Conference Transcript - NIQ 2026-06-03

Andrew Nicholas, Analyst — William Blair

All right. Thanks to everyone for joining. Appreciate it. My name is Andrew Nicholas, and I'm the business services analyst here at William Blair. Before getting started, I'm required to inform you that for a complete list of research disclosures and potential conflicts of interest, please visit our website at williamblair.com. With that out of the way, very pleased to welcome NIQ to the 46th annual William Blair at Growth Stock Conference. NIQ is a global consumer intelligence company that synthesizes retail, e-com, and consumer panel data to provide a comprehensive view of how consumers shop and what drives purchasing behavior. I have CFO Mike Burwell, Chief Product Officer Troy Triangin here with us today, and we're going to just give you an overview of the business, walk through a few key topics, and hopefully give you a better appreciation for the company. So maybe I'll start with you, Mike, or maybe you could help me with that and provide a brief company overview and walk through the two main segments, the intelligence and activation segment, and what you're doing for customers there.

Michael Burwell, CFO

Glad to do it and glad to be here. You know, look, NIQ is a global system of record for consumer commerce. You know, we deliver the full view of consumer shopping globally overall. We do that for 23,000 brands. We work with over 9,000 retailers. And, you know, look, our top five clients have been with us, you know, literally over 75 years. We cover $7.4 trillion of consumer spending around the world. We operate in 90-plus countries. And we have almost 5.5 million panelists that are giving information as to why they're making those decisions or purchase decisions. And we have 253 million items that we track. I think, interestingly enough, we're processing 4 trillion transactions a week in terms of consumer transactions, and that's up from 3.4 trillion a year ago. And our AI is helping us process that in a much more expeditious fashion each and every day. When we break our business down really in two segments, our intelligence segment, which is really a measurement-based solution as to what, where, how much is really a recurring revenue stream. Think about it as three- to five-year contracts with annual escalators that are included into it. So that's 80% of our business. The other 20% we call activation. analytics-based solutions that really feeds off that data to answer the questions as to you know what you know what's what why did you you know first is what was purchased and then why did you purchase it what else was in your basket so you can help make different decisions and analytics associated with it so you know look we're deeply embedded in clients workflows when you look at us from a NDR standpoint we're 104 percent but if you look at us from a GDR our standpoint, we're 99%. We have very little client churn of our 23,000 clients. So we're very deeply embedded into our clients' workflows and decision processes.

Andrew Nicholas, Analyst — William Blair

Perfect. Troy, thank you for joining us today. Can you talk about the client value proposition, how you're evolving that, and maybe more simply, what makes your data mission critical, important to clients and why you have 75 year plus client relationships all over the place.

Troy Treangen, Analyst — Other

So like we're a hundred percent rooted in a trusted decision grade data set. If you think about the industries that we play in, you need detailed transaction information for a brand to actually work with a retailer to get it on shelf and actually get it in consumers hands. So that's the key around the topic there. But then when you get into the actions, there's pricing, there's promotions, there's assortment, there's understanding your mentality of items. If you have this item versus that item, all of those analytics are built on top of that trusted core data asset. And then how things are evolving in the world of AI is important. The whole objective here is to everybody wants to use AI to do things faster and make decisions faster. In order to do that, you need to have trusted data that is more granular than it ever has been because you don't want to make decisions on a price, which consumer you want to actually target. You need more granularity. That's how the world is evolving. That's where we're putting our energy from just a broader value proposition kind of trend and action list. We are doing many POCs right now with clients to actually tackle that in more granularity and detail. So that's

Andrew Nicholas, Analyst — William Blair

ultimately the value problem. And maybe just to give a little bit more context for the audience, like maybe walk through some examples of what the decisions that NIQ data is helping clients with. I mean, you mentioned promotions, pricing, but maybe some examples just to hit it home.

Troy Treangen, Analyst — Other

Yeah. So you got to think of a manufacturer and a retail, a couple of different lenses. The first lens is they need the data to understand how they're performing and where they want to make their strategic investments. So that's the first bucket of items. It's kind of called internal operations. But more importantly is what I kind of referenced in the last answer, which is how do you actually make decisions with a retailer or where you want to target your advertising to know where consumer shopping behaviors are shifting? That's what's very, very important to kind of go do. So yes, for a specific example, I'll give you one. more and more data or more and more shoppers are actually buying things on TikTok shop or there's an emerging trend of people doing discovery within, you know, ChatGPT or Claude or whatever to find which products they want to buy. In order to actually get that content and make the right recommendations, you need to have really good product reference data. You need to have availability of those products where they can pick those things up. Those are all parts of that algorithm to make sure when you get that answer, it's a realistic answer and an answer that you

Andrew Nicholas, Analyst — William Blair

can action on to meet that expectation. Very helpful. And so, taking all this together, you come up with a business model. Can you walk through the revenue growth algorithm? Mike, I think there's multiple components of that, but I'll let you go through it.

Michael Burwell, CFO

Sure. So when I think about our overall revenue algorithm, we've been in mid-single digits for the last nine quarters. When we look at it, it's roughly two to three points are coming from price. As I said, 80% of the business is subscription-based with annual escalators that are in there in terms of pricing that's negotiated not over the life of that contract, but each and every year. Another two to three points are really coming from cross-sell and up-sell. When we look at our innovative products that we have to be in place those innovative products we're we're bringing them into our our ecosystem and driving it and then lastly is coming from new end products or end markets in terms of what it is that we're doing so we look at you know what we're doing in packaging you know what we're doing to government what we're doing in financial services each of those are new end markets and we're getting about a point there so that's really the you know we're kind of looking at a five to six percent kind of revenue growth range and and And that's really the driver of that algorithm.

Andrew Nicholas, Analyst — William Blair

And can you talk a little bit more about kind of product innovation within that growth algorithm or how important is that to sustaining growth? What are the areas of the business that are fastest growing now?

Michael Burwell, CFO

So e-commerce, you know, we had acquired eight companies in the e-commerce space. Our e-commerce, as we reported on our first quarter, our earnings was greater than 30 percent growth. We're also seeing panels, and panels are growing greater than 15%. We're two areas that we've invested in, and we're continuing to see that. Troy is leading all the efforts that's going on more and more in the AI world in terms of revenue, and I think that's really what we're seeing, the next supercharge that's coming. We've launched our AI Basie screener in the marketplace, which is really looking at synthetic consumers. I've got a new concept idea. We're working with over 70 clients and 2,300 concepts to bring that to life and evaluate that. Where before it was taken months, now we're doing it in a matter of minutes. In fact, one of our clients, you know, has referenced that it's cut their cycle time in half to be able to evaluate new product concepts overall. So, you know, that's just the beginning in terms of where we are, our journey of innovative new products.

Andrew Nicholas, Analyst — William Blair

I think during the first quarter on the call, you also highlighted some competitive winbacks, which at least during the IPO process, you kind of hadn't included in your expectations. So really good momentum there. Can you speak to what's driving that? What brings a customer back after having left maybe a couple of years ago?

Michael Burwell, CFO

I think it's, you know, they're continuing to see the value proposition that we're bringing to the marketplace. And based on our value prop, I look at America's, which is, you know, we kind of split that market with our competitor, and our market in the United States grew 9.3%. I look at, you know, what's, as I mentioned, e-com and panels growing at 30 and, you know, 30 plus and 15% respectively. And I would say in Europe, EMEA, overall, we have brought together both panel information as well as measurement information. We're the only ones who have it. It sits in our product discover and being able to evaluate it. And clients are saying, you know, I don't want to deal with two suppliers. What you're delivering to me, it really differentiates that decision process. And therefore, it's differentiated. And ultimately, you know, we delivered, you know, 17 seven-figure wins in the first quarter alone. So I feel very good about the momentum that we're seeing overall. And as I say, with what Troy is building and leading, the AI world here is really only going to supercharge where we're going to go going forward.

Andrew Nicholas, Analyst — William Blair

That's a great segue. So wouldn't be a conference Q&A in 2026 without some AI discussion. So Troy, maybe to level set, and we've written this several times, I mean, a big part of the investor community is focused on how proprietary the data is, how the data is accumulated, how difficult it would be to replicate. So can you spend some time talking about how it's sourced, how it's differentiated, what's proprietary, what's

Troy Treangen, Analyst — Other

analytics, and maybe we'll go from there. Yeah. So over 90% of our data is actually proprietary. And it's all built on three foundational layers. Number one, it's on governed retailer relationships. There's a trust factor in our industry. Like there's over 160 retailers in the U.S. All those retailers share that data with us and expect us to treat it in a way where we protect certain aspects of that, right? So that governed relationship is very, very important. And I just talked about one market. Think of doing that in 90 markets. So that's a lot. The second thing is we have consumer panels that are all over the world, which you have a trusted relationship with consumers. that are actually keeping track of all of the things that they buy with their receipts and all that, that we then collect on top of it. And that's the second part. And then the third part, which is kind of under, it's not talked about as much because it's not a, it's all of the glue and the decoders that make all that data talk together. We call that our product content a lot of the times. So when we say that this sparkling water is in this category of water, like that all of that matching and mapping across all the different retailers all the consumer receipts that come in makes it so we can get a trend and data within that so that's ultimately our moat in all the markets that we play that's that's the core core capability now how do you actually activate that with ai is what is the next phase you either do core analytics to make you determine some of the things we've already talked about which is what's the right price what's the right place that you put this product. All of those things are analytics that help manufacturers and brands figure out what to do. The second layer is AI enablers, which is all about, like I mentioned already, speed to those decisions. How much faster can you make these decisions, and how often can you pick up what new trends are showing up in the marketplace to be able to react to those? We were having a meeting just a little bit ago, and I gave the example that we're now actually monitoring trends, especially from the Asia part of the world. We actually just had a thought leadership study that came out about East meets West, what beauty trends are happening in Asia, what other trends are happening in Korea, and can you adapt those and bring those products to the U.S. to capitalize on that same type of thing, which is a very common thing these days. So that's where AI helps understand the trend, but also then react to the trend and adjust it in our products

Andrew Nicholas, Analyst — William Blair

so we can deliver faster insights. Are there any kind of regulatory considerations to kind of keep in mind when it comes to managing data, selling this data that could be supplemental to the moat?

Troy Treangen, Analyst — Other

So I think there's nothing really regulatory that we have to worry about within our business. You know, we do have certain things we obviously got to protect. And when I'm saying protect, that's more of a relationship protection than a broader government kind of issue there. So it's actually a positive, I think, for us that have this trust with these relationships, we can use that to our advantage. Great. So maybe

Andrew Nicholas, Analyst — William Blair

I'll ask Troy, Mike highlighted some of the product innovation that's already happened on the AI front, but maybe you could spend a little bit more time talking about product innovation tied to AI to date. It sounds like those are driving some competitive wins, some win backs, but maybe a little bit more on what products are out there that are new and maybe even what's in

Troy Treangen, Analyst — Other

the pipeline yeah so from we break up our products into two big buckets like we've already said so we have our activation set of products which are ai native products like he already mentioned like ai screener that was where you actually can go out and understand what innovation you can bring to market you understand it from synthetic respondents that's our those are basically ai digital twins and you can actually make innovation faster and bring it to market here to give some stats on that so that's one example we also got these things called product developers they're different things. Think of this space. It's all around how do you actually work with a manufacturer and how do they create innovation faster in the market, whether that's a new twist on flavor or whether that's a completely new item that you want to be in a category. There's a series of products that we're launching and we'll continue to build in that space, primarily on the things we talked about, which is how do you make decisions faster? How do you bring innovation faster? How do you get some insight that you need to uncover? And the other thing to just say in that space that's very, very important. Granularity is key to making those decisions. Think about even in your lives today, everything is becoming very micro for a brand and a consumer of what they want to buy. Ten years ago or so, a P&G or some company could mass market products. You just go out and say, I want to have just this one water. That's it. All consumers, that's what they want. I'm going to make it. That's not how it works anymore. Everything is getting micro-targeted to specific demographics, specific areas of the country. Most retailers in the US now allow a percentage of their store to be local assortment. So store managers now have the ability just to bring in their own products based on the demographic that sits around that store. So all of those things, when you talk about bringing some AI capabilities to determine those, that's bucket one. The other part though, which is in our core business, which is on our measurement assets, which is, he already mentioned Discover. We actually have three different buckets of products that we're working in that spot. We are saying, how are we building better AI and our tools to deliver those insights? So we have this thing we call Optic, which is our AI chat interface. We build that on top of our components so people can navigate our assets easier and faster. That's bucket one. We'll have some more announcements right around the corner about some innovations that we're launching. And the second bucket in that space is all around what we talk about delivering AI capabilities with our clients and in our clients' environments. So we work with them and have products where we allow a manufacturer, retailer, partner of ours to actually connect their environment to our environment so they can activate those AI components faster. So maybe they have an AI set of models or they have their own chat interface that they want to use. So we plug and connect those as another way to consume those assets. And then third is all around working with the leading, you know, call it LLM tools, so you can actually connect to our assets within those. So next week, we've actually already launched it, so it's not anything super private, but we're going to highlight it next week in our conference. Like right within Claude, you can actually connect to our environment to actually use Claude capabilities to understand what's happening in NIQ trends, the data that we provide, and do some level of analysis. So the point I'm just trying to make there is we have a three-pronged approach. Our tools, our clients' tools, and then also leading market tools, all three of them, we're innovating and building capabilities with that.

Andrew Nicholas, Analyst — William Blair

And maybe that final bucket is where you find agentic commerce. It seems like that's an area that you're really excited about. You guys spoke to it quite a bit on the last earnings call. Maybe you could flesh out that opportunity. Why is it important? And why do you see the market going that way? And why is it like you?

Troy Treangen, Analyst — Other

So agentic commerce is just another channel that's evolving. So, again, if I go back 50 years ago or 20 years ago, almost all the groceries and, you know, anything that you would buy was always through a brick and mortar store. That has obviously evolved to be more e-com, which is a big general bucket, which says you go to a website or use something to go get that and get it delivered to you. But e-com is evolving. You know, if you go back to social commerce was an emerging trend within the last couple years, that's the definition of like TikTok shop, right? So you're in a social media, you know, kind of based platform. It's got a store, you're doing live shopping or whatever the new trend is, and then those are sold. That's just an evolution of, you know, kind of an e-com type thing. Agenda commerce is that next evolution, which is on top of that, when I'm in an LLM and I'm just doing product discovery and I want to buy it, that's just another channel to us. So when we talk about Agenda Commerce, our whole value proposition as a company is to measure where people are buying things and informing with our partners what's happening and what decisions to make, like we've kind of talked about. That channel is shifting. So we will innovate and create products in that space. So that's the first part. The second thing that's really important in agenda commerce is it changes the way that the data, the granularity of data that's needed to transact in that environment is way more granular than all the other channels have been. Because if you think about what you do is you go in there and say, I want to go buy, we use this example a lot, a high protein granola bar. It's easy. Usually a product says those things, right? So you could filter out, you can do a web search. It's already collected through various pages. I know they say high protein on the package so you can kind of filter it. But the next set of questions that people usually ask these days are not specific about how many calories is in this. They want something that is derived, which is what we call derived on top of it. So I want something that's heart healthy. I want something that's a clean label. I want something like that. That question is not an easy question to answer. You have to understand what are all the ingredients of this product? What other trends are in the marketplace that you got to connect that data with? Then in order to filter that question to what you're actually asking for, you need a new set of data capabilities to be able to do that. Now, in the old world, again, you would make that conclusion and just do it on your own. You would say, what is clean leave? You do the research. The LLMs are allowing to interpret that and do that for you, which again, it needs those assets to do it. So that granularity is very, very important. So when we think about Agenda Commerce from a product standpoint, we have four buckets that we're going after. There is the discovery part. So as you was, I'm sure, there was just a recently study that we put out, over 50% of shoppers are already using an LLM to do product discovery. I mean, that's a pretty big number already, how quick this has been. But it's like, how do you actually report on that? What's the share of discovery? How many people went out and searched for this sparkling water last week within the various LLM? So that's product development number one is share of discovery, share of components. Then there's the quality metrics went in there. When the results that they got back, did they actually meet that requirement and expectation of what they were asking for? So going back to my clean label example, if they asked for products with a clean label, did what come back? What do they actually clean labels? Was it a good or a positive or negative? So that's bucket two. Bucket three is where did they leave from that LLM? Did they actually go to a website to buy it? Or did they just drop and then they maybe bought it in a store? That's still some path to purchase stuff to figure out. But that's bucket three of product innovation. And then bucket four, which is what we've always done, which is the measurement of that channel. And the measurement of that channel is important because when I was talking earlier about it's just a new channel that's emerging, people want to understand where that volume is shifting from. You as a consumer are not going to buy everything on an agent of commerce incremental, right? It's like, yeah, I used to buy 100 units of this water at Costco or pick a store. Now I'm not. I'm only buying 80 units from Costco, but I'm now buying 20 through an LLM-based service to kind of do it. There's a shift that happens. There will be some incrementality, don't get me wrong, but it's not 100%. So you've got to understand that in there. So long answer, but the big four points are the whole thing about measuring discovery on what's happening, but also the quality of it, where they're going from that discovery. So where did they actually go click? And then fourth is you've got to measure the sales. Did they actually get that conversion? All those things are very, very important for a brand or a retailer to understand, to actually know how to talk to the right consumers, market them to in the right way, and all that. And that's, at a high level, that's what our business is. It's just this emerging channel is just changing dynamics a little bit.

Andrew Nicholas, Analyst — William Blair

And, you know, there's a lot of different ways for people to interact with the data. customers are now interacting in a bunch of different ways whether it's in your tools in their own environments we're talking about all that so in like at a bigger picture level how do you see kind of data usage evolving and does that impact the way that you price for that

Troy Treangen, Analyst — Other

the pricing model yeah i mean the the commercial model is starting to shift right it's not just us doing it the industry is shifting which is we call it a hybrid model which is there's a base set of fees that to get going and then there's consumption based models on top of it exact same way that you would buy Claude license today, right? You have a certain number that you have, and then you get a certain amount of consumption, and when you run out of those credits or tokens, you've got to buy more. Same type of way that our business will evolve and has already started to evolve. So that's kind of the trend on the commercial side of things, or the commercialization and the pricing side. But the second part of that question really is around how are we ensuring that demand is increasing with the data asset, right? We already talked about that in the the data usage overall, but we're not going to be requiring people to always use our tools to go do that. We allow, like I said earlier, all three different options. So however you want to consume it, we are completely happy. We'll fit into your supply chains. We'll do our own. We'll work with partners. And like I said, the clods and all those things out there to do it. And then our monetization will be consistent and we can pick up transactions and revenue from all three of those

Andrew Nicholas, Analyst — William Blair

buckets. Great. Thank you. We have about five minutes or so. I want to make sure we hit margins because that's a huge part of the story, I think. So, Mike, can you talk about, I mean, there's been quite a bit of progress on the margin front over the past several years or since the carve-out.

Michael Burwell, CFO

Can you kind of just talk about that in the runway? Sure. So, at the time of the carve-out, this is March 2021, the margins in this business were looking roughly around 13 percent. reported at the end of the first quarter at 21%, which is 150 basis point improvement through the fourth quarter of last year. We've given guidance that our margins will be 23.5 to 23.8 by the end of this year, and that our midterm guidance will be at 25%. And we see a path to ultimately 30% margins in the business. What's happened in the first quarter has really been the GFK integration that we've had going on, as well as our productivity actions that we've done. And that drove about 100 basis points of margin improvement. And with our fixed cost base at 80% fixed cost base and the nine quarters of mid-single digit revenue growth, we're driving abruptly about 50 basis points of margin improvement overall. So we continue to see very good opportunities within margin. And we've only gotten started really on the AI side. You know, we are coding more and more, you know, being done through AI. As I look at our back office actions and opportunities, they're real. And we're going to continue to see more drive as it relates to margins going forward.

Andrew Nicholas, Analyst — William Blair

Great. How about capital allocation? I think it'd be helpful for, you know, a newly the public company. Kind of just walk through your framework there, how it's evolved since going public, where you sit in terms of the balance sheet and how you expect to use cash

Michael Burwell, CFO

going forward. Sure. So we were, we had put at the IPO date that we would get our leverage down to three and a half by the end of 2025. We were at 3.4 in terms of where we ended at the end of 2025. We've put the target to be below three by the end of this year. We're on track to get there. that's number one on our mindset. Our TTM was $130 million positive through Q1. Q1 is a low point for us. We pay bonuses, more of our IT payments, and more of our data costs are actually happening in the first quarter. And then the cash flow ramps up through the rest of the year. When we look at share buybacks, we only have about 15% float in the business right now. So the opportunity to do share buybacks, we just don't see it as a great opportunity. We put things in place to be able to do that at some point, but we're just not executing on it until we get our debt paid down. In terms of acquisitions, we will continue to look at, you know, deals that make sense. We did two deals last year, Gastrograph and Emtrix. One was an ingredients business and the other one was really a supply chain business. Think about them in the 25 to 50 million kind of range and equally, you know, in that kind of revenue range. But when you bring them into our distribution channel, they're accretive really fast. So we don't see a big transformational deals. We don't see that we have a product gap. We don't see we got a geographic gap, but we see these opportunities that are really going to accelerate our business and those things are in place. So if I kind of recap back, going back saying debt pay down is number one focus right now. We're going to continue to look at acquisitions that make sense in terms of what's happening. We'll always keep opportunities open to think about, you know, when would we do a share buyback? When might we think about dividends? Those things are on the table for us. But right

Andrew Nicholas, Analyst — William Blair

now, number one is focused on getting that debt paid down. Great. Maybe one more I'll squeeze in just on kind of guidance and guidance philosophy. As a public company to this point, you've been very successful in outperforming your expectations, street consensus. Can you speak to that philosophy what what you're going to have out there in your guidance now and maybe um upside or downside to to what you have out there for the full year yeah so um you know both jim and i this

Michael Burwell, CFO

isn't our first rodeo um in terms of of being you know senior executives at a public company so our philosophy is make sure we put expectations out there that we can meet or exceed um you know and make sure we're consistent about that and and we think that's the right way to to set it up having said that we don't want to you know be overly you know cautious either so we're trying to make sure we we set that bar at the at the right at the right level um so for the last four quarters we've met our you know the objectives that we've put out there we've we've done that um going forward you know when we looked at the first quarter for ourselves um you know we had a couple wars going on. We're looking at our competitors that were almost a lot of them were beat and hold, if you will, in terms of thinking about it. And so we evaluated that ourselves and said, that's probably where we need to be at this point in time. But we're not giving up in terms of what the year is going to look like. I said on the first quarter earnings call, April looked very good, better than what we saw in the first quarter. So we'll reflect our guidance going forward based on what we see happening, you know, overall, and we know it's important to be able to make sure we give, you know, the right guidance as we think about our

Andrew Nicholas, Analyst — William Blair

future. Perfect. With that, we'll wrap it up. Thank you to both of you for being here and engaging with me. Thanks to everyone in the audience. We're going to be moving to Richardson for the breakout for anyone who's interested. Thank you.