>> 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)

(upbeat music) >> Hello everyone, welcome to this CUBE conversation. I'm John Furrier, your host of theCUBE here in Palo Alto, California in our studios. Got a great guest here, Rachel Obstler, Vice President, Head of Product at heap.io or Heap is the company name, heap.io is URL. Rachel, thanks for coming on. >> Thanks for having me, John. Great to be here. >> So you guys are as a company is heavily backed with some big time VCs and funders. The momentum is pretty significant. You see the accolades in the industry. It's a hot market for anyone who can collect data easily and make sense of it relative to everything being measured, which is the Nirvana. You can measure everything, but then what do you do with it? So you're at the center of it. You're heading up product for heap. This is what you guys do. And there's a lot of solutions, so let's get into it. Describe the company. What's your mission and what you guys do? >> Yeah, so let me start maybe with how Heap was even started and where the idea came from. So Heap was started by Matin Movassate, someone who was working at Facebook. And this is important 'cause it gets right at the problem that we are trying to solve, which is that he was a product manager at Facebook and he was spending a lot of money on pizza. The reason why he was spending a lot of money on pizza is because he wanted to be able to measure what the users were doing in the product that he was responsible for, and he couldn't get the data. And in order to get the data, he would have to go beg his engineers to put in all sorts of tracking code to collect data. And every time he did so, he had to bribe him with pizza because it's no one's favorite work, number one, and then people want to build new things. They don't want to just constantly be adding tracking code. And then the other thing he found is that even when he did that then it took a couple weeks to get it done. And then he had to wait to collect the data to see what data is. It takes a while to build up the data, and he just thought there must be a better way. And so he founded, he with a couple other co-founders, and the idea was that we could automatically collect data all the time. So it didn't matter if you launched something new, you didn't have to do anything. The data would be automatically collected. And so Heap's mission is really to make it easy to create amazing digital experiences. And we do that by firstly, just making sure you have all the data of what your users are doing because you would think you want to create a new digital experience. You could just do that and it would be perfect the first time, but that's not how it works and users are not predictable. >> Yeah, remember back in the day, big data, Hadoop and that kind of fell flap, but the idea of a data lake started there. You saw the rise of Databricks, the Snowflakes. So this idea that you can collect is there. It's here now, state of the art. Now I see that market. Now the business model comes in. Okay, I can collect everything. How fast can I turn around the insights becomes the next question. So what is the business model of the company? What does the product do? Is it SaaS? Is it a as a package software? How do you guys deploy? How do your customers consume and pay for the service? >> Yeah, so we are a SaaS company and we sell largely to, it could be a product manager. It could be someone in marketing, but it's someone who is responsible for a digital service or a digital product. So they're responsible for making sure that that they're hitting whatever targets they have. It could be revenue, it could be just usage, getting more users adopted, making sure they stay in the product. So that's who we sell to. And so basically our model is just around sessions. So how many sessions do you have? How much data are you collecting? How much traffic do you have? And that's how we charge. I think you were getting at something else though that was really interesting, which is this proliferation of data and then how do you get to an insight. And so one of the things that we've done is first of all, okay, collecting all the data and making sure that you have everything that you need, but then you have a lot of data. So that is indeed an issue. And so we've also built on top of Heap a data science layer that will automatically surface interesting points. So for instance, let's say that you have a very common user flow. Maybe it's your checkout flow. Maybe it's a signup flow and you know exactly what the major milestones are. Like you first fill out a form, you sign up, like maybe you get to do the first thing in the trial. You configure it, you get some value. So we're collecting not only those major milestones, we're collecting every single thing that happens in between. And then we'll automatically surface when there is an important drop off point, for instance, between two milestones so that you know exactly where things are going wrong. >> So you have these indicators. So it's a data driven business. I can see that clearly. And the value proposition in the pitch to the customer is ease of use. Is it accelerated time to value for insights? Is it eliminating IT? Is it the 10X marketer? Or all of those things? What is the core contract with the customer, the brand promise? >> That's exactly. So it's the ability to get to insight. First of all, that you may never have found on your own, or that would take you a long time to keep trialing an error of collecting data until you found something interesting. So getting to that insight faster and being able to understand very quickly, how you can drive impact with your business. And the other thing that we've done recently that adds a lot to this is we recently joined forces with a company named Auryc so we just announced this on Monday. So now on top of having all the data and automatically surfacing points of interest, like this is where you're having drop off, this is where you have an opportunity, we now allow you to watch it. So not only just see it analytically, see it in the numbers, but immediately click a show me button, and then just watch examples of users getting stuck in that place. And it really gives you a much better or clearer context for exactly what's happening. And it gives you a much better way to come up with ideas as to how to fix it as one of those digital builders or digital owners. >> You know, kind of dating myself when I mention this movie "Contact" where Jodie foster finds that one little nugget that opens up so much more insight. This is what you're getting at where if you can find that one piece that you didn't see before and bring it in and open it up and bring in that new data, it could change the landscape and lens of the entire data. >> Yeah. I can give you an example. So we have a customer, Casper. Most are familiar with that they sell mattresses online. So they're really a digital innovator for selling something online that previously you had to like go into a store to do. And they have a whole checkout flow. And what they discovered was that users that at the very end of the flow chose same day delivery were much more likely to convert and ultimately buy a mattress. They would not necessarily have looked at this. They wouldn't necessarily have looked at or decided to track like delivery mechanism. Like that's just not the most front and center thing, but because he collects all the data, they could look at it and say, oh, people who are choosing this converted a much higher rate. And so then they thought, well, okay, this is happening at the very end of the process. Like they've already gone through choosing what they want and putting it in their card and then it's like the very last thing they do. What if we made the fact that you could get same day delivery obvious at the beginning of the whole funnel. And so they tried that and it improved their conversion rate considerably. And so these are the types of things that you wouldn't necessarily anticipate. >> I got to have a mattress to sleep on. I want it today. Come on. >> Yeah, exactly. Like there's a whole market of people who are like, oh no, I need a mattress right now. >> This is exactly the point. I think this is why I love this opportunity that you guys are in. Every company now is digitalizing their business, aka digital transformation. But now they're going to have applications, they're going to have cloud native developers, they're going to be building modern applications. And they have to think like an eCommerce company, but it's not about brick and mortars anymore. It's just digital. So this is the new normal. This is an imperative. This is a fact. And so a lot of them don't know what to do. So like, wait a minute, who do we call? This is like a new problem for the mainstream. >> Yeah, and think about it too. Actually e-commerce has been doing this for quite a while, but think about all the B2B companies and B2B SaaS, like all the things that today, you do online. And that they're really having to start thinking more like e-commerce companies and really think about how do we drive conversion, even if conversion isn't the same thing or doesn't mean the same thing, but it means like a successful retained user. It's still important to understand what their journey is and where you going to help them. >> Recently, the pandemic has pulled forward this digital gap that every company's seeing, especially the B2B, which is virtual events, which is just an indicator of the convergence of physical and online. But it brings up billions of signals and I know we have an event software that people do as well. But when you're measuring everything, someone's in a chat, someone hit a web page, I mean there are billions of signals that need to get stored, and this is what you guys do. So I want to ask you, you run the product team. What's under the covers? What's the secret sauce for you guys at Heap? Because you got to store everything. That's one challenge. That's one problem you got to solve. Then you got to make it fast because most of the databases can't actually roll up data fast enough. So you're waiting for the graph forever when some people say. What's under the covers? What's the secret sauce? >> Well, it's a couple different things. So one is we designed the system from the very beginning for that purpose. For the purpose of bringing in all those different signals and then being able to cut the data lots of different ways. And then also to be able to apply data science to it in real time to be able to surface these important points that you should be looking at. So a lot of it is just about designing the system for the very beginning for that purpose. It was also designed to be easy for everyone to use. So what was a really important principle for us is a democratization of data. So in the past, you have these central data teams. You still have them today. Central data teams that are responsible for doing complex analysis. Well, we want to bring as much of that functionality to the digital builders, the product managers, the marketers, the ones that are making decisions about how to drive impact for their digital products and make it super easy for them to find these insights without having to go through a central team that could again take weeks and months to get an answer back from. >> Well, that's what brings up a good point. I want to dig into, if you don't mind, Rachel, this data engineering challenge. There's not enough talent out there. When I call data engineer, I'm talking about like the specialist person. She could be a unique engineer, but not a data scientist. We're talking about like hardcore data engineering, pipelining, streaming data, hardcore. There's not many people that fit that bill. So how do you scale that? Is that what you guys help do? >> We can help with that. Because, again, like if you put the power in the hands of the product people or the marketers or the people that are making those decisions, they can do their own analysis. Then you can really offload some of those central teams and they can do some of the much more complex work, but they don't have to spend their time constantly serving maybe the easier questions to answer. You have data that's self-service for everyone. >> Okay, before I get into the quick customer side of it, quickly while I have you on the product side. What are some of your priorities? You look at the roadmap, probably got tons of people calling. I can only imagine the customer base is diverse in its feature requests. Everyone has the same need, but they all have different businesses. So they want a feature here. They want a feature there. What's the priorities? How do you prioritize? What are some of your priorities for how you're going to build out and keep continuing the momentum? >> Yeah, so I mentioned earlier that we just joined forces with a company name Auryc that has session replay capabilities, as well as voice of customer. So one of our priorities is that we've noticed in this market, there's a real, it's very broken up in a strange way. I shouldn't say it's strange. It's probably because this is the way markets form, startups start, and they pick a technology and they build on top of it. So as a result, the way the market has formed is that you have analytics tools like Heap, and they look at very quantitative data, collecting all sorts of data and doing all sorts of quantitative cuts on it. And then you have tools that do things like session replay. So I just want to record sessions and watch and see exactly what the user's doing and follow their path through one at a time. And so one is aggregating data and the other one is looking at individual user journeys, but they're solving similar jobs and they're used by the same people. So a product manager, for example, wants to find a point of friction, wants to find an opportunity in their product that is significant, that is happening to a lot of people, that if they make a change will drive impact like a large impact for the business. So they'll identify that using the quant, but then to figure out how to fix it, they need the qual. They need to be able to watch it and really understand where people are getting stuck. They know where, but what does that really look like? Like, let me visualize this. And so our priority is really to bring these things together to have one platform where someone can just, in seconds, find this point of opportunity and then really understand it with a show me button so that they can watch examples of it and be like, I see exactly what's happening here and I have ideas of how to fix this. >> Yeah, something's happening at that intersection. Let's put some cameras on. Let's get some eyes on that. Let's look at it. >> Exactly. >> Oh, hey, let's put something. Let's fix that. So it makes a lot of sense. Now, customer attraction has been strong. I know it's been a lot of press and accolades online with when you guys are getting review wise. I mean, I can see DevOps and app people just using this easily, like signing up and I can collect all the data and seeing value, so I get that. What are some of the customer value propositions that are coming out of that, that you can share? And for the folks watching that don't know Heap, what's their problem that they're facing that you can solve, and what pain are they in or what problem do they solve? So example of some success that's coming out of the platform, enablement, the disruptive enablement, and then what's the problem, what's the customer's pain point, and when they know to call you guys or sign up. >> Yeah, so there's a couple different ways to look at it. When I was talking about is really for the user. There's this individual person who owns an outcome and this is where the market is going that the product managers, the marketers, they're not just there to build new features, they're there to drive outcomes for the business. And so in order to drive these outcomes, they need to figure out what are the most impactful things to do? Where are the investments that they need to make? And so Heap really helps them narrow down on those high impact areas and then be able to understand quickly as I was mentioning how to fix them. So that's one way to look at it. Another use case is coming from the other side. So talking in about session replay, you may have a singular problem. You may have a single support ticket. You may have someone complaining about something and you want to really understand, not only what is the problem, like what were they experiencing that caused them to file this ticket, but is this a singular problem, or is this something that is happening to many different people? And therefore, like we should prioritize fixing it very quickly. And so that's the other use case is let's start, not with the group, like the biggest impact and go to like exactly some examples, let's start with the singular and figure out if that gives you a path to the group. But the other use case that I think is really interesting is if you think about it from a macro point of view or from a product leader or a marketing leader's point of view, they're not just trying to drive impact. They're trying to make it easy for their team to drive that impact. So they're thinking about how do they make their whole organization a lot more data driven or insights driven? How do they change the culture, the process, not just the tool, but all of those things together so that they can have a bigger business impact and enable their team to be able to do this on their own? >> You guys are like a data department for developers and product managers. >> Essentially, like we are the complete dataset and the easy analysis that really helps you figure out, where do I invest? How do I justify my investments? And how do I measure how well my investments are doing? >> And this is where the iteration comes in. This is the model everyone's doing. You see a problem, you keep iterating. Got to look at the data, get some insight and keep looking back and making that product, get that flywheel going. Rachel, great stuff. Coming out here, real quick question for you to end the segment. What's the culture like over at Heap? If people are interested in joining the company or working with you guys. Every company has their own kind of DNA. What's the Heap culture like? >> That's a great question. So Heap is definitely a unique company that I've worked at and in a really good way. We find it really important to be respectful to each other. So one of our values is respectful candor. So you may be familiar with radical candor. We've kind of softened it a bit and said, look, it's good to be truthful and have candor, but let's do it in a respectful way. We really find important that everyone has a growth mindset. So we're always thinking about how do we improve? How do we get better? How do we grow faster? How do we learn? And then the other thing that I'll mention, another one of our values that I love, we call it, "taste the soup". Some people use to call it dogfooding, but we are in Heap all the time. We call it Heap on Heap. We really want to experience what our customers experience and constantly use our product to also get better and make our product better. >> A little more salt on the sauce, keep the soup, taste it a little bit. Good stuff. Rachel, thanks for coming on. Great insights and congratulations on a great product opportunity. Again, as world goes digital transformation, developers, product, all people want to instrument everything to then start figuring out how to improve their offering. So really hot market and hot company. Thanks for coming on. >> Thanks, John. Thanks for having me. >> This is theCUBE conversation. I'm John Furrier here in Palo Alto, California. Thanks for watching. (gentle music)