 Welcome to this CUBE conversation. I'm here in Palo Alto, California. I'm John Furrier, host of theCUBE. And I'm here with MParticle, with Chi-Chu, Chief Product Officer. Thanks for joining us today. Thanks for coming on. Thank you, it's great to be here. So MParticle is doing some pretty amazing things around managing customer data end-to-end. It's a data platform, a lot of integrations. You guys are state-of-the-art cloud scale for this new kind of use case of using the data for customer value in real time. A lot of good stuff going on. So I really want to dig into this whole prospect. So what is the company about first? Dig a minute to explain what is MParticle for the folks watching? Yeah, absolutely. Well, if you think about the world today where it's like cloud computing and businesses are getting a lot of data from customers as consumers go online and they have these cloud services that are collecting all this data about the customer. How do you get it organized? How do you have all that data that's in different departments, reconcile them and give it to your department so they can really personalize the experiences? We've all had these experiences where with this loyal customer of a brand we shop there a lot and then we go over to the customer service and they act like they have no idea who we are. Our job is to help businesses really understand the customer and be able to treat them in a personal way to do the very best for every experience. Well, Chih, you're in a really big spot there with the company chief probably. You got the keys to the kingdom over there. You're overseeing all the action. You got a platform, a bunch of solutions you're enabling. Customer data has been around for a long time. We hear big systems in the past. Oh, got to leverage the customer data. Why is the customer data more important now than ever? As developers and cloud scaler emerging in why is customer data becoming more and more valuable to organizations? No, well, customer data has been around for like decades and decades. The amount of customer data being generated online has just accelerated. It's been exponential. There's been more data collected in the past four years than the past 40 years. And like businesses are just starting to realize how much of a goldmine that could be for them if they could really harness it. And especially in today's world where treating it properly, respecting people's privacy, really doing well by the customer, earning the right to use that data is ever so important. The combination that brings the need for solutions like MParticle. Talk about some of the enablement that you guys offer your customers. You got a platform, you got a lot of moving parts in there, a lot of key components, a lot of integrations with all the best platforms to connect to. We're an API economy. So trust is huge. You got to have the data governance. Everything's got to work together. It's a really hard problem. How do you guys enable value there? What is the key product value that you guys are enabling? Yeah, it is a hard problem. And with the data being so important to businesses and treating it well and collecting it from all the different aspects, there are many places where we, our customers really value the services we bring. As you mentioned, we have a large set of integrations. We can get data in from pretty much any system that you have. Even if you built it yourself, we have ways of enabling you to collect that data from all around the company. Then we reconcile them so we create one single view of the customer. We adhere to all the privacy regulations around the world to make sure that you're compliant with not only the laws, but with the trust with your consumers. We clean that data and then we distribute it to all the systems where you really want to create personalized experiences. So the collection, the reconciliation, the cleaning, the conformance, and then the distribution, those are all key events that we do to bring value to customers. It's funny in all these major shifts, you're seeing all the same things. You got to be a media company. You got to be a data company. You got to be a video company. You got to be a cloud company. So in the digital transformation, with machine learning and AI, really at the center of the application value now, you can measure everything in a company. So the smart leadership saying, hey, if we can measure everything, we don't want to know what's going on with respect to our customer, the journey they call it. So there's the industry taglines of customer best in class experiences, capturing the moments that matter. Describe how you do that because moments that matter to me feel like something that's real time or something that's super important that's contextualized. You got to get that context with that journey. How do you guys do that? This is something that I'm intrigued about. Yeah, absolutely. And this harking back to my experience when I was at Amazon doing retail and we really focused on personalization. And the notion of when you go to one page or one screen on your mobile device and then you go to the very next page, that very next page has to be personalized with the things that you did on just seconds ago in the previous one. That idea of being at the interaction speed, keeping up with the customers, that's what we provide for our brands. It's not enough to just collect the data, turn on it, do a bunch of calculations, and then tomorrow, figure out what to do. Tomorrow, figure out how to personalize it. It has to be an interaction time with our customers. It's interesting to get a lot of experience in big companies, hyperscalers with large media business and data, bringing that to normal companies, enterprises, and mid-market, they have to then stand up their own staffs. They have to operationalize a large data strategy that maximizes the value. How do brands do this effectively? Can you share best practice of what's the best way to stand up and operationalize the team, the developers, the strategy? Yeah, I think this is a great question. And right now, the way the world industry is developing, businesses don't all do it the same way. Like, at Amazon, we built our own. Now, we had several hundred engineers in my team who were collecting their data, analyzing it, and we're cleaning it. Not every company can afford a couple hundred engineers just to solve this one problem, which is why I'm super excited about what we're doing in MParticle, where we're trying to make that available to every company in the world, whether you're a huge brand, like an NBC, or you're a smaller or medium-sized startup, like you have a lot of data, and we can help make it accessible for you. Now, many companies do start and build it from scratch, and the problems early on seem very tractable, but then as new laws come out, as the platform changes, as Apple and iOS change the rules on what you can collect, what data you can't collect, that puts you on this treadmill, always reinvesting and reinvesting in the data collection and not as much as innovating on your business, and then many companies turn around and decide, oh, I understand why you want a company like MParticle providing that service. It's interesting, you guys do a lot of that, the key value proposition that we hear a lot for successful companies. You take care of the heavy differentiated, undifferentiated heavy lifting, so the customer can focus on the value. This seems to be the theme of the data problem that companies want to solve. There's a lot of grunt work that has to get done, a lot of get down and dirty and work on stuff. If you can just automate it and make it go faster, then you can apply more creative processes and tools onto getting more growth or more value out of the use case. Is that something that's happening here? Oh yeah, absolutely. You know, the dirty secret that if you talk to any, like a machine learning scientist, data engineer, what they'll tell you is it seems like the world is sexy when you talk to new computer science students about building models. But when they go to industry, they spend like 80 or 90% of the time cleaning data, getting access data, getting the right permissions, and they spend like 10 to 20% of the time actually building models and doing the really interesting things that you want your data science to do. That's a really expensive way of getting to your models. And that's why you're right, services like MParticle, like our core business is to take that grunt work and that things that might be less exciting and bespoke to your business. Like that's the stuff that we get excited about and we want to provide the best and breed experience for our customers. Yeah, there's no doubt every company will have to have this really complex, hard to solve platform problem. You either buy or build it. I mean, not everyone's Amazon, right? So not everyone can do that. So you got to have the integrations, you got to have the personalizations, you got the data quality, and you got to have the data governance in there too. You can't forget the fact that you'd be dealing with potentially trusted parties that don't work for you, right? So this is a huge connection point that I want to just quickly get into quickly. APIs connects companies, but now also connects data. How do you view that? How should customers think about the connection points when they start to share customer data with other companies? Yeah, you're totally right in that not only is it important for you to do this in terms of saving your time and engineering and all the amount of work you have, but the risk is super high. If you treat customers data incorrectly, you can break trust with your consumers. It takes a long time to build that trust in just a moment to lose it. And so it's more than just engineering time savings, but it's also a risk to the business. Now, then you go down to like, how do you do it? Why APIs? The reason for us, our push on really the API platform is to give power to developers. Within your company, you may have some innovation that you want, some way you want to really differentiate yourself from the rest of the field. If we provided only standard UI, standard ways of doing it, then our customers would all behave and have the same capabilities as every other customer. But by us providing APIs, it allows our customers to really innovate and make the platform bend to the will to support the unique ideas that they have. So that's our approach of why we really focus on the customer data infrastructure. Yeah, it's a great opportunity, I really appreciate your time. A real final question for you, as folks look at this opportunity to have a data platform and MParticle one that you have, they're going to probably ask you the question of, hey, I got developers too. I'm hiring more and more cloud native developers. We're API first, obviously we're cloud native. We love that direction. We're distributed computing, all that great stuff at the edge, I got machine learning. But I really want to integrate. I want to control the experience. I want to be agile and fast. Can you help us? What's your answer to that question? Absolutely. If you look at the things that your engineers are doing, you ask them how much of what they're doing is similar to what you expect from other similar companies and how much is really unique to your business. You'll probably find that a minority of the work is really unique to that business. And the majority are things that are common problems that other companies struggle with. Our job is to help take that away so you can really focus on what's unique, the spoke and innovative for you. A follow-up to that real quick is you're the chief product officer. Talk to the folks out there who watch it, who may not know what goes on in a product organization, making all kinds of trade-offs. You got a product roadmap, you got the 20 mile stair. You have a North Star. What should they know about MParticle, about the product that's important for them to either pay attention to or they may not know about? You know, what I think about MParticle is not just a product, there's the whole offering. And what you want to know about MParticle is we really work hard to empower our customers. Whether it's through the API platforms that you have the full flexibility to wherever you want, or through our customer service and our support teams, where we have a great reputation with our customers about really focusing on and unblocking them, enabling whatever the heart desires. Yeah, and building on top of it sounds great. Chief, thanks for coming on. Appreciate the update on MParticle. Thanks for your time, great to see you. Absolutely, thank you for your time. Okay, this is theCUBE conversation. I'm John Furrier, host of theCUBE. Thanks for watching.