>>Mhm >>Yes, welcome to this cube conversation. I'm lisa martin excited about this conversation. It's combining my background in life sciences with technology. Please welcome Mike Tarsa Lee, the chief scientific officer at Tetra Science. Mike I'm so excited to talk to you today. >>Thank you lisa and thank you very much to the cube for hosting us. >>Absolutely. So we talk about cloud and data all the time. This is going to be a very interesting conversation especially because we've seen events of the last what are we on 14 months and counting have really accelerated the need for drug discovery and really everyone's kind of focused on that. But I want you to talk with our audience about Tetra science, Who you guys are, what you do and you were founded in 2014. You just raised 80 million in series B but give us an idea of who you are and what you do. >>Got it. Tetro Science, what are we? We are digital plumbers and that may seem funny but really we are taking the world of data and we are trying to resolve it in such a way that people can actually pipe it from the data sources they have in a vendor agnostic way to the data targets in which they need to consume that data. So bringing that metaphor a little bit more to life sciences, let's say that you're a chemist and you have a mass spec and an NMR and some other piece of technology and you need all of those to speak the same language. Right? Generally speaking, all of these are going to be made by different vendors. They're all going to have different control software and they're all going to have slightly different ways of sending their data in. Petro Science takes those all in. We bring them up to the cloud or cloud native solution. We harmonize them, we extract the data first and then we actually put it into what we call our special sauce are intermediate data schema to harmonize it. So you have sort of like a picture and a diagram of what the prototypical mass spec or H P. L. C. Or cell counting data should look like. And then we build pipelines to export that data over to where you need it. So if you need it to live in an L. N. Or a limb system or in a visualization tool like spot fire tableau. We got you covered. So again we're trying to pipe things from left to right from sources to targets and we're trying to do it with scientific context. >>That was an outstanding description. Data plumbers who have secret sauce and never would have thought I would have heard that when I woke up this morning. But I'm going to unpack this more because one of the things that I read in the press release that just went out just a few weeks ago announcing the series B funding, it said that that picture science is pioneering a $300 billion dollar Greenfield data market and operating this is what got my attention without a direct cloud native and open platform competitor. Why is that? >>That's right. If you look at the way pharma data is handled today, even those that long tend to be either on prem solutions with a sort of license model or a distribution into a company and therefore maintenance costs, professional services, etcetera. Or you're looking at somebody who is maybe cloud but their cloud second, you know, they started with their on prem journey and they said we should go and build out some puppies, we should go to the cloud migrate. However, we're cloud first cloud native. So that's one first strong point. And the second is that in terms of data harmonization and in terms of looking at data in a vendor agnostic way, um many companies claim to do it. But the real hard test of this, the metal, what will say is when you can look at this with the Scientific contextual ization we offer. So yes, you can collect the data and put it on a cloud. Okay great. Yes. You may be able to do an extract, transform and load and move it to somewhere else. Okay. But can you actually do that from front to back while retaining all the context of the data while keeping all of the metadata in the right place? With veracity, with G XP readiness, with data fidelity and when it gets over to the other side can somebody say oh yeah that's all the data from all the H. P. L. C. S we control. I got it. I see where it is. I see where to go get it, I see who created it. I see the full data train and validation landscape and I can rebuild that back and I can look back to the old raw source files if I need to. Um I challenge someone to find another direct company that's doing that today. >>You talk about that context and the thing that sort of surprises me is with how incredibly important scientific discovery is and has been for since the beginning of time. Why is why has nobody come out in the last seven years and tried to facilitate this for life sciences organizations. >>Right. I would say that people have tried and I would say that there are definitely strides being made in the open source community, in the data science community and inside pharma and biotech themselves on these sort of build motif, right. If you are inside of a company and you understand your own ontology and processes while you can probably design an application or a workflow using several different tools in order to get that data there. But will it be generally useful to the bioscience community? One thing we pride ourselves on is when we product eyes a connector we call or an integration, we actually do it with a many different companies, generic cases in mind. So we say, OK, you have an h p l C problem over at this top pharma, you have an HPC problem with this biotech and you have another one of the C R. O. Okay. What are the common points between all of those? Can we actually distill that down to a workflow? Everyone's going to need, for example a compliance workflow. So everybody needs compliance. Right. So we can actually look into an empower or a unicorn operation and we can say, okay, did you sign off on that? Did it come through the right way? Was the data corrupted etcetera? That's going to be generically useful to everybody? And that's just one example of something we can do right now for anybody in bio pharma. >>Let's talk about the events of the last 14 months or so mentioned 10 X revenue growth in 2020. Covid really really highlighted the need to accelerate drug discovery and we've seen that. But talk to me about some of the things that Tetra science has seen and done to facilitate that. >>Yeah, this past 14 months. I mean um I will say that the global pandemic has been a challenge for everyone involved ourselves as well. We've basically gone to a full remote workforce. Um We have tried our very best to stay on top of it with remote collaboration tools with vera, with GIT hub with everything. However, I'll say that it's actually been some of the most successful time in our company's history because of that sort of lack of any kind of friction from the physical world. Right? We've really been able to dig down and dig deep on our integrations are connections, our business strategy. And because of that, we've actually been able to deliver a lot of value to customers because, let's be honest, we don't actually have to be on prem from what we're doing since we're not an on prem solution and we're not an original equipment manufacturer, we don't have to say, okay, we're going to go plug the thing in to the H. P. L. C. We don't have to be there to tune the specific wireless protocols or you're a W. S. Protocols, it can all be done remotely. So it's about building good relationships, building trust with our colleagues and clients and making sure we're delivering and over delivering every time. And then people say great um when I elect a Tetra solution, I know what's going right to the cloud, I know I can pick my hosting options, I know you're going to keep delivering more value to me every month. Um Thanks, >>I like that you make it sound simple and that actually you bring up a great point though that the one of the many things that was accelerated this last year Plus is the need to be remote that need to be able to still communicate, collaborate but also the need to establish and really foster those relationships that you have with existing customers and partners as everybody was navigating very, very different challenges. I want to talk now about how you're helping customers unlock the problem that is in every industry data silos and point to point integration where things can talk to each other, Talk to me about how you're helping customers like where do they start with? Touch? Where do you start that? Um kind of journey to unlock data value? >>Sure. Journey to unlock data value. Great question. So first I'll say that customers tend to come to us, it's the oddest thing and we're very lucky and very grateful for this, but they tend to have heard about what we've done with other companies and they come to us they say listen, we've heard about a deployment you've done with novo Nordisk, I can say that for example because you know, it's publicly known. Um so they'll say, you know, we hear about what you've done, we understand that you have deep expertise in chromatography or in bio process. And they'll say here's my really sticky problem. What can you do here? And invariably they're going to lay out a long list of instruments and software for us. Um we've seen lists that go up past 2000 instruments. Um and they'll say, yeah, they'll say here's all the things we need connected, here's four or five different use cases. Um we'll bring you start to finish, we'll give you 20 scientists in the room to talk through them and then we to get somewhere between two and four weeks to think about that problem and come back and say here's how we might solve that. Invariably, all of these problems are going to have a data silos somewhere, there's going to be in Oregon where the preclinical doesn't see the biology or the biology doesn't see the screening etcetera. So we say, all right, give us one scientist from each of those, hence establishing trust, establishing input from everybody. And collaboratively we'll work with, you will set up an architecture diagram, will set up a first version of a prototype connector, will set up all this stuff they need in order to get moving, we'll deliver value upfront before we've ever signed a contract and will say, is this a good way to go for you? And they'll say either no, no, thank you or they'll say yes, let's go forward, let's do a pilot a proof of concept or let's do a full production rollout. And invariably this data silos problem can usually be resolved by again, these generic size connectors are intermediate data schema, which talks and moves things into a common format. Right? And then also by organizationally, since we're already connecting all these groups in this problem statement, they tend to continue working together even when we're no longer front and center, right? They say, oh we set up that thing together. Let's keep thinking about how to make our data more available to one another. >>Interesting. So culturally, within the organization it sounds like Tetra is having significant influences their, you know, the collaboration but also data ownership. Sometimes that becomes a sticky situation where there are owners and they want to read retain that control. Right? You're laughing? You've been through this before. I'd like to understand a little bit more though about the conversation because typically we're talking about tech but we're also talking about science. Are you having these technical conversations with scientists as well as I. T. What is that actual team from the customer perspective look >>like? Oh sure. So the technical conversation and science conversation are going on sometimes in parallel and sometimes in the same threat entirely. Oftentimes the folks who reach out to us first tend to be the scientists. They say I've got a problem, you know and and my research and and I. T. Will probably hear about this later. But let's go. And then we will invariably say well let's bring in your R. And D. I. T. Counterparts because we need them to help solve it right? But yes we are usually having those conversations in parallel at first and then we unite them into one large discussion. And we have varied team members here on the Tetris side we have me from science along with multiple different other PhD holders and pharma lifers in our business who actually can look at the scientific use cases and recommend best practices for that and visualizations. We also have a lot of solutions architects and delivery engineers who can look at it from the how should the platform assemble the solution and how can we carry it through? Um And those two groups are three groups really unite together to provide a unified front and to help the customer through and the customer ends up providing the same thing as we do. So they'll give us on the one call, right? Um a technical expert, a data and QA person and a scientist all in one group and they'll say you guys work together to make sure that our orders best represented here. Um And I think that that's actually a really productive way to do this because we end up finding out things and going deeper into the connector than we would have otherwise. >>It's very collaborative, which is I bet those are such interesting conversations to be a part of it. So it's part of the conversation there helping them understand how to establish a common vision for data across their organization. >>Yes, that that tends to be a sort of further reaching conversation. I'll say in the initial sort of short term conversation, we don't usually say you three scientists or engineers are going to change the fate of the entire orig. That's maybe a little outside of our scope for now. But yes, that first group tends to describe a limited solution. We help to solve that and then go one step past and then they'll nudge somebody else in the Oregon. Say, do you see what Petra did over here? Maybe you could use it over here in your process. And so in that way we sort of get this cultural buy in and then increased collaboration inside a single company. >>Talk to me about some customers that you've worked with it. Especially love to know some of the ones that you've helped in the last year where things have been so incredibly dynamic in the market. But give us an insight into maybe some specific customers that work with you guys. >>Sure. I'd love to I'll speak to the ones that are already on our case studies. You can go anytime detector science dot com and read all of these. But we've worked with Prelude therapeutics for example. We looked at a high throughput screening cascade with them and we were able to take an instrument that was basically unloved in a corner at T. Can liquid handler, hook it up into their Ln. And their screening application and bring in and incorporate data from an external party and do all of that together and merge it so they could actually see out the other side a screening cascade and see their data in minutes as opposed to hours or days. We've also worked as you've seen the press release with novo Nordisk, we worked on automating much of their background for their chromatography fleet. Um and finally we've also worked with several smaller biotechs in looking at sort of in stan shih ation, they say well we've just started we don't have an L. N. We don't have a limbs were about to buy these 50 instruments. Um what can you do with us and we'll actually help them to scope what their initial data storage and harmonization strategy should even be. Um so so we're really man, we're at everywhere from the enterprise where its fleets of thousands of instruments and we're really giving data to a large amount of scientists worldwide, all the way down to the small biotech with 50 people who were helping add value there. >>So big range there in terms of the data conversation, I'm curious has have you seen it change in the last year plus with respect to elevating to the C suite level or the board saying we've got to be able to figure this out because as we saw, you know, the race for the Covid 19 vaccine for example. Time to value and and to discovery is so critical. Is that C suite or board involved in having conversations with you guys? >>It's funny because they are but they are a little later. Um we tend to be a scientist and user driven um solution. So at the beginning we get a power user, an engineer or a R and D I. T. Person in who really has a problem to solve. And as they are going through and developing with us, eventually they're going to need either approval for the time, the resources or the budget and then they'll go up to their VP or their CIA or someone else at the executive level and say, let's start having more of this conversation. Um, as a tandem effort, we are starting to become involved in some thought leadership exercises with some larger firms. And we are looking at the strategic aspect through conferences, through white papers etcetera to speak more directly to that C suite and to say, hey, you know, we could fit your industry for dato motif. And then one other thing you said, time to value. So I'll say that the Tetro science executive team actually looks at that as a tract metric. So we're actually looking at driving that down every single week. >>That's outstanding. That's a hard one to measure, especially in a market that is so dynamic. But that time to value for your customers is critical. Again, covid sort of surfaced a number of things and some silver linings. But that being able to get hands on the day to make sure that you can actually pull insights from it accelerate facilitate drug discovery. That time to value there is absolutely critical. >>Yeah. I'll say if you look at the companies that really, you know, went first and foremost, let's look at Moderna right? Not our customer by the way, but we'll look at Madonna quickly as an example as an example are um, everything they do is automated, right? Everything they do is cloud first. Everything they do is global collaboration networks, you know, with harmonized data etcetera. That is the model we believe Everyone's going to go to in the next 3-5 years. If you look at the fact that Madonna went from sequence to initial vaccine in what, 50, 60 days, that kind of delivery is what the market will become accustomed to. And so we're going to see many more farmers and biotechs move to that cloud first. Distributed model. All data has to go in somewhere centrally. Everyone has to be able to benefit from it. And we are happy to help them get >>Well that's that, you know, setting setting a new record for pace is key there, but it's also one of those silver linings that has come out of this to show that not only was that critical to do, but it can be done. We have the technology, we have the brain power to be able to put those all user would harmonize those together to drive this. So give me a last question. Give me an insight into some of the things that are ahead for Tetra science the rest of this year. >>Oh gosh, so many things. One of the nice parts about having funding in the bank and having a dedicated team is the ability to do more. So first of course our our enterprise pharma and BioPharma clients, there are plenty more use cases, workflows, instruments. We've just about scratch the surface but we're going to keep growing and growing our our integrations and connectors. First of all right we want to be like a netflix for connectors. You know we just want you to come and say look do they have the connector? No well don't worry. They're going to have it in a month or two. Um so that we can be basically the almost the swiss army knife for every single connector you can imagine. Then we're going to be developing a lot more data apps so things that you can use to derive value from your data out. And then again, we're going to be looking at helping to educate everybody. So how is cloud useful? Why go to the system with harmonization? How does this influence your compliance? How can you do bi directional communication? There's lots of ways you can use. Once you have harmonized centralized data, you can do things with it to influence your order and drive times down again from days and weeks, two minutes and seconds. So let's get there. And I think we're going to try doing that over the next year. >>That's awesome. Never a dull moment. And I, you should partner with your marketing folks because we talked about, you talked about data plumbing the secret sauce and becoming the netflix of connectors. These are three gems that you dropped on this this morning mike. This has been awesome. Thank you for sharing with us what teacher science is doing, how you're really helping to fast track a lot of the incredibly important research that we're all really um dependent on and helping to heal the world through data. It's been a pleasure talking with you. >>Haley says I'm a real quickly. It's a team effort. The entire Tetro science team deserves credit for this. I'm just lucky enough to be able to speak to you. So thank you very much for the opportunity. >>And she about cheers to the whole touch of science team. Keep up the great work guys. Uh for mike Roselli, I'm lisa martin. You're watching this cube conversation. >>Mhm.

(upbeat music) >> Welcome to today's session of the AWS Startup Showcase, featuring Cordial. I'm your host, Lisa Martin. I've got two guests with me here today. Christy Parrish here, she's the director of client success at Cordial, and Hailey Pettit is here as well. She's the CRM manager at Nurx. Ladies, welcome to today's session. >> Thank you. >> Thank you, happy to be here. >> Excited about this conversation. You're going to be talking about personalizing at scale and we're going to look, learn how Nurx is re-inventing the digital patient experience, such a relevant topic. Let's go ahead and get started So the audience understands about each of your companies. Christy, we'll start with you. Give us an overview of Cordial and how you help customers? >> Absolutely. So Cordial is a cross channel messaging and data platform. So our clients can collect all of their unstructured customer and business data from wherever it lives in their tech stack and really use that data to build audience segments, discover trends and insights, and automate super hyper-personalized customer experiences at enterprise scale. So as someone who essentially grew up in the legacy email space, I actually worked at a legacy ESP for about 13 years. I see Cordial as a radical shift from heavy cumbersome data processes and the need for lengthy delays and heavy lift to send messages. We're activating massive amounts of consumer and business data kind of up to the second, regardless of its underlying structure or format. And we're making that available across any outbound channel to deliver these highly personalized messaging. So I think it's important to also mention that Cordial is more than just a platform. All of that power, all of the AWS powered power is backed by some of the best innovators and support teams in the industry. So I'm especially proud of how it partner with our clients like Nurx to help them build and execute on their business goals. We're enabling some of the best brands out there. You know, we have Eddie Bauer, we have 1-800 Contacts, REVOLVE Clothing. We're really bringing them agility and a solid marriage of art and science. >> Oh, I like that, a marriage of art and science Especially as we become more demanding as consumers. Whether we're consuming something in a retail environment or we're patients, we want the information to be really as you said, hyper personalized. So Hailey, let's talk about Nurx. This is a very interesting brand and I think it's very fitting that we're talking about this during Women's History Month as well. Give us an overview of what you guys do and why you're so radically novel? >> Yeah, so Nurx is a telehealth company and we are really focused on sensitive health needs. We're really a leader in the birth control space right now. So we prescribe and deliver online directly to our patients. So we offer not only birth control, but STI home testing prep, which is HIV preventative medication. We just launched acne treatment, migraine treatment. So really expanding within the healthcare space. I think what really sets Nurx apart is our one-to-one relationship with our providers, with our patients, and really at our core we really believe that healthcare should be accessible and affordable to everyone, no matter what their circumstances. So yeah, it's a very exciting space to be in and definitely being data-driven it really impacts that patient care and helps us really care for our patients in a really innovative, exciting way. >> It's very innovative. Christy let's talk a little bit about some of the other customers. We're going to dig into the Nurx story, but talk to me about some of the other customers that Cordial helps in other industries for example. You mentioned a few, but let's kind of open that up. >> Cordial really is helping a lot customers really in the retail space. So retail is that is a large focus on e-comm for us. What really kind of stands out to me about Cordial with retail and maybe even some of our publishing clients is our ability to sort of take that data agnostic approach. Data can come from anywhere, from anywhere in their tech stack and come into Cordial. And then we're really focused on making it accessible to them and meaningful for their outbound communications. So any channel, anytime kind of if they want to do direct mail or Facebook audiences, we really are able to bring in that data and look at their business goals, look at what they're trying to achieve inside of their vertical and then make that data powerful for them, not only for just talking to their customers and growing things like revenue per email or their lifetime value for their customers but really bringing it into their insights. And one of the things that I think Nurx is doing really well is using that data, using those insights to kind of feed the next evolution of their messaging programs. So that's a lot of what we're doing for our clients, and having some really stellar successes across verticals. >> So the data explosion, we have to address that. It's something that we're also helping to create as consumers, as patients, et cetera. But we also have this demand, like I said earlier. We want information on any channel. It's great if a brand can come to the channel that we want, that's rare to get that. But creating a data-driven customer experience is a really challenging thing to accomplish. Christy, how do you, how does Cordial help your customers in any industry actually do that and in a timely fashion so that the messages are relevant and personalized? >> Yeah, so I think in this case and in many cases, the key to creating that great customer experience is really using that data with empathy, being able to not just go out and check a box, look for the next logical data data point but really grabbing that data, making it into maybe thoughtful cohorts, thoughtful automated customer journeys, and using that not just to blast out marketing messages but to potentially, and like in the case of Nurx, address pain points or gaps in the knowledge on the behalf of the consumer. Or even for retail, faults in the buying cycle, right? So are they going to buy again soon? What is going to happen next? So this will really kind of make or break the customer experience. And in this case with Nurx it's the patient experience with the brand. So we want to be of the moment. We don't want to send out something that's wrong, last week's news or something like that, or push them beyond where they're at in their cycle. So being able to have kind of that empathy with the data and looking at it from a holistic standpoint, I think is kind of the data magic that Cordial is able to bring. >> The empathy point is provocative. How do you look at data with empathy and deliver those customer experiences that relay that, so that that customer actually feels the empathy coming from the vendor? >> Yeah, I love that point as well, especially in the healthcare space it's all about patient care and understanding how each patient is different in their needs. And so utilizing the data, understanding where they are in their journey with healthcare is so important and Cordial really does allow us to do that. And we use that data to craft really empathetic messaging. So we know where they are in the flow. We know what pain points they may have or what questions they may have at that stage. And so addressing those head on is super important and it's like a key strategic goal of decisions that we've made and everything that we do. I also think there's a lot of stigma in the healthcare space and so education is also a very key factor around these service lines. And yeah, it's really exciting to be able to have a voice in this space and really educate our patients and address those needs. >> And meet them where they are. I think, again, as consumers we're more and more demanding. We can get anything anywhere, any time. And we want you to come where we are, rather than us have to go to where you are. And certainly with healthcare that's been a big challenge in the last year or so. But let's talk about some of the, Christy I want to get your perspective on some of the challenges and the roadblocks when businesses are trying to really form synergistic, empathetic customer relationships at scale, what are some the roadblocks that you help customers move out of the way? >> Right, yeah. So every day at Cordial the volume of data increases, right? So data's coming from all places and we're trying to be smart about using it. We're really working on helping marketers figure out ways to apply insights and meaningful communication strategies to get past this concept of data paralysis, right? It's making that data accessible and meaningful and then giving marketers tools to distill that data into more actionable views so that they can take what they have learned from it and then again iterate on it. So building out customer attributes, cohorts, different ways of slicing the data to make sure that it's as meaningful as possible for their program. And then we partner that with offline insights. So best practices, program strategy trends, to push that distilled data even farther on behalf of their marketing programs. >> You mentioned data paralysis, and that's certainly something that no business, especially in the last year as we've seen a demand for real time is no longer a nice to have, it's really table stakes, but that data paralysis can be a big challenge in terms of how to work around it. How do you pull actionable nuggets from the data to make decisions in the fast enough time that are still relevant for your audience? Can you walk us through how you're doing that at Nurx? >> Yeah, at X we definitely stay focused on the patient and when you have that clarity it's easier to navigate through the data and not getting caught up in that paralysis. I mean, I'm not saying we're perfect, because I've definitely experienced that where there's just so much information that you have. And if you were to touch on each point, a lot of your automations would get really thin. So using the data smart and with, but also you're creative is really important. Another roadblock that we've had is, when you have increasing demand, when you're at scale, really automating some of the one-to-one interactions that you have is so important. And digging down into what data is important to automate those interactions. And I think a great example for us is we launched a post prescription flow. So our patients are notified when their prescription is on their way. And our providers told us, "Like clockwork we get these questions once patients are notified. And so we validated that in the data, we put that data within Cordial and we were able to build out a really successful automation that proactively address those questions. And we saw a direct decrease in those types of tickets to our providers asking those questions." So, yeah, that was really great to see too. >> So taking a look at the data and seeing the most common questions for certain types of prescriptions that providers are getting, which I imagine takes time from the provider being able to treat somebody else, condensing those down, automating those and then you're freeing up the provider as well because you know the common questions they could ask. So in terms of the patient then they sort of proactively got messages about questions that they might have. >> Yes, so more specifically how to start their medication. And then also some of the side effects that may be involved with that medication and what would be normal versus abnormal and what you should pay attention to. So just putting that in a very user-friendly format within an email worked really well. And addressing that question that our providers were taking a lot of time to answer. >> So, Hailey, so a prospective patient would go online, order what they want prescription wise, gets to a provider. They write the prescription and then is that sent to the patient's home? So there's no like physical interaction, it's all digital? >> Correct, yeah. It's all digital. We have our own pharmacy that fills the prescriptions and sends it right to your door. >> Yeah, excellent, on demand. So if we look at the last year there's been so many challenges, too many to count. But I'm wondering how, as the channels expand, we're all dependent on text and email and mobile, as the channels expand, Christy, how does the Cordial data architecture allow customers like Nurx to be able to flex as data sources expand, as data volumes grow, as channels expand, how do you allow them to have an architecture that will allow them to grow and continue to scale? >> Yeah, it's really important to ask that we be able to bring in all of this data and then like you said, a really critical point to Nurx and to a lot of our customers and our clients is, "Hey, we want to send it out across any channel." So Nurx, Hailey didn't mention that they're sending not only prescription information and follow up out by SMS or MMS marketing. They're also sending marketing messages too. So they're able to really leverage what we've built in terms of making that data accessible through all of these different channels, this channel agnostic at this point. So leveraging all of the bells and whistles of the platform, and also then using their data smartly, that's really where the clients are seeing a huge lift with the Cordial platform. They're able to visualize their data, see it, access it, even manipulate it, where in a legacy ESP, it's very limited in terms of manipulating data, aggregating it, looking at it from different angles and then being able to actually make it useful inside the platform for them. >> And Hailey, question for you. We talked about that automated prescription workflow a second ago. You also talked about this, each patient patient's journey being unique, wanting to deliver personalized, hyper-personalized actually is the word, Christy that you use. How does Cordial's platform allow you to respect the individual patient journey, customize it, and also do automation at scale? >> Yeah, I think with Cordial it's an incredible platform. We're able to pull in data from multiple sources and then it's very user-friendly in the way that you can interact with that data and manipulate it and really get at the cohorts that you were trying to reach. I think it's really a special platform. Honestly I think I haven't seen a lot of other platforms like this where it does make it really visually accessible to a brand or a company. >> Something, Christy that I wanted to ask you. I saw in the marketing messaging that what you're aiming to do is making marketing not personalized. And I thought, "Ooh, that's an interesting statement." What's the difference between personal and personalized from Cordial's point of view? >> It really goes back to that whole checking a box, right? So the traditional way of doing outbound communications marketing, even going back to the days of direct mail is to sort of wedge our customers into little boxes or even big boxes, and then send out messages that we think will resonate with them. Now we're really looking at it in real time as the messages are being generated and sent out of a platform where at the moment of send we're reading some signals that the customer is giving us, like what did they do on a website? Or did they respond to an SMS message or a text message? And at the moment of said we're actually sending content that is relevant at that time. It's vastly different from the way that we've traditionally marketed in outbound communications across all channels. So looking at real time, Hailey mentioned that she can visualize, we have a feature called orchestration builder that allows Hailey to come in and say, "Okay, based on these signals or triggers, I want to send this message to these users or these patients, but they need to be in that moment ready for that message. Or she could say, "If they're not ready for that message, let's skip them and come back to them later." And be able to really kind of narrow in and get super personal with those messages. Nurx is incredible, the way that they've used the platform and the way that she's built out these orchestrations, all credit to Haley on this. The way that she's smartly used her tools, it's not only effective, but it's sort of revolutionary, just in the way that she's able to find the right message at the right time. And in email we've said that for years. Right message at the right time. But really we haven't said, "Let's make it personal. Let's use the data that we just got 10 seconds ago and send the message now." So it's been great. >> Yeah, that's a game changer. Using the data that we just got about this person. Speaking of that, on-demand culture, that's a game changer for retail, for healthcare, to be able to tune that in an automated way. I imagine that the campaign ROI numbers, Christy are probably pretty much off the wall for your customers? >> In a lot of cases, they are. Yeah, they're doing really well. They're leveraging data in ways that I've never seen before. We've got some clients who are looking across periods of time, especially in retail, looking across periods of time at their customer's behavior. And then looking for ways to communicate them when maybe there wouldn't be a way to communicate with them that day. So it's the day that they send out a sale but they're are a person who doesn't like sales or doesn't respond to sales. So they may send them a different piece of content something lifestyle, or, you know, curating content, that kind of thing. So it's really been it has been a bit revolutionary in the way that the clients have leveraged the ability to let you know to use their data in new and kind of special ways. >> I can only imagine the last year has affected this in a good way, because we've become even more demanding as a society. Everybody everywhere struggling to get certain supplies for example, but Christy, how has the last year affected Cordial's growth and that of your customers? >> Yeah, so I say this frequently, we have sort of trained a new generation of e-com buyers in the last year. We've taught people how to buy online and that has affected a lot of our brick and mortar clients who also have e-comm business. You know, so we have a large group of furniture clients. And so they've really seen some incredible success, retraining their their customers to buy large items online. It's not an easy thing, but they've really become sort of renegade in the way that they're pushing out messaging and finding the right people to send those to these new econ buyers. So it's been really interesting and they've come back and invested in technology that has enabled them to build trust and build out these individualized brand experiences so that they can actually scale those programs. Now this year, as we're reopening, the strategy is shifting, right? We're looking at, "Okay, we had an incredible year in some cases last year with e-com. Now we're going to have a store that's opened." How do we make that experience special? How do we continue the dialogue with these customers? >> Such an interesting thing that sounds like it's Cordial's been a facilitator of the many pivots that so many businesses have needed to go through. And to your point, sort of re-pivoting back towards some mixture of online e-com and in physical retail or store rather experience, it'll be interesting to see how that happens. And then, Hailey, some pretty big statistics you have to share in terms of some of the things that Nurx saw in the last 12 months with respect to use of your platform and personalization. Talk to us about that? >> Yeah, it's been a very interesting year for Nurx for sure. We've seen a 50% increase in our demand for birth control, with medical providers, brick and mortar medical providers, having limited capacity. We've been able to really step up and serve these patients and make sure they have their healthcare needs met during this really difficult time. We've also seen about a three X increase in our demand for emergency contraception, 130% in STI home test kits. Yeah, it's just across the board it's been really incredible to be able to really fill this need in such a difficult time. So it's been exciting. I love being able to help serve these patients during this time, yeah. >> Yeah, and that need to do something so personalized during such an incredibly difficult time. That's a really interesting mix there. And congratulations on the success that you guys have had. I want to wrap things up, Christy with you. Let's just talk a little bit about the Cordial AWS relationship. You guys started on day one back in 2014, or you built on AWS, tell me about that? >> Yep, so definitely built on AWS. We leveraged the AWS system extensively and yeah, we started in 2014. I think the founders were looking for, where do we go for stability? Where do we go for efficiency and reliability? And so came over to AWS and since then we've become an advanced tier independent software vendor. And then I think more recently in the last couple of years, we've kind of gained a couple of competencies, retail and digital customer experience. So super embedded there. And really, I think AWS not only contributed to the foundation of the platform, it allows us to store and manage that massive volume of customer and business data for our clients and be able to actually house it in the cloud. Really it kind of empowers us to do that, to deliver that messaging at scale that we've been talking about. >> So AWS is an enabler of the way that you help your customers create this personalized experience at scale? >> Yeah, absolutely. And it really it helps us solve these challenging problems that we have where we're working with a client like Nurx and we have a few others where we have to be HIPAA compliant. So we rely on the AWS architecture to not only enable our scalability and reliability, but also with those high security and compliance standards. This is incredibly important to us in servicing our clients. >> Well, ladies, thank you so much for joining me today on the Showcase and sharing what your companies are each doing and what they're doing together. Big changes, big opportunities, and that personalized experience that I think we all crave. Thank you so much for joining me today. >> Thanks Lisa. >> Thank you. For my guests, Christy Parrish and Hailey Pettit. I'm Lisa Martin. Thanks for watching. (gentle music)