Informatica Inc. (INFA) Earnings Call Transcript & Summary

Okay. Thank you, everyone, for joining us. And most importantly, thank you, Amit and Mike for joining us today. So we actually had the pleasure of speaking last year at this conference. That was March '23. So let's think about what's happened since. Over $1.6 billion in ARR now, cloud business is over $600 million plus in cloud subscription, growing 40% plus, cloud NRR of 125%. You continue to be the undisputed leader in numerous Gartner quadrants. You made progress on CLAIRE AI. You've announced numerous expanded partnerships with Microsoft, Google, Snowflake and Databricks and your stock has doubled since then.

So coming in to the conference is a great idea. It seems. Can you share more about the journey since that last year? What have you learned? What do you expect in the year ahead? And why has it been such a successful year for you?

I wish I had a good recap like that for myself. I think, look -- first of all, thank you for hosting us. I really appreciate it, and good to see everybody. I think what has happened since then, in all honesty, is that the hard work that we have put in. Rome isn't built in a day, technology companies are not built in a day. It's nothing else, but that execution has shown through. Because it's not like we just built the product in the last 12 months and suddenly they scaled overnight, and it's not like somehow our customer relationships somehow happened in the last 6 and 12 months. I think what has happened is that the accumulation of everything. And I think the other one that has happened is a true recognition of some very simple things, and I'll put them in 3 categories. From an innovation point of view, ours is an extremely fragmented industry. There is just not anybody who has innovated to this scale. We put more than 1 billion plus in R&D to build, number one, the best product in the industry, every Magic Quadrant of [ A, B, C, D, E ]. The only company that is a platform, which is driven by consumption pricing and powered by our AI CLAIRE. And the third one is that we can support industrial-grade, multi-vendor, multi-cloud, hybrid workloads. So that's innovation. Second is we have not skimmed on our focus on customers. We serve the enterprise, the global G2K, complex companies -- and whether you look at our NRR, you look at our renewal rates, you look at our customer side, they are through the roof. And we have made sure that our investments, not just in innovation, but customer success, our innovations and post-sale value creation is high, and that has shown through this. And the third one is we pride ourselves in being the Switzerland of data. Our customers run a very complex IT environment, and we partner with everybody, not because partnership is important for us, but because partnership is important for our customers to be successful, whether it's the 3 hyperscalers or the 2 Databricks, I think, you talked about, but equally important to the GSIs. All the large GSIs have Informatica. By the way, for all the large GSIs, their fastest-growing practice is data and AI. And in that practice, they have an Informatica practice. And if you talk to any one of them, they'll have 6 partners. They'll have the 3 hyperscalers, the 2 guys you talked about and Informatica, and guess who worked with all of them? Us. So if you look at these 3 categories, the deliberate investment and execution has shown through, and we are extremely proud of it. And I think that we're just still scratching the surface.

Maybe let's stick on that first one, which is about the platform, the intelligent data management cloud. Why has that been so differentiated in the market? Like what is it in particular for those who are less familiar? Why has there been able to scale in so many different categories that are sometimes related sometimes even orthogonal?

Yes. So this is a big strategic bet we made. 7, 8 years ago when we were beginning the journey to build the new Informatica, my belief was that in a very fragmented -- by the way, any technology industry, the platform player takes disproportionate share, it's obvious. But to get there, our market landscape was very fragmented. Yes, there are hundreds of companies running around trying to solve point problems. But if you focus on the enterprise, they cannot become an integrator of their own cobbling 300 tools to figure out some part of the landscape. It just doesn't scale. But to me, the biggest important thing was that how do you create a platform that creates 3 benefits for our customers. They don't have to do the hard work. We have prewired and pre-integrated all the key capabilities data management in one place, one common front end, one common back end and so that they don't have to worry about going from A to B because those product categories are used to run many different workloads in analytics, analytics of warehouse, [indiscernible] or running a Customer 360 or a Supplier 360 or Data Governance, any uses. That's number one. Second is that, that platform should be so simple to use, not technologically, but from a pricing point of view, single consumption-based pricing. And no, we don't run 1 product. We run 7 product category that are very different than 33 services. So we had to dramatically simplify the pricing. So that one IPU, Informatica Processing Unit, can be used for anything. So you can literally through 1 token do anything with us. Thirdly is this platform is open. It's not just focused on Informatica. We have open APIs. So for an enterprise, we can look into anything else that exists over there, not just our partners, but even competitive tools. They can hook with us and we can run it then. And that has allowed us to come to a point where at the last count, our platform is now at 86 trillion transactions per month, which grew 62% year-over-year when we were at our last earnings call. And at that scale, you're growing 60%, 65%. And run by CLAIRE, our AI engine that runs on 40 petabytes of metadata. So that's the strategic premise that is now playing out.

Can I add one thing to that? That oftentimes in the platform thesis folks saying, you're competing best-of-breed versus platform, best-of-breed versus platform, who's going to win? In our case, it's and because we actually have the best-of-breed products as well as the platform. You don't get B+ products when you choose our platform. It sounds boastful, but just look at the Gartner MQs, look at the Forrester Waves, look at the IDC reports, you actually don't have to compromise on the best of breed by getting the platform to.

I want to dig into that point in particular. You just mentioned that growth in data, 60% plus. The only way you're going to get that many more transactions as you're winning new customers, and you've consistently this last year have shown us incredible new customer wins. Can you go a bit deeper and say, why do these customers come to you? Why do they take these point solutions out or didn't even go look at them and maybe move through any specific example and if you can name them, that would be great, but just really make it tangible for us?

So let's take -- I think everybody knows us for analytics, warehousing, ETL, I will not talk about that. So let's pick a -- so when we -- the new Informatica, basically, by the way, it's not just tied to analytics, warehousing workloads, we basically serve the digital enterprise from the front end to the back office, whether it's data governance or 360. And I'll pick a complex global implementation of -- Unilever basically -- you all know Unilever, 96 countries, they wanted to make sure that they digitize their supply chain. So they wanted to make sure that across 96 countries, every supplier is onboarded, and managed through one product, and this is an operational workload to our MDM, Supplier 360. And that's what we said about to do for them. And right now, they run the whole world through that. From there, the natural extension for them was now that every supplier, what does supplier do? Give you products. So the next extension was a Product 360. So I can understand every product that every supplier gives me so I can understand that maybe the supplier is doing a great job with this product, let's say, in Malaysia, but good Lord, not a great job, let's say, in the U.K. So -- and by the way, can I give them based on the SLAs, maybe they get a credit here or a ding there, but maybe I have a relationship so that you can just see the complexity of the scale. That's a quintessential running additional enterprise to an MDM, that Informatica never did 7, 8 years ago. Or if I'm an Anthem, and I'm basically doing so much of what Anthem does, and I want to make sure my data is governed, so anybody who's doing processing of that information, it's governed for all kind of compliance purposes as well as data democratization purposes. Those are the kind of use cases that customers are using, barring the ones that we typically know Informatica for is supporting warehouses or lake house use cases.

So maybe something like Unilever, how do they come to you to make that decision? Were they already an existing customer on another product? And then they said, I got this transferable credit. And I can use it. And they call you into pitch, do you pitch out to them? How much is a mix of that?

Unilever was not an existing customer as well. So we do have it. I mean, I think, look, we have existing customers, but good -- and Mike will go through some of the numbers in a minute, but this was a brand-new customer. They basically was -- they were looking at this use case, and they wanted to go out in the marketplace. And like any good large enterprise customers do, they look at references, they look at MQs. They basically figure out who are the top 2 or 3 that they can work with them, and they look around and they bring some to the table. And then they have the classic enterprise sales cycle that you go through. And they also look at, by the way, the scalability, the longevity, the ability to work with the different partners. Like in this case, they had a very complex environment, as you know, they had certain other technology partners. They also had GSIs will bring us to the table or talk about us. So a multitude of things play into this. It's not just technology, but the ability to take that technology to convert to value and the ability to work and solve that such an industrial grade and also being able to work with a variety of partners that they depend upon. All of those things start playing out. So that's how Unilever and then from there, they became multi-use case customer of us.

So if I can add some numbers to that. So Informatica has the reputation for being a little bit complicated in terms of our financials, many transition stories are. But it's as simple as we have 3 categories of ARR; maintenance on perpetual licenses that were sold in the past, Informatica is 30 years old, and a lot of that was a perpetual license maintenance company. We don't sell any more perpetual licenses that maintenance bucket is, therefore, declining and will forever. Self-managed subscription, which is modern product, but sold on a self-managed basis, so either on-prem or in the customer's private cloud or standing it up on Azure AWS themselves, subscription-based modern product, but end of sale. At the beginning of 2023, we said end of sale because we're an entirely cloud-focused company now. And then the third category is cloud subscription. ARR. That's the IDMC, the Intelligent Data Management Cloud, that grew 37% last year, and we've guided it to grow 35% in this year. So to understand Informatica, you need to understand the growth of the cloud business and how fast are those other 2 going to decline to come up with the total growth of 7.3% ARR that we've guided to in 2024 and faster growth than that in the years ahead as the cloud that's growing at 35% becomes a bigger and bigger portion of our total revenue, and that decline piece has become a smaller and smaller portion. So getting to the point of the new customers in the last 12 months, our cloud NNARR, our net new ARR for the cloud piece, the growing piece was 75% new customers or new workloads from existing customers, so brand-new customers to Informatica or new workloads from customers that have another relationship with us and 25% was migration of customers that have an on-prem maintenance relationship or an on-prem self-managed subscription relationship, taking that workload and moving it to the cloud at what is on average a 2x uplift. They were paying us $100 for one of those on-prem implementations, they choose to move to our cloud. They're paying us $200 on average. And of that 75% that is net new customers and workloads, about 35% of that is brand new logos, people who've never done business with us before. The important thing to understand is while we have this big base of on-prem business that will be migrated to a large extent, over time, that's not what we're relying on for growth. We are winning in the marketplace net new business, 75% of our NARR is new workloads, new customers, not moving from left pocket to right pocket.

Yes. Look, it's an incredible new customer story. Examples like Unilever, brand-new large enterprise discerning customers, no existing relationship. But you did mention you've got a unique position in that you do have this $1 billion on-prem installed base. Can you talk a lot more about that opportunity? Because in one sense, you have the opportunity to migrate, which is great 2x, but you can also upsell them on all the products Informatica didn't even have 10, 15 years ago that are winning all these new enterprises. How do you look at that opportunity? You mentioned previously that you see it accelerating that migration. What's the long term? Will they all migrate? Will they all double? Where do you think it will be medium, long term for that?

So they won't all migrate. There will be some long tail as there is in every situation like this. But we're a long ways from testing the boundary of who will migrate. And in terms of the future potential, you're absolutely right. We see that every day. You see that in our net retention rate, which on a global parent basis is at 125 and end user base is 119. And a big part of that is the first land from a migration customer or a new customer and new sales. I mean, just today, I was reading a WinWire from our field of a customer that has had a maintenance relationship with us forever. 4 months ago, we called them up and said, "Hey, we have this new thing called PowerCenter Cloud Edition, which enables you to move from PowerCenter onto IDMP in 6 months rather than 2." So that's super interesting because we were already in process of moving our data state to Snowflake, and we were going to use one of your point product competitors. 4 months later, we won the deal and our CIO, our Chief Product Officer is with that customer today talking about the second use case, the third use case, the fourth use case, because now they have the platform, the expansion capability is so obvious to them.

So I know we spoke about the migration story, the new customer story. In the new customer story, you talked about MDM. The other big thematic right now is governance, security, privacy. You have a very unique play there. I wanted to just spend a bit of time saying what is Informatica doing in that space? And how is that driving the business right now?

Yes. So data governance, obviously, we all know started years ago when it was more compliance oriented, especially in the financial service sector. I think data governance right now for us is when you look at the businesses on a pair. And I would split the business equally between compliance-oriented use cases as well as what we call data democratization based use cases. Compliance everybody gets it, like, you've got to basically comply to all the different regulatory compliance, whether it's U.S. or Europe, and that's totally fine. I give you example over there a large bank when they have to give their stress test report to the ECB, the ECB looks like, say, "Just don't tell me. Just show me exactly where this data is and do you have those deposits over there that much assets that I can count on." That is a whole governance -- it's not just governance of the [ last in ], managing the whole data workflow to say, these particular billions of dollars actually come from here. This is truly a system of record, and you can see it, verify it and you can file it in the system to say, yes, check the box, not a spreadsheet. On the other hand, every company also democratize data. Everybody wants access to data, but you don't make it to Wild West. So the same capabilities of governance now can be used to manage this Wild West problem into a regulated, complied governed availability of data to anybody and everybody. And under the covers, you can track, hey, look, you want this data. For example, we also took it the last mile to create this -- something called data marketplace. By the way, completely Amazon shopping cart experience. So even you -- if you go there and use it, you can drag and drop the data you want into a shopping cart under the covers the whole governance people who knows whether you have access to it or not. If you do, you get it. If you don't, it will immediately send a workflow to the owner of that data and that person can decide whether or not you get data or not. And by the way, only after full approval, will you get provision that data. In the old days, this was a multi-month process. People used to [indiscernible] even everyone get this. Those 2 use cases for governance are basically growing significantly for us. So that's data governance, and that can be used by any companies like an Anthem, a Mastercard or a PayPal or a Western Union or any other -- or a Ford, so on and so forth for -- and different regions have different compliance purposes. So we see that as a pretty high growth sector for us.

Amazing. The other topic that's been top of mind for everyone in the last year being AI and you guys have a unique play they would CLAIRE. And so I thought maybe we'd start by what is CLAIRE, what is Copilot, what's GPT? What have you been doing? And what are your customers doing with CLAIRE right now?

We really have to talk about GenAI?

Just AI. We don't have to bring the GenAI.

So clearly, something happened in the world called GenAI. I think we all know that AI has been there before. So to give you like a little bit of a history lesson, we launched our AI called CLAIRE in 2018 at Informatica World in May. And we all knew that it was very obvious to us that AI is needed in the world of data. And by the way, the use -- and CLAIRE is embedded in all up, by the way, how we came to the world CLAIRE, no marketing dollars of spend. Our engineers had no room and our belief was this. What do we want our customers to become if they got Informatica players that has, clairvoyant with data. From clairvoyant came CLAIRE. There was literally a working session and we came up with CLAIRE. And our goal there is to take all the machine learning algorithm that exist in consumer world, like we all do photo tagging in Facebook. We converted curated that to make a data tagging. Data tagging, we all know Amazon shopping cart recommendations when you go there, data recommendations. So we took those 1,000s of machine learning algorithms and curated within CLAIRE to make sure it's used for one purpose in data integration, another purpose of data quality or another purpose of data catalog, that CLAIRE is already doing. So when the GenAI wave came, it was not like to start from scratch. We already have an existing AI-powered platform. By the way, CLAIRE runs on 40 petabytes of Metadata in the cloud. So we had CLAIRE copilot available right away. So CLAIRE copilot was launched with GA last year at Informatica. Well, it's available, and our product sits there, and it basically guides users to do. It basically recommend them to do things, handhold them, tell them it's right or wrong, all that kind of stuff, as we sit here today. So when people are making these complex data pipes, warehousing use case, they'll tell you do this and this, it will give you a starting point. Imagine the productivity when we have new IT users coming into play, they don't know we're doing it, so it makes it a lot easier. On the other side is CLAIRE GPT, we all know what GPT is. So it's in private preview. It's a complete chat interface on IDMC, literally a chat interface. If you haven't had a chance, I would highly encourage go to our investor website, we showcased a demo at Investor Day last year, so you'll be able to see a quick demo. In fact on YouTube, you have Informatica World demo. You can literally ask questions, like, for example, give me the sales churn analysis of my Western region. Under the covers, it basically has to go, it has to understand -- for the last quarter, it has to understand sales West region last quarter, it has context from this date to figure out last quarter. It's doing all data management through context analysis. It goes into the right places, picks out sales data for Western region for this time period, then it goes into our data quality move to make sure [ deep ] I can go on and on. You can see it's doing data management under the covers. It gives you a certain result. It matters it shows you results. So you can say, "Oh, I like this. Maybe can you give me this data?" Now it goes and say, "Oh, you're asking for this data." Now it has to go to the owner of the data and say, "Can I provision this data" Well, if you don't have access to it, he'll say, "Well, I got to get a permission." So you can just see suddenly data governance system. So through CLAIRE GPT, we are putting a full-blown chat interface to the platform, and that's going to be transformative. 300-odd large enterprises are doing private preview right now, giving us tremendous feedback, whether it is like 1 customer is doing what we call processing of claims, 2 types of claims. It can be fraudulent claim or it could be right claim, but the process have made a mistake in terms of both of them can have revenue or leakage impact, right? So they're basically using CLAIRE to figure out how they can automate a lot of that work. So that basically -- and there are hundreds of million dollars of worth of savings or revenue upside over there. Those are the kind of things that we think customers say, we're going to launch it next quarter. And obviously, we see that as the next big wave for IDMC adoption and expansion.

And if I can add one thing, the AI part of the Informatica story, everyone has to have an AI part of their story these days really has 2 parts. One is AI from Informatica, which is what Amit just talked about, CLAIRE and all of its capabilities, that's the AI in our product that makes the data management user more productive, get time to value more quickly, have more insight from their data. That helps us win more in the marketplace. We win more deals because we have this capability as part of our product. We don't charge for it explicitly today. We may in the future, but it's a win rate advantage for Informatica. But then there's Informatica for AI, and we'll probably talk more about this, but to have an operational enterprise-grade AI use case, your data needs to be holistic, it needs to be connected, it needs to be governed and it needs to be of high quality. And you need Informatica to do all that stuff to run your AI workload. And CLAIRE makes you accomplish all that more quickly, but the Informatica for AI is a key driver in the future. Revenue impact in 2024, we don't have anything in it in our model because the enterprise readiness to actually stand up those use cases is still in very, very early innings. But it's those 2 pieces for us, AI from Informatica and Informatica for AI.

So let's talk a bit about that. So if you think about AI serving all these -- the data serving these AI and LLMs, they'll need the data from across the system. You guys have a unique play with the data enabler format. But you do that with your partners. And so maybe we talk about both those things. What do you think about strategic partners? How is that changing under the AI sort of premise? And what do you think in the near term you're going to be doing or announcing in terms of partnerships potentially?

Yes. So I think I'll answer this question in 2 part. First is as we talk about the platform. One core thesis. And by the way, that we had a big bet on that, that's going to become a very powerful moat for us in the world of AI. Google index, the World Wide Web. We all know that. We all Google every day. What did Google do? Google basically created a central metadata repository, so when you all do a search, it hits the metadata. Through that, it gets the context of your search and goes and finds the right output wherever it sits and brings it in services to you and you can start accessing information, pretty much search in a nutshell. Our belief was that nobody has indexed the enterprise metadata. So we wanted to be the Google for enterprise data. So when we said about building IDMC, we basically have every 50,000-plus connectors that we have are not dumb connectors. They have metadata. Metadata is data about data, rich context, which, by the way, is very hard to do. But today, we truly have, and I believe, is still scratching the surface. We truly have 40 petabytes of metadata. And by the way, 1 petabyte of metadata is multi-petabytes of data, by the way. So in the world of AI, as more and more AI used Informatica for AI or CLAIRE for AI, you're basically going to leverage the metadata a lot. Now to build on the partnership part. Look, enterprises are supremely fragmented. It's a myth that in the world of cloud, it's centralized. It's not. You ask a customer, where does your customer -- when you go to any CIO, do you know your customer data set? The answer is no. It sits in many systems, for a sales leader, it's in sales force; for somebody else, it's somewhere else. So ultimately, the fragmentation of the landscape is what we make sure we simplify our customers. So in that, we partner with the hyperscalers. We partner with the warehouse players, lake house players. We partner with the GSIs, we partner with many vendors. They are the right ones. We partner with application vendors. And our goal is to be the Switzerland to data to make sure that we can bring it all together. Now coming to partnerships. We, by the way, have been part. We partnered with Amazon, AWS, then Redshift came by. And for all of them, any new technology comes we're the first ones to partner. We know 18 months in advance because we are the only scale vendor that can help them and the large customers. For example, in fabric is coming out. We've been partnering with them for more than 12 months to be the native service on fabric. It's not that we were not naive on Azure, same goes with GCP, same goes with Snowflake or Databricks, Unity Catalog came out, we were there to support it. Snowflake, by the way, the first ones, they needed an SAP application to run on Snowflake, who can do it with us. When Frank came to me, we chatted and then our product team got into play. So same thing working with them. And we just announced a new partnership MongoDB because obviously, as more and more transaction data goes over there, we want to make sure our customers get supported by that. Similar to GSI is a very important one. You all know GSIs play a big role in transformational projects. All of them have Informatica practices, and we make sure that they are enabled. We enable tens of thousands of their people every year. So partnerships are very important to us to make sure we can continuously drive innovation for our customers to drive their project.

And thinking about innovation. If you have this metadata, you have a deep understanding of your customers, you can build many products on it, and that's what you've done. You now have extremely amount of very multiproduct. How do you think about the next product and when you go next? Is it sticking with this and expanding it? Or could there be future stuff that we should be keeping an eye for?

There's always more to do, but actually we're scratching the surface. I look at it this way that we have a $62 billion TAM. We are the biggest player in this market with $1.7 billion guided this year, right, Mike, of $1 billion of revenue. So clearly, we are scratching the surface. When I look at a particular customer, the number of services they use is still not -- they don't still use all my 33 services. And by the way, even if they use 17 of them doesn't matter because the user scale has to go up more and more intensity. So there is a growing up in the same service of more usage, and there is a growing this way of using many other services. We have tremendous room to grow in that. And I think one of the biggest strategy decision every company has to make is to have the impulse and the desire to say no, what not to do. I think we have tremendous room with the organic investments we made with the leadership we have, with the partners we have to scale it out both vertically and horizontally as I gave you. And with the whole GenAI wave in front of us, I think there is a whole new -- this is by the way, my belief. My belief is data management or putting a data house in order is going to become a business process in the next 5 years, just like HCM is a business process. CRM is a business process. You cannot not have your data house in order to do GenAI. So you've got to think of it like a business process. I think it's still in the early days. I was talking to hundreds of CDOs. Last week in New York we had a customer event, hundreds of customers, and that's what they have now realized. That's where the supply chain gap is getting you data house in order. Very early inning. I think we're excited. We're still scratching the surface.

So you spent a lot of time with CIOs, a lot of your customers globally. What are you learning the most from them in the last 12 months, what is the biggest feedback you're hearing? What is -- how is that shaping your thinking?

Everybody is ready for AI, except the data. I think it's the biggest thing. I think everybody looks at what's happening in this 4, 5 things that are -- the whole infrastructure build out and everybody is just obviously getting so enamored by. I think there is -- look, we are in the third leg of digital transformation. It was app-centric, it went infra-centric, now it's going AI-centric. Just starting. Not that the infra-centric is not yet by any [indiscernible]. I think this is the wave of digital transformation that gets supremely accelerated. It has tremendous amount of productivity and value. People are still scratching -- enterprises are catching surface, I believe that in the second half of this year, the first proper use cases are going to get implemented. By the way, even them not fully operationalized because you're a large bank like Morgan Stanley, just imagine the complexity you have, right? So you're going to go do some experiment over here, run it, monitor it and then scale it out, right? I think the next 18 months are going to start seeing this curve. It's kind of like hype cycle. Hype cycle is going to be here, then people like, it's going slow. I think it's just because people don't have the skill sets. They're concerned about governance. This goes about whatever lawsuit comes? What do I get this wrong? What if my brand goes down? There are so many concerns and that's what I'm hearing. But they also realize that good lord, I was running -- cleaning up my data for a project -- now for to get the value of AI, which means holistic data, I got to get 2 things at a large scale. So now I have to go cut somewhere else that budget to do. So I think all of that stuff happened right now. Very, very dynamic times, good things, but I think it will take some time for industrialization of AI in the enterprise one.

You spend time with the customers. You also have a unique vantage point across the whole cloud and data and AI landscape. So what are your predictions in the next 5, 10 years? What's going to happen in these cloud wars, the data platform wars? Where do we end up in 5 to 10 years?