot of different optionality around what's happened contextually both over time and currently and it adds to it. Makes it smarter. It's not just siloed, just one dimensional. It feels like it's got a lot there. This is clearly I'm a big fan of and I think this is the way to go. As you get more personalization, you get more data. Graphic database makes a lot of sense. So I have to ask you, this is a really cutting edge value proposition, who are the primary buyers and users in an organization that you guys are working with? >> Yeah, great question. So we typically have CMO organizations approaching us with this problem and they usually talk to their CIO organizations, their counterparts, and the chief information officers have been investing in data fabrics, data lakes, data warehouses for the better part of last decade or two, and have some very cutting edge technology that goes into organizing all this data. But that doesn't still solve the problem of how do I take this data and make a meaningful, relevant, authentic experience for the customer. That's the CMO problem. And CMO are now challenge with creating product level experience with every interaction and that's where we coming. So the CMO are the buyers of our SmartHub CDP platform. And we're looking for consolidating hundreds of tools that they had in the past and making that one or two channel marketers. Actually, the 10X marketer that we talk about. And you need the right tool on top of your data lakes and data warehouses to be able to do that. So CMO are also the real drivers of using this technology. >> I think that also place the ROI equation around ROI and having that unified platform. Great call out there. I got to ask you the question here 'cause this comes up a lot and when I hear you talking, I think, okay, all the great stuff you guys have there. But if I'm a company, I want to make my core competencies mine. I don't really want to outsource or buy something that's going to be core to my business. But at the same time as market shifts, the business changes. And sometimes people don't even know what business they're in at the end of the day. And as it gets more complicated too, by the way. So the question comes up with companies and I can see this clearly, do I buy it? Do I build it? When it comes to AI because that's a core competency. Wait a minute, AI. I'm going to maybe buy some chatbot technology. That's not really AI, but it feels like AI, but I'm a company, I want to buy it or build it. That's a choice. What do you see there? 'Cause you guys have a very comprehensive platform. It's hard to replicate, imitates, inimitable. So what's your customers doing with respect buy and build? And where do they get the core competency? What do they get to have as a core competency? >> Fantastic. I think certainly, AI as it applies to at the organization level, I've seen this at my previous organization that I was part of, and there will be product and financial applications that are using AI for the service of that organization. So we do see, depending upon the size of the organization having in-house AI and data science teams. They are focused on these long term problems that they are doing as part of their product itself. Adjacent to that, the CMO organization gets some resources, but not certainly a lot. I think the CMO organization is usually challenged with the task, but not given the hundred people data science and engineering team to be able to go solve that. So what we see among our customer base is that they need agile platform to do most of the things that they need to do on a day to day basis, but augmented with what our in-house data science they have. So we are an extensible platform. What we have seen is that half of our customers use us solely for the AI needs. The other half certainly uses both AI modules that we provide and are actually augmented with things that they've already built. And we do not have a fight in that ring. But we do acknowledge and we do provide the right hooks for getting the data out of our system and bringing their AI back into our system. And we think that at the end of the day, if you want agility for the CMO, there should not be any barriers. >> It's like they're in the data business and that's the focus. So I think with what I hear you saying is that with your technology and platform, you're enabling to get them to be in the data business as fast as possible. >> That's right. >> Versus algorithm business, which they could add to over time. >> Certainly they could add to. But I think the bulk of competencies for the CMO are on the creative side. And certainly wrangling with data pipelines day in and day out and wondering what actually happened to a pipeline in the middle of the night is not probably what they would want to focus on. >> Not their core confidence. Yeah, I got that. >> That's right. >> You can do all the heavy lifting. I love that. I got to ask you on the Blueshift side on customer experience consumption. how can someone experience the product before buying? Is there a trial or POC? What's the scale and scope of operationalizing and getting the Blueshift value proposition in them? >> Yeah, great. So we actually recently released a fantastic way to experience our product. So if you go to our website, there's only one call-to-action saying, explore Blueshift. And if you click on that, without asking, anything other than your business email address, you're shown the full product. You're given a guided tour of all the possibilities. So you can actually experience what your marketing team would be doing in the product. And they call it Project Rover. We launched it very recently and we are seeing fantastic reception to that. I think a lot of times, as you said, there is that question mark of like, I have a marketing team that is already doing X, Y, Z. Now you are asking me to implement Blueshift. How would they actually experience the product? And now they can go in and experience the product. It's a great way to get the gist of the product in 10 clicks. Much more than going through any number of videos or articles. I think people really want to say, let me do those 10 clicks. And I know what impression that I can get from platform. So we do think that's a great way to experience the product and it's easily available from the main website. >> It's in the value proposition. It isn't always a straight line. And you got that technology. And I got to ask from between your experience with the customers that you're talking to, prospects, and customers, where do you see yourself winning deals on Customer Engagement, Made Simple because the word customer engagement's been around for a while, and it's become, I won't say cliche, but there's been different generational evolutions of technology that made that possible. Obviously, we're living in an era of high velocity Omni-Channel, a lot of data, the graph databases you mentioned are in there, big part of it. Where are you winning deals? Where are customers pain points where you are solving that specifically? >> Yeah, great question. So the organizations that come to us usually have one of the dimensions of either they have offering complexity, which is what catalog of content or videos or items do they offer to the customers. And on the data complexity on the other side is to what the scale of customer base that I usually target. And that problem has not gone away. I think the customer engagement, even though has been around for a while, the problem of engaging those customers at scale hasn't gone away and it only is getting harder and harder and organizations that have, especially on what we call the business-to-consumer side where the bulk of what marketing organizations in a B2C segments are doing. I have tens to millions of customers and how do I engage them day in and day out. And I think that all that problem is only getting harder because consumer preferences keeps shifting all the time. >> And where's your sweet spot for your customer? What size? Can you just share the target organization? Is it medium enterprise, large B2C, B2B2C? What's the focus area? >> Yeah, great question. So we have seen like startups that are in Silicon Valley. I have now half a million monthly active users, how do I actually engage them to customers and clients like LendingTree and PayPal and Discovery and BBC who have been in the business for multiple decades, have tens of millions of customers that they're engaging with. So that's kind of our sweet spot. We are certainly not maybe for small shop with maybe a hundred plus customers. But as you reach the scale of tens of thousands of customers, you start seeing this problem. And then you start to look out for solutions that are beyond, especially list-based marketing and email blast. >> So as the scale, you can dial up and down, but you have to have some enough scale to get the data pattern. >> That's right. >> If I can connect the dots there. >> I would probably say, looking at a hundred thousand or more monthly active customer base, and then you're trying to ramp up your own growth based on what you're learning and to engage those customers. >> It's like a bulldozer. You need the heavy equipment. Great conversation. For the last minute we have here Manyam, give you a plug for the company. What's going on? What are you guys doing? What's new? Give some success stories, your latest achievements. Take a minute to give a plug for the company. >> Yeah, great. We have been recognized by Deloitte as the fastest growth startup two years in a row and continuing to be on that streak. We have released currently integrations with AWS partners and Snowflake partners and data lake partners that allow implementing Blueshift a much streamlined experience with bidirectional integrations. We have now hundred plus data connectors and data integrations in our system and that takes care of many of our needs. And now, I think organizations that have been budget constraint and are trying to achieve a lot with a small team are actually going to look at these solutions and say, "Can I get there?" and "Can I become that 10X marketing organization? And as you have said, agility at scale is very, very hard to achieve. Being able to take your marketing team and achieve 10X requires the right platform and the right solution. We are ready for it. >> And every company's in the data business that's the asset. You guys make that sing for them. It's good stuff. Love the 10X. Love the scale. Manyam Mallela, thanks for coming on. Co-founder, Head of AI at Blueshift. This is the AWS Startup Showcase season two, episode three of the ongoing series covering the exciting startups from the AWS ecosystem. I'm John Furrier, your host. Thanks for watching. >> Thank you, John. (upbeat music)

(upbeat music) >> Hello, everyone. Welcome to the theCUBE's presentation of the AWS Startup Showcase. The theme, this showcase is MarTech, the emerging cloud scale customer experiences. Season two of episode three, the ongoing series covering the startups, the hot startups, talking about analytics, data, all things MarTech. I'm your host, John Furrier, here joined by Christian Wiklund, founder and CEO of unitQ here, talk about harnessing the power of user feedback to empower marketing. Thanks for joining us today. >> Thank you so much, John. Happy to be here. >> In these new shifts in the market, when you got cloud scale, open source software is completely changing the software business. We know that. There's no longer a software category. It's cloud, integration, data. That's the new normal. That's the new category, right? So as companies are building their products, and want to do a good job, it used to be, you send out surveys, you try to get the product market fit. And if you were smart, you got it right the third, fourth, 10th time. If you were lucky, like some companies, you get it right the first time. But the holy grail is to get it right the first time. And now, this new data acquisition opportunities that you guys in the middle of that can tap customers or prospects or end users to get data before things are shipped, or built, or to iterate on products. This is the customer feedback loop or data, voice of the customer journey. It's a gold mine. And it's you guys, it's your secret weapon. Take us through what this is about now. I mean, it's not just surveys. What's different? >> So yeah, if we go back to why are we building unitQ? Which is we want to build a quality company. Which is basically, how do we enable other companies to build higher quality experiences by tapping into all of the existing data assets? And the one we are in particularly excited about is user feedback. So me and my co-founder, Nik, and we're doing now the second company together. We spent 14 years. So we're like an old married couple. We accept each other, and we don't fight anymore, which is great. We did a consumer company called Skout, which was sold five years ago. And Skout was kind of early in the whole mobile first. I guess, we were actually mobile first company. And when we launched this one, we immediately had the entire world as our marketplace, right? Like any modern company. We launch a product, we have support for many languages. It's multiple platforms. We have Android, iOS, web, big screens, small screens, and that brings some complexities as it relates to staying on top of the quality of the experience because how do I test everything? >> John: Yeah. >> Pre-production. How do I make sure that our Polish Android users are having a good day? And we found at Skout, personally, like I could discover million dollar bugs by just drinking coffee and reading feedback. And we're like, "Well, there's got to be a better way to actually harness the end user feedback. That they are leaving in so many different places." So, you know what, what unitQ does is that we basically aggregate all different sources of user feedback, which can be app store reviews, Reddit posts, Tweets, comments on your Facebook ads. It can be better Business Bureau Reports. We don't like to get to many of those, of course. But really, anything on the public domain that mentions or refers to your product, we want to ingest that data in this machine, and then all the private sources. So you probably have a support system deployed, a Zendesk, or an Intercom. You might have a chatbot like an Ada, or and so forth. And your end user is going to leave a lot of feedback there as well. So we take all of these channels, plug it into the machine, and then we're able to take this qualitative data. Which and I actually think like, when an end user leaves a piece of feedback, it's an act of love. They took time out of the day, and they're going to tell you, "Hey, this is not working for me," or, "Hey, this is working for me," and they're giving you feedback. But how do we package these very messy, multi-channel, multiple languages, all over the place data? How can we distill it into something that's quantifiable? Because I want to be able to monitor these different signals. So I want to turn user feedback into time series. 'Cause with time series, I can now treat this the same way as Datadog treats machine logs. I want to be able to see anomalies, and I want to know when something breaks. So what we do here is that we break down your data in something called quality monitors, which is basically machine learning models that can aggregate the same type of feedback data in this very fine grained and discrete buckets. And we deploy up to a thousand of these quality monitors per product. And so we can get down to the root cause. Let's say, passive reset link is not working. And it's in that root cause, the granularity that we see that companies take action on the data. And I think historically, there has been like the workflow between marketing and support, and engineering and product has been a bit broken. They've been siloed from a data perspective. They've been siloed from a workflow perspective, where support will get a bunch of tickets around some issue in production. And they're trained to copy and paste some examples, and throw it over the wall, file a Jira ticket, and then they don't know what happens. So what we see with the platform we built is that these teams are able to rally around the single source of troop or like, yes, passive recent link seems to have broken. This is not a user error. It's not a fix later, or I can't reproduce. We're looking at the data, and yes, something broke. We need to fix it. >> I mean, the data silos a huge issue. Different channels, omnichannel. Now, there's more and more channels that people are talking in. So that's huge. I want to get to that. But also, you said that it's a labor of love to leave a comment or a feedback. But also, I remember from my early days, breaking into the business at IBM and Hewlett-Packard, where I worked. People who complain are the most loyal customers, if you service them. So it's complaints. >> Christian: Yeah. >> It's leaving feedback. And then, there's also reading between the lines with app errors or potentially what's going on under the covers that people may not be complaining about, but they're leaving maybe gesture data or some sort of digital trail. >> Yeah. >> So this is the confluence of the multitude of data sources. And then you got the siloed locations. >> Siloed locations. >> It's complicated problem. >> It's very complicated. And when you think about, so I started, I came to Bay Area in 2005. My dream was to be a quant analyst on Wall Street, and I ended up in QA at VMware. So I started at VMware in Palo Alto, and didn't have a driver's license. I had to bike around, which was super exciting. And we were shipping box software, right? This was literally a box with a DVD that's been burned, and if that DVD had bugs in it, guess what it'll be very costly to then have to ship out, and everything. So I love the VMware example because the test cycles were long and brutal. It was like a six month deal to get through all these different cases, and they couldn't be any bugs. But then as the industry moved into the cloud, CI/CD, ship at will. And if you look at the modern company, you'll have at least 20 plus integrations into your product. Analytics, add that's the case, authentication, that's the case, and so forth. And these integrations, they morph, and they break. And you have connectivity issues. Is your product working as well on Caltrain, when you're driving up and down, versus wifi? You have language specific bugs that happen. Android is also quite a fragmented market. The binary may not perform as well on that device, or is that device. So how do we make sure that we test everything before we ship? The answer is, we can't. There's no company today that can test everything before the ship. In particular, in consumer. And the epiphany we had at our last company, Skout, was that, "Hey, wait a minute. The end user, they're testing every configuration." They're sitting on the latest device, the oldest device. They're sitting on Japanese language, on Swedish language. >> John: Yeah. >> They are in different code paths because our product executed differently, depending on if you were a paid user, or a freemium user, or if you were certain demographical data. There's so many ways that you would have to test. And PagerDuty actually had a study they came out with recently, where they said 51% of all end user impacting issues are discovered first by the end user, when they serve with a bunch of customers. And again, like the cool part is, they will tell you what's not working. So now, how do we tap into that? >> Yeah. >> So what I'd like to say is, "Hey, your end user is like your ultimate test group, and unitQ is the layer that converts them into your extended test team." Now, the signals they're producing, it's making it through to the different teams in the organization. >> I think that's the script that you guys are flipping. If I could just interject. Because to me, when I hear you talking, I hear, "Okay, you're letting the customers be an input into the product development process." And there's many different pipelines of that development. And that could be whether you're iterating, or geography, releases, all kinds of different pipelines to get to the market. But in the old days, it was like just customer satisfaction. Complain in a call center. >> Christian: Yeah. >> Or I'm complaining, how do I get support? Nothing made itself into the product improvement, except for slow moving, waterfall-based processes. And then, maybe six months later, a small tweak could be improved. >> Yes. >> Here, you're taking direct input from collective intelligence. Okay. >> Is that have input and on timing is very important here, right? So how do you know if the product is working as it should in all these different flavors and configurations right now? How do you know if it's working well? And how do you know if you're improving or not improving over time? And I think the industry, what can we look at, as far as when it relates to quality? So I can look at star ratings, right? So what's the star rating in the app store? Well, star ratings, that's an average over time. So that's something that you may have a lot of issues in production today, and you're going to get dinged on star ratings over the next few months. And then, it brings down the score. NPS is another one, where we're not going to run NPS surveys every day. We're going to run it once a quarter, maybe once a month, if we're really, really aggressive. That's also a snapshot in time. And we need to have the finger on the pulse of product quality today. I need to know if this release is good or not good. I need to know if anything broke. And I think that real time aspect, what we see as stuff sort of bubbles up the stack, and not into production, we see up to a 50% reduction in time to fix these end user impacting issues. And I think, we also need to appreciate when someone takes time out of the day to write an app review, or email support, or write that Reddit post, it's pretty serious. It's not going to be like, "Oh, I don't like the shade of blue on this button." It's going to be something like, "I got double billed," or "Hey, someone took over my account," or, "I can't reset my password anymore. The CAPTCHA, I'm solving it, but I can't get through to the next phase." And we see a lot of these trajectory impacting bugs and quality issues in these work, these flows in the product that you're not testing every day. So if you work at Snapchat, your employees probably going to use Snapchat every day. Are they going to sign up every day? No. Are they going to do passive reset every day? No. And these things are very hard to instrument, lower in the stack. >> Yeah, I think this is, and again, back to these big problems. It's smoke before fire, and you're essentially seeing it early with your process. Can you give an example of how this new focus or new mindset of user feedback data can help customers increase their experience? Can you give some examples, 'cause folks watching and be like, "Okay, I love this value. Sell me on this idea, I'm sold. Okay, I want to tap into my prospects, and my customers, my end users to help me improve my product." 'Cause again, we can measure everything now with data. >> Yeah. We can measure everything. we can even measure quality these days. So when we started this company, I went out to talk to a bunch of friends, who are entrepreneurs, and VCs, and board members, and I asked them this very simple question. So in your board meetings, or on all hands, how do you talk about quality of the product? Do you have a metric? And everyone said, no. Okay. So are you data driven company? Yes, we're very data driven. >> John: Yeah. Go data driven. >> But you're not really sure if quality, how do you compare against competition? Are you doing as good as them, worse, better? Are you improving over time, and how do you measure it? And they're like, "Well, it's kind of like a blind spot of the company." And then you ask, "Well, do you think quality of experience is important?" And they say, "Yeah." "Well, why?" "Well, top of fund and growth. Higher quality products going to spread faster organically, we're going to make better store ratings. We're going to have the storefronts going to look better." And of course, more importantly, they said the different conversion cycles in the product box itself. That if you have bugs and friction, or an interface that's hard to use, then the inputs, the signups, it's not going to convert as well. So you're going to get dinged on retention, engagement, conversion to paid, and so forth. And that's what we've seen with the companies we work with. It is that poor quality acts as a filter function for the entire business, if you're a product led company. So if you think about product led company, where the product is really the centerpiece. And if it performs really, really well, then it allows you to hire more engineers, you can spend more on marketing. Everything is fed by this product at them in the middle, and then quality can make that thing perform worse or better. And we developed a metric actually called the unitQ Score. So if you go to our website, unitq.com, we have indexed the 5,000 largest apps in the world. And we're able to then, on a daily basis, update the score. Because the score is not something you do once a month or once a quarter. It's something that changes continuously. So now, you can get a score between zero and 100. If you get the score 100, that means that our AI doesn't find any quality issues reported in that data set. And if your score is 90, that means that 10% will be a quality issue. So now you can do a lot of fun stuff. You can start benchmarking against competition. So you can see, "Well, I'm Spotify. How do I rank against Deezer, or SoundCloud, or others in my space?" And what we've seen is that as the score goes up, we see this real big impact on KPI, such as conversion, organic growth, retention, ultimately, revenue, right? And so that was very satisfying for us, when we launched it. quality actually still really, really matters. >> Yeah. >> And I think we all agree at test, but how do we make a science out of it? And that's so what we've done. And when we were very lucky early on to get some incredible brands that we work with. So Pinterest is a big customer of ours. We have Spotify. We just signed new bank, Chime. So like we even signed BetterHelp recently, and the world's largest Bible app. So when you look at the types of businesses that we work with, it's truly a universal, very broad field, where if you have a digital exhaust or feedback, I can guarantee you, there are insights in there that are being neglected. >> John: So Chris, I got to. >> So these manual workflows. Yeah, please go ahead. >> I got to ask you, because this is a really great example of this new shift, right? The new shift of leveraging data, flipping the script. Everything's flipping the script here, right? >> Yeah. >> So you're talking about, what the value proposition is? "Hey, board example's a good one. How do you measure quality? There's no KPI for that." So it's almost category creating in its own way. In that, this net new things, it's okay to be new, it's just new. So the question is, if I'm a customer, I buy it. I can see my product teams engaging with this. I can see how it can changes my marketing, and customer experience teams. How do I operationalize this? Okay. So what do I do? So do I reorganize my marketing team? So take me through the impact to the customer that you're seeing. What are they resonating towards? Obviously, getting that data is key, and that's holy gray, we all know that. But what do I got to do to change my environment? What's my operationalization piece of it? >> Yeah, and that's one of the coolest parts I think, and that is, let's start with your user base. We're not going to ask your users to ask your users to do something differently. They're already producing this data every day. They are tweeting about it. They're putting in app produce. They're emailing support. They're engaging with your support chatbot. They're already doing it. And every day that you're not leveraging that data, the data that was produced today is less valuable tomorrow. And in 30 days, I would argue, it's probably useless. >> John: Unless it's same guy commenting. >> Yeah. (Christian and John laughing) The first, we need to make everyone understand. Well, yeah, the data is there, and we don't need to do anything differently with the end user. And then, what we do is we ask the customer to tell us, "Where should we listen in the public domain? So do you want the Reddit post, the Trustpilot? What channels should we listen to?" And then, our machine basically starts ingesting that data. So we have integration with all these different sites. And then, to get access to private data, it'll be, if you're on Zendesk, you have to issue a Zendesk token, right? So you don't need any engineering hours, except your IT person will have to grant us access to the data source. And then, when we go live. We basically build up this taxonomy with the customers. So we don't we don't want to try and impose our view of the world, of how do you describe the product with these buckets, these quality monitors? So we work with the company to then build out this taxonomy. So it's almost like a bespoke solution that we can bootstrap with previous work we've done, where you don't have these very, very fine buckets of where stuff could go wrong. And then what we do is there are different ways to hook this into the workflow. So one is just to use our products. It's a SaaS product as anything else. So you log in, and you can then get this overview of how is quality trending in different markets, on different platforms, different languages, and what is impacting them? What is driving this unitQ Score that's not good enough? And all of these different signals, we can then hook into Jira for instance. We have a Jira integration. We have a PagerDuty integration. We can wake up engineers if certain things break. We also tag tickets in your support system, which is actually quite cool. Where, let's say, you have 200 people, who wrote into support, saying, "I got double billed on Android." It turns out, there are some bugs that double billed them. Well, now we can tag all of these users in Zendesk, and then the support team can then reach out to that segment of users and say, "Hey, we heard that you had this bug with double billing. We're so sorry. We're working on it." And then when we push fix, we can then email the same group again, and maybe give them a little gift card or something, for the thank you. So you can have, even big companies can have that small company experience. So, so it's groups that use us, like at Pinterest, we have 800 accounts. So it's really through marketing has vested interest because they want to know what is impacting the end user. Because brand and product, the lines are basically gone, right? >> John: Yeah. >> So if the product is not working, then my spend into this machine is going to be less efficient. The reputation of our company is going to be worse. And the challenge for marketers before unitQ was, how do I engage with engineering and product? I'm dealing with anecdotal data, and my own experience of like, "Hey, I've never seen these type of complaints before. I think something is going on." >> John: Yeah. >> And then engineering will be like, "Ah, you know, well, I have 5,000 bugs in Jira. Why does this one matter? When did it start? Is this a growing issue?" >> John: You have to replicate the problem, right? >> Replicate it then. >> And then it goes on and on and on. >> And a lot of times, reproducing bugs, it's really hard because it works on my device. Because you don't sit on that device that it happened on. >> Yup. >> So now, when marketing can come with indisputable data, and say, "Hey, something broke here." And we see the same with support. Product engineering, of course, for them, we talk about, "Hey, listen, you you've invested a lot in observability of your stack, haven't you?" "Yeah, yeah, yeah." "So you have a Datadog in the bottom?" "Absolutely." "And you have an APP D on the client?" "Absolutely." "Well, what about the last mile? How the product manifests itself? Shouldn't you monitor that as well using machines?" They're like, "Yeah, that'd be really cool." (John laughs) And we see this. There's no way to instrument everything, lowering the stack to capture these bugs that leak out. So it resonates really well there. And even for the engineers who's going to fix it. >> Yeah. >> I call it like empathy data. >> Yup. >> Where I get assigned a bug to fix. Well, now, I can read all the feedback. I can actually see, and I can see the feedback coming in. >> Yeah. >> Oh, there's users out there, suffering from this bug. And then when I fix it and I deploy the fix, and I see the trend go down to zero, and then I can celebrate it. So that whole feedback loop is (indistinct). >> And that's real time. It's usually missed too. This is the power of user feedback. You guys got a great product, unitQ. Great to have you on. Founder and CEO, Christian Wiklund. Thanks for coming on and sharing, and showcase. >> Thank you, John. For the last 30 seconds, the minute we have left, put a plug in for the company. What are you guys looking for? Give a quick pitch for the company, real quick, for the folks out there. Looking for more people, funding status, number of employees. Give a quick plug. >> Yes. So we raised our A Round from Google, and then we raised our B from Excel that we closed late last year. So we're not raising money. We are hiring across go-to-markets, engineering. And we love to work with people, who are passionate about quality and data. We're always, of course, looking for customers, who are interested in upping their game. And hey, listen, competing with features is really hard because you can copy features very quickly. Competing with content. Content is commodity. You're going to get the same movies more or less on all these different providers. And competing on price, we're not willing to do. You're going to pay 10 bucks a month for music. So how do you compete today? And if your competitor has a better fine tuned piano than your competitor will have better efficiencies, and they're going to retain customers and users better. And you don't want to lose on quality because it is actually a deterministic and fixable problem. So yeah, come talk to us if you want to up the game there. >> Great stuff. The iteration lean startup model, some say took craft out of building the product. But this is now bringing the craftsmanship into the product cycle, when you can get that data from customers and users. >> Yeah. >> Who are going to be happy that you fixed it, that you're listening. >> Yeah. >> And that the product got better. So it's a flywheel of loyalty, quality, brand, all off you can figure it out. It's the holy grail. >> I think it is. It's a gold mine. And every day you're not leveraging this assets, your use of feedback that's there, is a missed opportunity. >> Christian, thanks so much for coming on. Congratulations to you and your startup. You guys back together. The band is back together, up into the right, doing well. >> Yeah. We we'll check in with you later. Thanks for coming on this showcase. Appreciate it. >> Thank you, John. Appreciate it very much. >> Okay. AWS Startup Showcase. This is season two, episode three, the ongoing series. This one's about MarTech, cloud experiences are scaling. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>> Hey everyone, welcome to theCUBE's coverage of the AWS startup showcase. This is season two, episode three of our ongoing series featuring AWS and its big ecosystem of partners. This particular season is focused on MarTech, emerging cloud scale customer experiences. I'm your host, Lisa Martin, and I'm pleased to be joined by James Fang, the VP of product marketing at mparticle. James, welcome to the program. Great to have you on. >> Thanks for having me. >> Tell us a little bit about mparticle, what is it that you guys do? >> Sure, so we're mparticle, we were founded in 2013, and essentially we are a customer data platform. What we do is we help brands collect and organize their data. And their data could be coming from web apps, mobile apps, existing data sources like data warehouses, data lakes, et cetera. And we help them help them organize it in a way where they're able to activate that data, whether it's to analyze it further, to gather insights or to target them with relevant messaging, relevant offers. >> What were some of the gaps in the market back then as you mentioned 2013, or even now, that mparticle is really resolving so that customers can really maximize the value of their customer's data. >> Yeah. So the idea of data has actually been around for a while, and you may have heard the buzzword 360 degree view of the customer. The problem is no one has really been actually been able to, to achieve it. And it's actually, some of the leading analysts have called it a myth. Like it's a forever ending kind of cycle. But where we've kind of gone is, first of all customer expectations have really just inflated over the years, right? And part of that was accelerated due to COVID, and the transformation we saw in the last two years, right. Everyone used to, you know, have maybe a digital footprint, as complimentary perhaps to their physical footprint. Nowadays brands are thinking digital first, for obvious reasons. And the data landscape has gotten a lot more complex, right? Brands have multiple experiences, on different screens, right? And, but from the consumer perspective, they want a complete end to end experience, no matter how you're engaging with the brand. And in order to, for a brand to deliver that experience they have to know, how the customers interacted before in each of those channels, and be able to respond in as real time as possible, to those experiences. >> So I can start an interaction on my iPad, maybe carry it through or continue it on my laptop, go to my phone. And you're right, as a, as a consumer, I want the experience across all of those different media to be seamless, to be the same, to be relevant. You talk about the customer 360, as a marketer I know that term well. It's something that so many companies use, interesting that you point out that it's really been, largely until companies like mparticle, a myth. It's one of those things though, that everybody wants to achieve. Whether we're talking about healthcare organization, a retailer, to be able to know everything about a customer so that they can deliver what's increasingly demanded that personalized, relevant experience. How does mparticle fill some of the gaps that have been there in customer 360? And do you say, Hey, we actually deliver a customer 360. >> Yeah, absolutely. So, so the reason it's been a myth is for the most part, data has been- exists either in silos, or it's kind of locked behind this black box that the central data engineering team or sometimes traditionally referred to as IT, has control over, right? So brands are collecting all sorts of data. They have really smart people working on and analyzing it. You know, being able to run data science models, predictive models on it, but the, the marketers and the people who want to draw insights on it are asking how do I get it in, in my hands? So I can use that data for relevant targeting messaging. And that's exactly what mparticle does. We democratize access to that data, by making it accessible in the very tools that the actual business users are are working in. And we do that in real time, you don't have to wait for days to get access to data. And the marketers can even self-service, they're able to for example, build audiences or build computed insights, such as, you know, average order value of a customer within the tool themselves. The other main, the other main thing that mparticle does, is we ensure the quality of that data. We know that activation is only as as good, when you can trust that data, right? When there's no mismatching, you know, first name last names, identities that are duplicated. And so we put a lot of effort, not only in the identity resolution component of our product but also being able to ensure that the consistency of that data when it's being collected meets the standard that you need. >> So give us a, a picture, kind of a topology of a, of a customer data platform. And what are some of the key components that it contains, then I kind of want to get into some of the use cases. >> Yeah. So at, at a core, a lot of customer data platforms look similar. They're responsible first of all for the collection of data, right? And again, that could be from web mobile sources, as well as existing data sources, as well as third party apps, right? For example, you may have e-commerce data in a Shopify, right. Or you may have, you know, a computer model from a, from a warehouse. And then the next thing is to kind of organize it somehow, right? And the most common way to do that is to unify it, using identity resolution into this idea of customer profiles, right. So I can look up everything that Lisa or James has done, their whole historical record. And then the third thing is to be able to kind of be able to draw some insights from that, whether to be able to build an audience membership on top of that, build a predictive model, such as the churn risk model or lifetime value of that customer. And finally is being able to activate that data, so you'll be able to push that data again, to those relevant downstream systems where the business users are actually using that data to, to do their targeting, or to do more interesting things with it. >> So for example, if I go to the next Warrior's game, which I predict they're going to win, and I have like a mobile app of the stadium or the team, how, and I and I'm a season ticket holder, how can a customer data platform give me that personalized experience and help to, yeah, I'd love to kind of get it in that perspective. >> Yeah. So first of all, again, in this modern day and age consumers are engaging with brands from multiple devices, and their attention span, frankly, isn't that long. So I may start off my day, you know, downloading the official warriors app, right. And I may be, you know browsing from my mobile phone, but I could get distracted. I've got to go join a meeting at work, drop off my kids or whatever, right? But later in the day I had in my mind, I may be interested in purchasing tickets or buying that warriors Jersey. So I may return to the website, or even the physical store, right. If, if I happen to be in the area and what the customer data platform is doing in the background, is associating and connecting all those online and offline touchpoints, to that user profile. And then now, I have a mar- so let's say I'm a marker for the golden state warriors. And I see that, you know, this particular user has looked at my website even added to their cart, you know, warriors Jersey. I'm now able to say, Hey, here's a $5 promotional coupon. Also, here's a special, limited edition. We just won, you know, the, the Western conference finals. And you can pre-book, you know, the, you know the warriors championships Jersey, cross your fingers, and target that particular user with that promotion. And it's much more likely because we have that contextual data that that user's going to convert, than just blasting them on a Facebook or something like that. >> Right. Which all of us these days are getting less and less patient with, Is those, those broad blasts through social media and things like that. That was, I love that example. That was a great example. You talked about timing. One of the things I think that we've learned that's in very short supply, in the last couple of years is people's patience and tolerance. We now want things in nanoseconds. So, the ability to glean insights from data and act on it in real time is no longer really a nice to have that's really table stakes for any type of organization. Talk to us about how mparticle facilitates that real time data, from an insights perspective and from an activation standpoint. >> Yeah. You bring up a good point. And this is actually one of the core differentiators of mparticle compared to the other CDPs is that, our architecture from the ground up is built for real time. And the way we do that is, we use essentially a real time streaming architecture backend. Essentially all the data points that we collect and send to those downstream destinations, that happens in milliseconds, right? So the moment that that user, again, like clicks a button or adds something to their shopping cart, or even abandons that shopping cart, that downstream tool, whether it's a marketer, whether it's a business analyst looking at that data for intelligence, they get that data within milliseconds. And our audience computations also happens within seconds. So again, if you're, if you have a targeted list for a targeted campaign, those updates happen in real time. >> You gave an- you ran with the Warrior's example that I threw at you, which I love, absolutely. Talk to me. You must have though, a favorite cu- real world customer example of mparticle's that you think really articulates the value to organizations, whether it's to marketers operators and has some nice, tangible business outcomes. Share with me if you will, a favorite customer story. >> Yeah, definitely one of mine and probably one of the- our most well known's is we were actually behind the scenes of the Whopper jr campaign. So a couple of years ago, Burger King ran this really creative ad where the, effectively their goal was to get their mobile app out, as well as to train, you know, all of us back before COVID days, how to order on our mobile devices and to do things like curbside checkout. None of us really knew how to do that, right. And there was a challenge of course that, no one wants to download another app, right? And most apps get downloaded and get deleted right out away. So they ran this really creative promotion where, if you drove towards a McDonald's, they would actually fire off a text message saying, Hey, how about a Whopper for 99 cents instead? And you would, you would, you would receive a text message personalized just for you. And you'd be able to redeem that at any burger king location. So we were kind of the core infrastructure plumbing the geofencing location data, to partner of ours called radar, which handles you geofencing, and then send it back to a marketing orchestration vendor to be able to fire that targeted message. >> Very cool. I, I, now I'm hungry. You, but there's a fine line there between knowing that, okay, Lisa's driving towards McDonald's let's, you know, target her with an ad for a whopper, in privacy. How do you guys help organizations in any industry balance that? Cause we're seeing more and more privacy regulations popping up all over the world, trying to give consumers the ability to protect either the right to forget about me or don't use my data. >> Yeah. Great question. So the first way I want to respond to that is, mparticle's really at the core of helping brands build their own first party data foundation. And what we mean by that is traditionally, the way that brands have approached marketing is reliant very heavily on second and third party data, right? And most that second-third party data is from the large walled gardens, such as like a Facebook or a TikTok or a Snapchat, right? They're they're literally just saying, Hey find someone that is going to, you know fit our target profile. And that data is from people, all their activity on those apps. But with the first party data strategy, because the brand owns that data, we- we can guarantee that or the brands can guarantee to their customers it's ethically sourced, meaning it's from their consent. And we also help brands have governance policies. So for example, if the user has said, Hey you're allowed to collect my data, because obviously you want to run your business better, but I don't want any my information sold, right? That's something that California recently passed, with CPRA. Then brands can use mparticle data privacy controls to say, Hey, you can pass this data on to their warehouses and analytics platforms, but don't pass it to a platform like Facebook, which potentially could resell that data. >> Got it, Okay. So you really help put sort of the, the reigns on and allow those customers to make those decisions, which I know the mass community appreciates. I do want to talk about data quality. You talked about that a little bit, you know, and and data is the lifeblood of an organization, if it can really extract value from it and act on it. But how do you help organizations maintain the quality of data so that what they can do, is actually deliver what the end user customer, whether it's a somebody buying something on a, on a eCommerce site or or, a patient at a hospital, get what they need. >> Yeah. So on the data quality front, first of all I want to highlight kind of our strengths and differentiation in identity resolution. So we, we run a completely deterministic algorithm, but it's actually fully customizable by the customer depending on their needs. So for a lot of other customer data providers, platform providers out there, they do offer identity resolution, but it's almost like a black box. You don't know what happens. And they could be doing a lot of fuzzy matching, right. Which is, you know, probabilistic or predictive. And the problem with that is, let's say, you know, Lisa your email changed over the years and CDP platform may match you with someone that's completely not you. And now all of a sudden you're getting ads that completely don't fit you, or worse yet that brand is violating privacy laws, because your personal data is is being used to target another user, which which obviously should not, should not happen, right? So because we're giving our customers complete control, it's not a black box, it's transparent. And they have the ability to customize it, such as they can specify what identifiers matter more to them, whether they want to match on email address first. They might've drawn on a more high confidence identifier like a, a hash credit card number or even a customer ID. They have that choice. The second part about ensuring data quality is we act actually built in schema management. So as those events are being collected you could say that, for example, when when it's a add to cart event, I require the item color. I require the size. Let's say it's a fashion apparel. I require the size of it and the type of apparel, right? And if, if data comes in with missing fields, or perhaps with fields that don't match the expectation, let's say you're expecting small, medium, large and you get a Q, you know Q is meaningless data, right? We can then enforce that and flag that as a data quality violation and brands can complete correct that mistake to make sure again, all the data that's flowing through is, is of value to them. >> That's the most important part is, is to make sure that the data has value to the organization, and of course value to whoever it is on the other side, the, the end user side. Where should customers start, in terms of working with you guys, do you recommend customers buy an all in one marketing suite? The best, you know, build a tech stack of best of breed? What are some of those things that you recommend for folks who are going, all right, We, maybe we have a CDP it's been under delivering. We can't really deliver that customer 360, mparticle, help us out. >> Yeah, absolutely. Well, the best part about mparticle is you can kind of deploy it in phases, right. So if you're coming from a world where you've deployed a, all in one marketing suite, like a sales force in Adobe, but you're looking to maybe modernize pieces of a platform mparticle can absolutely help with that initial step. So let again, let's say all you want to do is modernize your event collection. Well, we can absolutely, as a first step, for example, you can instrument us. You can collect all your data from your web and mobile apps in real time, and we can pipe to your existing, you know Adobe campaign manager, Salesforce, marketing cloud. And later down the line, let's say, you say I want to, you know, modernize my analytics platform. I'm tired of using Adobe analytics. You can swap that out, right again with an mparticle place, a marketer can or essentially any business user can flip the switch. And within the mparticle interface, simply disconnect their existing tool and connect a new tool with a couple of button clicks and bam, the data's now flowing into the new tool. So it mparticle really, because we kind of sit in the middle of all these tools and we have over 300 productized prebuilt integrations allows you to move away from kind of a locked in, you know a strategy where you're committed to a vendor a hundred percent to more of a best of breed, agile strategy. >> And where can customers that are interested, go what's your good and market strategy? How does that involve AWS? Where can folks go and actually get and test out this technology? >> Yeah. So first of all, we are we are AWS, a preferred partner. and we have a couple of productized integrations with AWS. The most obvious one is for example, being able to just export data to AWS, whether it's Redshift or an S3 or a kinesis stream, but we also have productized integrations with AWS, personalized. For example, you can take events, feed em to personalize and personalize will come up with the next best kind of content recommendation or the next best offer available for the customer. And mparticle can ingest that data back and you can use that for personalized targeting. In fact, Amazon personalize is what amazon.com themselves use to populate the recommended for use section on their page. So brands could essentially do the same. They could have a recommended for you carousel using Amazon technology but using mparticle to move the data back and forth to, to populate that. And then on top of that very, very soon we'll be also launching a marketplace kind of entry. So if you are a AWS customer and you have credits left over or you just want to transact through AWS, then you'll have that option available as well. >> Coming soon to the AWS marketplace. James, thank you so much for joining me talking about mparticle, how you guys are really revolutionizing the customer data platform and allowing organizations and many industries to really extract value from customer data and use it wisely. We appreciate your insights and your time. >> Thank you very much, Lisa >> For James Fang, I'm Lisa Martin. You're watching theCube's coverage of the AWS startup showcase season three, season two episode three, leave it right here for more great coverage on theCube, the leader in live tech coverage.

(introductory riff) >> Hey everyone. Welcome to theCUBE's presentation of the "AWS Startup Showcase." This is Season 2, Episode 3 of our ongoing series that features great partners in the massive AWS partner ecosystem. This series is focused on, "MarTech, Emerging Cloud-Scale Customer Experiences." I'm Lisa Martin, and I've got two guests here with me to talk about this. Please welcome Daisy Urfer, Cloud Alliance Sales Director at Algolia, and Jason Lang, the Head of Product for Apply Digital. These folks are here to talk with us today about how Algolia's Search and Discovery enables customers to create dynamic realtime user experiences for those oh so demanding customers. Daisy and Jason, it's great to have you on the program. >> Great to be here. >> Thanks for having us. >> Daisy, we're going to go ahead and start with you. Give the audience an overview of Algolia, what you guys do, when you were founded, what some of the gaps were in the market that your founders saw and fixed? >> Sure. It's actually a really fun story. We were founded in 2012. We are an API first SaaS solution for Search and Discovery, but our founders actually started off with a search tool for mobile platforms, so just for your phone and it quickly expanded, we recognize the need across the market. It's been a really fun place to grow the business. And we have 11,000 customers today and growing every day, with 30 billion searches a week. So we do a lot of business, it's fun. >> Lisa: 30 billion searches a week and I saw some great customer brands, Locost, NBC Universal, you mentioned over 11,000. Talk to me a little bit about some of the technologies, I see that you have a search product, you have a recommendation product. What are some of those key capabilities that the products deliver? 'Cause as we know, as users, when we're searching for something, we expect it to be incredibly fast. >> Sure. Yeah. What's fun about Algolia is we are actually the second largest search engine on the internet today to Google. So we are right below the guy who's made search of their verb. So we really provide an overall search strategy. We provide a dashboard for our end users so they can provide the best results to their customers and what their customers see. Customers want to see everything from Recommend, which is our recommended engine. So when you search for that dress, it shows you the frequently bought together shoes that match, things like that, to things like promoted items and what's missing in the search results. So we do that with a different algorithm today. Most in the industry rank and they'll stack what you would want to see. We do kind of a pair for pair ranking system. So we really compare what you're looking for and it gives a much better result. >> And that's incredibly critical for users these days who want results in milliseconds. Jason, you, Apply Digital as a partner of Algolia, talk to us about Apply Digital, what it is that you guys do, and then give us a little bit of insight on that partnership. >> Sure. So Apply Digital was originally founded in 2016 in Vancouver, Canada. And we have offices in Vancouver, Toronto, New York, LA, San Francisco, Mexico city, Sao Paulo and Amsterdam. And we are a digital experiences agency. So brands and companies, and startups, and all the way from startups to major global conglomerates who have this desire to truly create these amazing digital experiences, it could be a website, it could be an app, it could be a full blown marketing platform, just whatever it is. And they lack either the experience or the internal resources, or what have you, then they come to us. And and we are end-to-end, we strategy, design, product, development, all the way through the execution side. And to help us out, we partner with organizations like Algolia to offer certain solutions, like an Algolia's case, like search recommendation, things like that, to our various clients and customers who are like, "Hey, I want to create this experience and it's going to require search, or it's going to require some sort of recommendation." And we're like, "Well, we highly recommend that you use Algolia. They're a partner of ours, they've been absolutely amazing over the time that we've had the partnership. And that's what we do." And honestly, for digital experiences, search is the essence of the internet, it just is. So, I cannot think of a single digital experience that doesn't require some sort of search or recommendation engine attached to it. So, and Algolia has just knocked it out of the park with their experience, not only from a customer experience, but also from a development experience. So that's why they're just an amazing, amazing partner to have. >> Sounds like a great partnership. Daisy, let's point it back over to you. Talk about some of those main challenges, Jason alluded to them, that businesses are facing, whether it's e-commerce, SaaS, a startup or whatnot, where search and recommendations are concerned. 'Cause we all, I think I've had that experience, where we're searching for something, and Daisy, you were describing how the recommendation engine works. And when we are searching for something, if I've already bought a tent, don't show me more tent, show me things that would go with it. What are some of those main challenges that Algolia solution just eliminates? >> Sure. So I think, one of the main challenges we have to focus on is, most of our customers are fighting against the big guides out there that have hundreds of engineers on staff, custom building a search solution. And our consumers expect that response. You expect the same search response that you get when you're streaming video content looking for a movie, from your big retailer shopping experiences. So what we want to provide is the ability to deliver that result with much less work and hassle and have it all show up. And we do that by really focusing on the results that the customers need and what that view needs to look like. We see a lot of our customers just experiencing a huge loss in revenue by only providing basic search. And because as Jason put it, search is so fundamental to the internet, we all think it's easy, we all think it's just basic. And when you provide basic, you don't get the shoes with the dress, you get just the text response results back. And so we want to make sure that we're providing that back to our customers. What we see average is even, and everybody's going mobile. A lot of times I know I do all my shopping on my phone a lot of the time, and 40%-50% better relevancy results for our customers for mobile users. That's a huge impact to their use case. >> That is huge. And when we talked about patients wearing quite thin the last couple of years. But we have this expectation in our consumer lives and in our business lives if we're looking for SaaS or software, or whatnot, that we're going to be able to find what we want that's relevant to what we're looking for. And you mentioned revenue impact, customer churn, brand reputation, those are all things that if search isn't done well, to your point, Daisy, if it's done in a basic fashion, those are some of the things that customers are going to experience. Jason, talk to us about why Algolia, what was it specifically about that technology that really led Apply Digital to say, "This is the right partner to help eliminate some of those challenges that our customers could face?" >> Sure. So I'm in the product world. So I have the wonderful advantage of not worrying about how something's built, that is left, unfortunately, to the poor, poor engineers that have to work with us, mad scientist, product people, who are like, "I want, make it do this. I don't know how, but make it do this." And one of the big things is, with Algolia is the lift to implement is really, really light. Working closely with our engineering team, and even with our customers/users and everything like that, you kind of alluded to it a little earlier, it's like, at the end of the day, if it's bad search, it's bad search. It just is. It's terrible. And people's attention span can now be measured in nanoseconds, but they don't care how it works, they just want it to work. I push a button, I want something to happen, period. There's an entire universe that is behind that button, and that's what Algolia has really focused on, that universe behind that button. So there's two ways that we use them, on a web experience, there's the embedded Search widget, which is really, really easy to implement, documentation, and I cannot speak high enough about documentation, is amazing. And then from the web aspect, I'm sorry, from the mobile aspect, it's very API fort. And any type of API implementation where you can customize the UI, which obviously you can imagine our clients are like, "No we want to have our own front end. We want to have our own custom experience." We use Algolia as that engine. Again, the documentation and the light lift of implementation is huge. That is a massive, massive bonus for why we partnered with them. Before product, I was an engineer a very long time ago. I've seen bad documentation. And it's like, (Lisa laughing) "I don't know how to imple-- I don't know what this is. I don't know how to implement this, I don't even know what I'm looking at." But with Algolia and everything, it's so simple. And I know I can just hear the Apply Digital technology team, just grinding sometimes, "Why is a product guy saying that (mumbles)? He should do it." But it is, it just the lift, it's the documentation, it's the support. And it's a full blown partnership. And that's why we went with it, and that's what we tell our clients. It's like, listen, this is why we chose Algolia, because eventually this experience we're creating for them is theirs, ultimately it's theirs. And then they are going to have to pick it up after a certain amount of time once it's theirs. And having that transition of, "Look this is how easy it is to implement, here is all the documentation, here's all the support that you get." It just makes that transition from us to them beautifully seamless. >> And that's huge. We often talk about hard metrics, but ease of use, ease of implementation, the documentation, the support, those are all absolutely business critical for the organization who's implementing the software, the fastest time to value they can get, can be table stakes, and it can be on also a massive competitive differentiator. Daisy, I want to go back to you in terms of hard numbers. Algolia has a recent force or Total Economic Impact, or TEI study that really has some compelling stats. Can you share some of those insights with us? >> Yeah. Absolutely. I think that this is the one of the most fun numbers to share. We have a recent report that came out, it shared that there's a 382% Return on Investment across three years by implementing Algolia. So that's increase to revenue, increased conversion rate, increased time on your site, 382% Return on Investment for the purchase. So we know our pricing's right, we know we're providing for our customers. We know that we're giving them the results that we need. I've been in the search industry for long enough to know that those are some amazing stats, and I'm really proud to work for them and be behind them. >> That can be transformative for a business. I think we've all had that experience of trying to search on a website and not finding anything of relevance. And sometimes I scratch my head, "Why is this experience still like this? If I could churn, I would." So having that ability to easily implement, have the documentation that makes sense, and get such high ROI in a short time period is hugely differentiated for businesses. And I think we all know, as Jason said, we measure response time in nanoseconds, that's how much patience and tolerance we all have on the business side, on the consumer side. So having that, not just this fast search, but the contextual search is table stakes for organizations these days. I'd love for you guys, and on either one of you can take this, to share a customer example or two, that really shows the value of the Algolia product, and then also maybe the partnership. >> So I'll go. We have a couple of partners in two vastly different industries, but both use Algolia as a solution for search. One of them is a, best way to put this, multinational biotech health company that has this-- We built for them this internal portal for all of their healthcare practitioners, their HCPs, so that they could access information, data, reports, wikis, the whole thing. And it's basically, almost their version of Wikipedia, but it's all internal, and you can imagine the level of of data security that it has to be, because this is biotech and healthcare. So we implemented Algolia as an internal search engine for them. And the three main reasons why we recommended Algolia, and we implemented Algolia was one, HIPAA compliance. That's the first one, it's like, if that's a no, we're not playing. So HIPAA compliance, again, the ease of search, the whole contextual search, and then the recommendations and things like that. It was a true, it didn't-- It wasn't just like a a halfhearted implementation of an internal search engine to look for files thing, it is a full blown search engine, specifically for the data that they want. And I think we're averaging, if I remember the numbers correctly, it's north of 200,000 searches a month, just on this internal portal specifically for their employees in their company. And it's amazing, it's absolutely amazing. And then conversely, we work with a pretty high level adventure clothing brand, standard, traditional e-commerce, stable mobile application, Lisa, what you were saying earlier. It's like, "I buy everything on my phone," thing. And so that's what we did. We built and we support their mobile application. And they wanted to use for search, they wanted to do a couple of things which was really interesting. They wanted do traditional search, search catalog, search skews, recommendations, so forth and so on, but they also wanted to do a store finder, which was kind of interesting. So, we'd said, all right, we're going to be implementing Algolia because the lift is going to be so much easier than trying to do everything like that. And we did, and they're using it, and massively successful. They are so happy with it, where it's like, they've got this really contextual experience where it's like, I'm looking for a store near me. "Hey, I've been looking for these items. You know, I've been looking for this puffy vest, and I'm looking for a store near me." It's like, "Well, there's a store near me but it doesn't have it, but there's a store closer to me and it does have it." And all of that wraps around what it is. And all of it was, again, using Algolia, because like I said earlier, it's like, if I'm searching for something, I want it to be correct. And I don't just want it to be correct, I want it to be relevant. >> Lisa: Yes. >> And I want it to feel personalized. >> Yes. >> I'm asking to find something, give me something that I am looking for. So yeah. >> Yeah. That personalization and that relevance is critical. I keep saying that word "critical," I'm overusing it, but it is, we have that expectation that whether it's an internal portal, as you talked about Jason, or it's an adventure clothing brand, or a grocery store, or an e-commerce site, that what they're going to be showing me is exactly what I'm looking for, that magic behind there that's almost border lines on creepy, but we want it. We want it to be able to make our lives easier whether we are on the consumer side, whether we on the business side. And I do wonder what the Go To Market is. Daisy, can you talk a little bit about, where do customers go that are saying, "Oh, I need to Algolia, and I want to be able to do that." Now, what's the GTM between both of these companies? >> So where to find us, you can find us on AWS Marketplace which another favorite place. You can quickly click through and find, but you can connect us through Apply Digital as well. I think, we try to be pretty available and meet our customers where they are. So we're open to any options, and we love exploring with them. I think, what is fun and I'd love to talk about as well, in the customer cases, is not just the e-commerce space, but also the content space. We have a lot of content customers, things about news, organizations, things like that. And since that's a struggle to deliver results on, it's really a challenge. And also you want it to be relevant, so up-to-date content. So it's not just about e-commerce, it's about all of your solution overall, but we hope that you'll find us on AWS Marketplace or anywhere else. >> Got it. And that's a great point, that it's not just e-commerce, it's content. And that's really critical for some industry, businesses across industries. Jason and Daisy, thank you so much for joining me talking about Algolia, Apply Digital, what you guys are doing together, and the huge impact that you're making to the customer user experience that we all appreciate and know, and come to expect these days is going to be awesome. We appreciate your insights. >> Thank you. >> Thank you >> For Daisy and Jason, I'm Lisa Martin. You're watching "theCUBE," our "AWS Startup Showcase, MarTech Emerging Cloud-Scale Customer Experiences." Keep it right here on "theCUBE" for more great content. We're the leader in live tech coverage. (ending riff)

>>Hello, everyone. Welcome to the cubes presentation of the 80 startup showcase marketing technology, emerging cloud scale customer experiences. This is season two, episode three of the ongoing series covering the exciting startups from the, a AWS ecosystem to talk about all the top trends and also featuring the key customers. I'm your host, John ER, today we're joined by Louis Fernando, Denise vice president of peak pay social and John Kim, the CEO of Sandberg to learn about the future of what's going on in fostering deeper customer relationships. Gentlemen, thanks for joining us in the cube showcase, >>Excited to be here. >>So John talk about Sendbird real quick set the table for us. What you guys do, you got a customer here to highlight some of the key things you're doing with customers, the value proposition what's Sendbird and what's the showcase about, >>Yeah, I'm really excited to be here. Uh, I'm John founder, C of Sandberg. So Sandberg is the worst leading conversations platform for mobile applications. We can power user to user conversations in mobile applications, as well as the brand to user conversations such as marketing sales and support. So, uh, today we power over quarter billion users on a monthly basis. Uh, we have, you know, through over 300 employees across seven different countries around the world, we work with some of the world's leading, uh, uh, customers such as big pay that we are going to showcase today, along with other, uh, wonderful customers like DoorDash, Reddit, <inaudible> sports and so forth. We have collectively raised over 200 million in funding. Um, so that's kind of where we are today. >>Well, it's always great to have, uh, one great success. Uh, good funding, more important is the customers. And I love showcases where the customers do the talking, because that means you've got some success stories. Louise, talk about, um, are you happy customer? What's it like working with Sandberg? Give us the, give us the scoop. >>So sandbar is being a great partner with us. So pick pay is a Brazilian payment app. We're at a FinTech here with more than 30 million active users using everyday pick pay to pay everything. So the, the, the majority of the payments are between peers, between people. So sandbar is, is helping us to improve a lot this journey to make it more pleasant between every everyone who are using big, big. So we are here, let's talk and it's a >>Pleasure. Yeah, it's awesome. Well, I great to have you guys on great, great relationship. And one of the things we've been talking about on the cube, if the folks watching that know our audience, no we've been banging the, the drum hard on this new world and this new patterns of user expectations and building relationships in this new digital world is not about the old way, the old MarTech way. There are new new use cases, new expectations by the consumers, John, that are, that are bringing up new opportunities, but also expectations. It's not about, I mean, I mean, if someone's using discord, for example, cuz they're gamers, they're done discord. If they want to communicate with, with slack, they, I do slack, SMS, kind of old hat. You got WhatsApp, you've got all these now peer to peer organic connections, multiple channels. This is all the new world. What's your vision on this new relationship building digital communication world. >>Yeah. So I, I think you brought a really good point there. One of the most frequently used applications in the world today are messaging applications across any countries, any region, any culture, if you look at the most frequently used and most longest used applications are usually some form of a, a messaging application. Now the end users or the customers in the world are so used to using, uh, uh, such a, you know, frictionless ver very responsive, modern experience on those messaging applications. What we want to help with the business around the world, the 99.9% of the business around the world don't have those really te knowledge or user experience expertise in messaging. So we want to help our businesses, help our customers be able to harness the power of modern messaging capabilities and then be able to embed it in their own business so that they can retain their users on their platform, engage with them in the con context that their, uh, what their business is about so that they can not only, uh, control or provide a better user experience, but also be able to, uh, understand their users better, uh, understand what they're doing on their businesses, be able to own and, uh, control the data in a more secure and safe way. >>So really it's uh, we're like the Robin hood of the world trying to keep superpower yeah. Back to the businesses. >>Yeah. Deal from the rich idea, the messaging scale. Bring that to everybody else. I love that. Uh, and you got kind of this double int Robin hood kind of new for the new generation finance. This is about taking the advantage of scalable platforms, monopolies, right. And giving the entrepreneur an opportunity to have that same capability feature, rich Louise PPE. You guys used Sendbird together. You have to level up, you gotta compete with those big monopolies to pride, scalable conversations. Okay. How did you engage this? What was your success path look? What was it look like? >>Yeah. When we look to this majority, the bigger chat apps that we have nowadays in the market, we are looking to them and then Brazilians are using for their daily course, but Brazilians are paying every day millions and millions of payments. And these chat apps are not, uh, able to, to, to deal with these payments. So what we are doing here is that, uh, providing a solution where every conversation that are going to happen before, during, or after a payment between the, the people, they would, uh, uh, have a nice platform that could afford all, all of their emotions and discussions that they have to do before or after the payment. So we are putting together the chat platform and we with the payment platform. So that's, that's what we are doing now. >>Okay. So just so I get this right. You're using Sandberg essentially integrated your mobile payment experience. Okay. Which is your app you're Sandberg to bring that scalability into the, into the social app application into the app itself. Is that right? >>Yes. Perfect. Integrated with the payment journey. So everybody who is going to pay, they need to find the one, the, the one they want to pay and then they can chat and conclude the payment through the platform. Yeah. I >>Mean, why not have it right there at point of, uh, transaction. Right. Um, why did you, um, decide to, um, to use conversations in your mobile wallet? Just curious. >>So it's important to say that we were born social. We born in 2012. So when our main main product was peer to peer payments, so everybody were sending money to a friend requesting or charging their family. So a service provider. And once we, we started as a social platform in that period. In that moment, we are just focusing in likes comments and like public interactions and the word become more private. And as soon we under understood this situation, we decided to move from a public feed to a private, to a private interaction. So that's, uh, that then the, the conversational space was the solution for that moving from a public interaction to a private interaction. So between the peers, which are involved in the, the transaction. So that's why we are providing the chat solution integrated with payments. >>That's a great call. John, just give some context here, again, for the folks watching this is now expected, this integrated experience. What's your, how would you talk to folks out there? I mean, first of all, I, I, I see it clearly, you've got an app, you gotta have all this integration and you need it scaling to reach features. Talk about your view on that. Is that the, is that what's happening here? What's, what's the real dynamic here. What's the, the big trend. >>Yeah. One thing that's, uh, super interesting about, uh, uh, like messaging experience in general, if you think about any kind of conversations that's happening, uh, digitally between human beings, more and more conversations, just like what Louis mentioned earlier are happening between in a private setting, even on applications, whether it be slack or other forms of communication, uh, more hap uh, more conversations happen through either one-on-one conversations or in a private small group settings. And because people feel more secure, uh, safe to have, uh, more intimate conversations. So even when you're making transactions is more, you know, there's a higher trust and, uh, people tend to engage, uh, far better on platforms through these kind of private conversations. That's where we kind of come in, whether it be, you want to set a one-on-one conversations or with a group conversation. And then ultimately if you want to take it public in a large group setting, you can also support, you know, thousands, if not, you know, hundreds of thousands of people, uh, engaging a public forum as well. So all of those capabilities can be implemented using something Ember, but again, the world is, uh, right now the businesses and how the user are, are interacting with this with each other is all happening through digital conversations. And we're seeing more and more of that happening, uh, throughout the life cycle of our company. >>Yeah, just as a sidebar, I was just talking to a venture in San Francisco the other day, and we're talking about the future of security and SAS and cloud scale. And, you know, the conversation went to more of, is it SAS? Is it platform as a service Louis? I wanna get your thoughts because, you know, you're seeing more and more needs for customization, low code, no code. You're seeing these trends. You gotta built in security. So, you know, the different, the old SAS model was softwares a service, but now that's everything in the cloud is softwares a service. So, but you need to have that platform kind of vibe for scale customization, maybe some developer integration, cuz apps are becoming the, the touchpoint. So can you walk us through what your vision was when you decided to integrate, chat into your app and how did you see that chat, changing the customer experience for payments and across your user journey? Cause, I mean, it's obvious now looking at it, but it might not have been for some. What was your, what was your vision? And when you had to do that, >>When you looked to Brazilian reality, we can see those in, uh, payment apps. All of them are focused on the transactional moment. And as soon as we started to think, how could be, how could our journey be better, more pleased than the others and make people want to be here and to use and to open our app every day is just about making the interaction with the peers easier, even with a merchant or even with my friend. So the main point that our first step was just to connect all, all the users between themselves to payments. The second step we are providing now is using the chat platform, the send bird platform as a platform for peak pay. So we are going to provide more best information. We're going to provide a better customer experience through the support and everything. So, um, this, this, this interaction or this connection, this partnership with Sandberg are going to unlock a new level of service for our users. And at the same time, a much more pleasant or a more pleasant journey for them while they are using the, the app for a, a simple payment, or if they are going to look for a group objective or maybe a crowdfund in the future or a group to decide, or just to pay something. So we are then locking a new level of interaction between the peers between the people and the users that are, that are involved into this, this payment or this simple transaction, we are making it more conversational. >>Yeah. You're making the application more valuable. We're gonna get to that in the next segment about, you know, the future of apps one and done, you see a lot of sports apps, oh, this big tournament, you know, and then you use it and then you never use it again until next year. You know, you have very time specific apps, but now you guys are smart to kind of build this in, but I gotta ask you a question because a lot of developers and companies out there always have this buy versus build decision. Why did you decide to use Sendbird versus building it in house? It's always kind of like the big trade off. >>Yeah. First of all, it will take a long, long time for us to achieve a major platform as Sandberg. And we are not a chat platform. So we are going to use this social interaction to improve the payment platform that we have. So when we look to the market and we found Sandberg, then we thought, okay, this guys, they are a real platform. And through the conversations, we are seeing that they are roadmap working in synergy with our roadmap. And then we can, we could start to deliver value to our, to our users in a fastest way. Could you imagine it spending 2, 3, 4 years to develop something like sand? And even when we achieve this point, probably our solution will be, would be weaker than, than Sandberg. So it was like no brainer to do that. Yeah. Because we want to improve the payment journey, not to do a chat, only a chat platform. So that's why we are working together to prove it's >>Really, you start to see these plugins, these, you know, look at Stripe for payments, for instance, right. And here in the success they've had, you know, people want to plug in for services. So John, I gotta ask you about, um, about the, the complexity that goes into it. The trust required that they have for you, you have to do this heavy lifting, you gotta provide the confidence that your service is gonna have to scale the compliance. Talk about that. What do you guys do under the covers that make this easy again, great business model, heavy lifting done by you. Seamless integration provide that value. That's why business is good, but there's a lot going on share what's happening under the, under the covers. >>Yeah. Um, before going to like the technical, like intricacy of what we do just to provide a little bit of background context on why we even started this business is we, uh, this is my second startup. My first company was a gaming company. We had built like chat three, four times just for our own game. So we were basically, we felt like we were reinventing the wheel. And then we actually went on a buyer's journey when we were building a social application, uh, uh, for, for, uh, uh, building our own community. We tried to actually be a buyer to see if we can actually find a solution. We want to use turns out that there weren't a lot of like sophisticated, you know, top notch, modern, uh, uh, chat experience that we can build using some other third party solutions. So we had to build all of that ourselves, which became the foundation for se today. >>And what we realized is that for most companies like using a building, the most sophisticated chat is probably not going to be their highest priority in case a pick pay will be, you know, financial transactions and all the other business that can be built on and hosted by platform like pick pay. But, you know, building the most topnotch chat experience would be a priority for a company like let's say WhatsApp or, or telegram, but it will probably not be the priority for, you know, major gaming companies, food delivery companies, finance companies, chat is not the highest priority. That's kind of where we come in, cuz chat is the highest priority for us. And we also have a privilege of working with some of the other, uh, world industry, uh, industry leaders. So by, uh, having this collective experience, working with the industry leaders, we get, uh, uh, technological superiority, being able to, uh, scale to, you know, hundreds of millions of users on a monthly basis. Also the security and the compliances by working with some of the largest commercial banks on some of the largest FinTech applications across the globe. So we have, you know, security, compliances, all the industry, best practices that are built in and all the new topnotch user experience that we are, uh, building with other customers can be also be, uh, utilized by a customer like pick pay. So you get this collective almost like evolutionary benefit. Yeah. By, uh, working with a company like us, >>You get a lot of economies of scale. Could you mind just sharing the URL for the company? So folks watching can go get, do a deep dive. Cause I'm you guys got a lot of, lot of, um, certifications under the covers, a lot of things you guys do. So you mind just sharing URL real quick. >>Yeah. So our company, uh, you can find everything about our company on sandberg.com like carrot pigeon. So, uh, you're sending a bird to send a message. So, uh, yeah. send.com >>All so let's get it to the application, cuz this is really interesting cuz Chad is table stakes now, but things are evolving beyond Chad. You gotta integrate that user experience. It's data. Now you gotta have scale. I mean, you know, people who wanna roll their own chat will find out there's a lot of client side and backend scale issues. Right. You can have a tsunami river like on Twitch, you know, you chat. I mean that, could you got client side issues, data scale. <laugh> right. You got backend. Um, Louis, talk about that dynamic because you know, as you start to scale, you want to rely on that. Talk about this dynamic, how apps now are integrating all these new features. So is it, are apps gonna go like more multifunctional? Do you see apps one and done? What's the, how do you guys see this app world playing out and where does, does the Sendbird fit in? And >>Just, just let me know better John, about the performance or about the, just, just let me >>Oh, slow with performance. Uh, performance is huge, right? You gotta have no one wants to have lag on, on chat. >>Okay. So, um, big pay when we look to the payments have millions, thousands of, of, of payments happen happening every second. So what we are doing now is moving all the payments through a conversation. So it always happened inside the conversation. So since from the first moment, um, every second counts to convert this client. And since from the first moment we never saw in, on Sandberg, any issue about that. And even when we have a question or something that we need to improve the team we're working together. So that that's, those are the points that are making us to work together and to make things going pretty fast. When we look to the users who are going to use chat, they are, their intention is three times better than the users who are not using payments through the chat. They are average. Average spent is three times higher too. >>So they, they are making more connections. They are chatting with their friends. They are friends are here. So the network effect is stronger. So if they're going to pay and they need to wait one more second, two seconds to conclude the payment, probably they will not go into choose paying through the, again, they will use only the wallet, only the code, only the Alliance of the user. So that's is so important for us to perform really, really fast. And then this is what we are finding. And this is what is happening with the integration with Sandberg. >>And what's interesting is, is that the by build chat with conversation, we just had a minute ago kind of plays in here. You get the benefits of Sandberg, but now your transactional fidelity is in the chat <laugh> that you don't build that you rely on them on. So again, that's an interesting dynamic. This is the future of apps, John, this is where it matters. The engagement. This is what you talk about is the new, the new digital experience who would've thought that five, 10 years ago. I mean, chat was just like, Hey, what's going around direct message. Now it's integral part of the app. What's your reading. >>Yeah. I mean, we're seeing that across, uh, uh, to Lewis's point, not just transactions, but like marketing messages are now being sent through chat. So the marketing is no longer just about like giving discount calls, but you can actually reengage with the brand. Uh, also support is becoming more real time through chat. So you're actually building a relationship. The support agents have a better context about the previous conversations and the transactions, the sales conversations, even like building, uh, building alerts, notification, all those things are now, uh, happening through conversations. And that's a better way for customers to engage with the brand cuz you actually, you're actually building a better relationship and also, uh, being able to trust the brand more because there is a channel for you to communicate and, and, and be seen and be heard, uh, by the brand. So we do believe that that's the future of the business and how more and more, uh, brands will be building relationships with their customers. >>Yeah. I love, I love your business model. I think it's really critical. And I think that stickiness is a real, uh, call out point there and the brand, the co-branding and the branding capability, but also really quickly in the last minute we have John and Luis, if you don't mind talking about security, I mean, I can't go a day now without getting an SMS scam, uh, text, uh, you seeing it now on WhatsApp. I mean, I don't even use telegram anymore. I mean, come on. So like, like this is now a problem. The old way has been infiltrated with spam and security issues. Security has to be there. The trust and security real quick, John, we'll start with you and we all Louis go, go ahead. >>No, no. Just, just to, to say how important is that we are not only a chatting platform. We are a payment platform, so we have money now, the transaction. So here in Brazil, we have all this safe, the, the, the layers, the security layers that we have in, on our app. And then we have the security layers provided from Sandburg. So, and when we look to the features, Sandberg are providing to us a lot of features that help users to feel safer like per refined profiles, like announcements, where it's a profile from peak pay, where the users can recognize. So this is peak pay talking with me. It's not a user trying to pass, trying to use big Bay's name to talk with me. So these issues is something that we are really, really, we really care about here because we are not only a chat platform. As I said before, we are a payment platform. We are a FinTech, we're at a digital bank. So we need to take care a lot and we don't have any complaint about it because Sandberg understood it. And then they, they, they are providing since the first moment with the perfect solutions and the user interface to make it simpler for the users to recognize that we speak, pay who is chatting with them, not a user with, with bad, bad intentions. >>Great, great insight, Louis. Thanks for sharing that, John really appreciate you guys coming on. Great showcase. Real final word. John will give you the final word folks watching out there. How do they engage with Sendbird? I want to integrate, I want to use your chat service. What do I do? Do I have to connect in as it managed service is the line of code. What do I do to get Sendbird? >>Yeah. So if you're a developer building a mobile application, simply come visit our website, we have a open documentation and SDK you can download and simply plug into your application. You can have a chat experience up and running matter of minutes, if not ours using our UI kit. So we want to make it as easy as possible for all the builders in the world to be able to harness the superpower of digital conversations. >>All right, great. Congratulations, John, on your success and all the growth and Louis, thanks for coming in, sharing the customer perspective and great insight. Thanks for coming on the showcase. Really appreciate it. Thanks for your time. >>Yeah. Thank you for having me. >>Okay. The a of us startup showcase season two, episode three here I'm John for your host. Thanks for watching.

(upbeat music) >> Hello, everyone, welcome to theCUBE's presentation of the AWS Startup Showcase. We're in Season two, Episode three, and this is the topic of MarTech and the Emerging Cloud-Scale Customer Experiences, the ongoing coverage of AWS's ecosystem of large scale growth and new companies and growing companies. I'm your host, John Furrier. We're excited to have Tim Barnes, Global Director, General Manager of Advertiser and Marketing at AWS here doing the keynote cloud-scale customer experience. Tim, thanks for coming on. >> Oh, great to be here and thank you for having me. >> You've seen many cycles of innovation, certainly in the ad tech platform space around data, serving consumers and a lot of big, big scale advertisers over the years as the Web 1.0, 2.0, now 3.0 coming, cloud-scale, roll of data, all big conversations changing the game. We see things like cookies going away. What does this all mean? Silos, walled gardens, a lot of new things are impacting the applications and expectations of consumers, which is also impacting the folks trying to reach the consumers. And this is kind of creating a kind of a current situation, which is challenging, but also an opportunity. Can you share your perspective of what this current situation is, as the emerging MarTech landscape emerges? >> Yeah, sure, John, it's funny in this industry, the only constant has changed and it's an ever-changing industry and never more so than right now. I mean, we're seeing with whether it's the rise of privacy legislation or just breach of security of data or changes in how the top tech providers and browser controllers are changing their process for reaching customers. This is an inflection point in the history of both ad tech and MarTech. You hit the nail on the head with cookie deprecation, with Apple removing IDFA, changes to browsers, et cetera, we're at an interesting point. And by the way, we're also seeing an explosion of content sources and ability to reach customers that's unmatched in the history of advertising. So those two things are somewhat at odds. So whether we see the rise of connected television or digital out of home, you mentioned Web 3.0 and the opportunities that may present in metaverse, et cetera, it's an explosion of opportunity, but how do we continue to connect brands with customers and do so in a privacy compliant way? And that's really the big challenge we're facing. One of the things that I see is the rise of modeling or machine learning as a mechanism to help remove some of these barriers. If you think about the idea of one-to-one targeting, well, that's going to be less and less possible as we progress. So how am I still as a brand advertiser or as a targeted advertiser, how am I going to still reach the right audience with the right message in a world where I don't necessarily know who they are. And modeling is a really key way of achieving that goal and we're seeing that across a number of different angles. >> We've always talked about on the ad tech business for years, it's the behemoth of contextual and behavioral, those dynamics. And if you look at the content side of the business, you have now this new, massive source of new sources, blogging has been around for a long time, you got video, you got newsletters, you got all kinds of people, self-publishing, that's been around for a while, right? So you're seeing all these new sources. Trust is a big factor, but everyone wants to control their data. So this walled garden perpetuation of value, I got to control my data, but machine learning works best when you expose data, so this is kind of a paradox. Can you talk about the current challenge here and how to overcome it because you can't fight fashion, as they say, and we see people kind of going down this road as saying, data's a competitive advantage, but I got to figure out a way to keep it, own it, but also share it for the machine learning. What's your take on that? >> Yeah, I think first and foremost, if I may, I would just start with, it's super important to make that connection with the consumer in the first place. So you hit the nail on the head for advertisers and marketers today, the importance of gaining first party access to your customer and with permission and consent is paramount. And so just how you establish that connection point with trust and with very clear directive on how you're going to use the data has never been more important. So I would start there if I was a brand advertiser or a marketer, trying to figure out how I'm going to better connect with my consumers and get more first party data that I could leverage. So that's just building the scale of first party data to enable you to actually perform some of the types of approaches we'll discuss. The second thing I would say is that increasingly, the challenge exists with the exchange of the data itself. So if I'm a data control, if I own a set of first party data that I have consent with consumers to use, and I'm passing that data over to a third party, and that data is leaked, I'm still responsible for that data. Or if somebody wants to opt out of a communication and that opt out signal doesn't flow to the third party, I'm still liable, or at least from the consumer's perspective, I've provided a poor customer experience. And that's where we see the rise of the next generation, I call it of data clean rooms, the approaches that you're seeing, a number of customers take in terms of how they connect data without actually moving the data between two sources. And we're seeing that as certainly a mechanism by which you can preserve accessibility data, we call that federated data exchange or federated data clean rooms and I think you're seeing that from a number of different parties in the industry. >> That's awesome, I want to get into the data interoperability because we have a lot of startups presenting in this episode around that area, but why I got you here, you mentioned data clean room. Could you define for us, what is a federated data clean room, what is that about? >> Yeah, I would simply describe it as zero data movement in a privacy and secure environment. To be a little bit more explicit and detailed, it really is the idea that if I'm a party A and I want to exchange data with party B, how can I run a query for analytics or other purposes without actually moving data anywhere? Can I run a query that has accessibility to both parties, that has the security and the levels of aggregation that both parties agree to and then run the query and get those results sets back in a way that it actually facilitates business between the two parties. And we're seeing that expand with partners like Snowflake and InfoSum, even within Amazon itself, AWS, we have data sharing capabilities within Redshift and some of our other data-led capabilities. And we're just seeing explosion of demand and need for customers to be able to share data, but do it in a way where they still control the data and don't ever hand it over to a third party for execution. >> So if I understand this correctly, this is kind of an evolution to kind of take away the middleman, if you will, between parties that used to be historically the case, is that right? >> Yeah, I'd say this, the middleman still exists in many cases. If you think about joining two parties' data together, you still have the problem of the match key. How do I make sure that I get the broadest set of data to match up with the broadest set of data on the other side? So we have a number of partners that provide these types of services from LiveRamp, TransUnion, Experian, et cetera. So there's still a place for that so-called middleman in terms of helping to facilitate the transaction, but as a clean room itself, I think that term is becoming outdated in terms of a physical third party location, where you push data for analysis, that's controlled by a third party. >> Yeah, great clarification there. I want to get into this data interoperability because the benefits of AWS and cloud scales we've seen over the past decade and looking forward is, it's an API based economy. So APIs and microservices, cloud native stuff is going to be the key to integration. And so connecting people together is kind of what we're seeing as the trend. People are connecting their data, they're sharing code in open source. So there's an opportunity to connect the ecosystem of companies out there with their data. Can you share your view on this interoperability trend, why it's important and what's the impact to customers who want to go down this either automated or programmatic connection oriented way of connecting data. >> Never more important than it has been right now. I mean, if you think about the way we transact it and still too today do to a certain extent through cookie swaps and all sorts of crazy exchanges of data, those are going away at some point in the future; it could be a year from now, it could be later, but they're going away. And I think that that puts a great amount of pressure on the broad ecosystem of customers who transact for marketers, on behalf of marketers, both for advertising and marketing. And so data interoperability to me is how we think about providing that transactional layer between multiple parties so that they can continue to transact in a way that's meaningful and seamless, and frankly at lower cost and at greater scale than we've done in the past with less complexity. And so, we're seeing a number of changes in that regard, whether that's data sharing and data clean rooms or federated clean rooms, as we described earlier, whether that's the rise of next generation identity solutions, for example, the UID 2.0 Consortium, which is an effort to use hashed email addresses and other forms of identifiers to facilitate data exchange for the programmatic ecosystem. These are sort of evolutions based on this notion that the old world is going away, the new world is coming, and part of that is how do we connect data sources in a more seamless and frankly, efficient manner. >> It's almost interesting, it's almost flipped upside down, you had this walled garden mentality, I got to control my data, but now I have data interoperability. So you got to own and collect the data, but also share it. This is going to kind of change the paradigm around my identity platforms, attributions, audience, as audiences move around, and with cookies going away, this is going to require a new abstraction, a new way to do it. So you mentioned some of those standards. Is there a path in this evolution that changes it for the better? What's your view on this? What do you see happening? What's going to come out of this new wave? >> Yeah, my father was always fond of telling me, "The customer, my customers is my customer." And I like to put myself in the shoes of the Marc Pritchards of the world at Procter & Gamble and think, what do they want? And frankly, their requirements for data and for marketing have not changed over the last 20 years. It's, I want to reach the right customer at the right time, with the right message and I want to be able to measure it. In other words, summarizing, I want omnichannel execution with omnichannel measurement, and that's become increasingly difficult as you highlighted with the rise of the walled gardens and increasingly data living in silos. And so I think it's important that we, as an industry start to think about what's in the best interest of the one customer who brings virtually 100% of the dollars to this marketplace, which is the CMO and the CMO office. And how do we think about returning value to them in a way that is meaningful and actually drives its industry forward. And I think that's where the data operability piece becomes really important. How do we think about connecting the omnichannel channels of execution? How do we connect that with partners who run attribution offerings with machine learning or partners who provide augmentation or enrichment data such as third party data providers, or even connecting the buy side with the sell side in a more efficient manner? How do I make that connection between the CMO and the publisher in a more efficient and effective way? And these are all challenges facing us today. And I think at the foundational layer of that is how do we think about first of all, what data does the marketer have, what is the first party data? How do we help them ethically source and collect more of that data with proper consent? And then how do we help them join that data into a variety of data sources in a way that they can gain value from it. And that's where machine learning really comes into play. So whether that's the notion of audience expansion, whether that's looking for some sort of cohort analysis that helps with contextual advertising, whether that's the notion of a more of a modeled approach to attribution versus a one-to-one approach, all of those things I think are in play, as we think about returning value back to that customer of our customer. >> That's interesting, you broke down the customer needs in three areas; CMO office and staff, partners ISV software developers, and then third party services. Kind of all different needs, if you will, kind of tiered, kind of at the center of that's the user, the consumer who have the expectations. So it's interesting, you have the stakeholders, you laid out kind of those three areas as to customers, but the end user, the consumer, they have a preference, they kind of don't want to be locked into one thing. They want to move around, they want to download apps, they want to play on Reddit, they want to be on LinkedIn, they want to be all over the place, they don't want to get locked in. So you have now kind of this high velocity user behavior. How do you see that factoring in, because with cookies going away and kind of the convergence of offline-online, really becoming predominant, how do you know someone's paying attention to what and when attention and reputation. All these things seem complex. How do you make sense of it? >> Yeah, it's a great question. I think that the consumer as you said, finds a creepiness factor with a message that follows them around their various sources of engagement with content. So I think at first and foremost, there's the recognition by the brand that we need to be a little bit more thoughtful about how we interact with our customer and how we build that trust and that relationship with the customer. And that all starts with of course, opt-in process consent management center but it also includes how we communicate with them. What message are we actually putting in front of them? Is it meaningful, is it impactful? Does it drive value for the customer? I think we've seen a lot of studies, I won't recite them that state that most consumers do find value in targeted messaging, but I think they want it done correctly and there in lies the problem. So what does that mean by channel, especially when we lose the ability to look at that consumer interaction across those channels. And I think that's where we have to be a little bit more thoughtful with frankly, kind of going back to the beginning with contextual advertising, with advertising that perhaps has meaning, or has empathy with the consumer, perhaps resonates with the consumer in a different way than just a targeted message. And we're seeing that trend, we're seeing that trend both in television, connected television as those converge, but also as we see about connectivity with gaming and other sort of more nuanced channels. The other thing I would say is, I think there's a movement towards less interruptive advertising as well, which kind of removes a little bit of those barriers for the consumer and the brand to interact. And whether that be dynamic product placement, content optimization, or whether that be sponsorship type opportunities within digital. I think we're seeing an increased movement towards those types of executions, which I think will also provide value to both parties. >> Yeah, I think you nailed it there. I totally agree with you on the contextual targeting, I think that's a huge deal and that's proven over the years of providing benefit. People, they're trying to find what they're looking for, whether it's data to consume or a solution they want to buy. So I think that all kind of ties together. The question is these three stakeholders, the CMO office and staff you mentioned, and the software developers, apps, or walled gardens, and then like ad servers as they come together, have to have standards. And so, I think to me, I'm trying to squint through all the movement and the shifting plates that are going on in the industry and trying to figure out where are the dots connecting? And you've seen many cycles of innovation at the end of the day, it comes down to who can perform best for the end user, as well as the marketers and advertisers, so that balance. What's your view on this shift? It's going to land somewhere, it has to land in the right area, and the market's very efficient. I mean, this ad market's very efficient. >> Yeah, I mean, in some way, so from a standards perspective, I support and we interact extensively with the IB and other industry associations on privacy enhancing technologies and how we think about these next generations of connection points or identifiers to connect with consumers. But I'd say this, with respect to the CMO, and I mentioned the publisher earlier, I think over the last 10 years with the rise of programmatic, certainly we saw the power reside mostly with the CMO who was able to amass a large pool of cookies or purchase a large sort of cohort of customers with cookie based attributes and then execute against that. And so almost a blind fashion to the publisher, the publisher was sort of left to say, "Hey, here's an opportunity, do you want to buy it or not?" With no real reason why the marketer might be buying that customer? And I think that we're seeing a shift backwards towards the publisher and perhaps a healthy balance between the two. And so, I do believe that over time, that we're going to see publishers provide a lot more, what I might almost describe as mini walled gardens. So the ability, great publisher or a set of publishers to create a cohort of customers that can be targeted through programmatic or perhaps through programmatic guaranteed in a way that it's a balance between the two. And frankly thinking about that notion of federated data clean rooms, you can see an approach where publishers are able to share their first party data with a marketer's first party data, without either party feeling like they're giving up something or passing all their value over to the other. And I do believe we're going to see some significant technology changes over the next three to four years. That really rely on that interplay between the marketer and the publisher in a way that it helps both sides achieve their goals, and that is, increasing value back to the publisher in terms of higher CPMs, and of course, better reach and frequency controls for the marketer. >> I think you really brought up a big point there we can maybe follow up on, but I think this idea of publishers getting more control and power and value is an example of the market filling a void and the power log at the long tail, it's kind of a straight line. Then it's got the niche kind of communities, it's growing in the middle there, and I think the middle of the torso of that power law is the publishers because they have all the technology to measure the journeys and the click throughs and all this traffic going on their platform, but they just need to connect to someone else. >> Correct. >> That brings in the interoperability. So, as a publisher ourselves, we see that long tail getting really kind of fat in the middle where new brands are going to emerge, if they have audience. I mean, some podcasts have millions of users and some blogs are attracting massive audience, niche audiences that are growing. >> I would say, just look at the rise of what we might not have considered publishers in the past, but are certainly growing as publishers today. Customers like Instacart or Uber who are creating ad platforms or gaming, which of course has been an ad supported platform for some time, but is growing immensely. Retail as a platform, of course, amazon.com being one of the biggest retail platforms with advertising supported models, but we're seeing that growth across the board for retail customers. And I think that again, there's never been more opportunities to reach customers. We just have to do it the right way, in the way that it's not offensive to customers, not creepy, if you want to call it that, and also maximizes value for both parties and that be both the buy and the sell side. >> Yeah, everyone's a publisher and everyone's a media company. Everyone has their own news network, everyone has their own retail, it's a completely new world. Tim, thanks for coming on and sharing your perspective and insights on this key note, Tim Barnes, Global Director, General Manager of Advertiser and Market at AWS here with the Episode three of Season two of the AWS Startup Showcase. I'm John Furrier, thanks for watching. (upbeat music)