Total Market Measurement with NielsenIQ's Kim Cox & Richard Pereira

SPEAKER_03 0:00

I'm Richard Pereira, North America product leader for Nielsen IQ.

SPEAKER_00 0:03

Hi, I'm Kim Cox, North America Managing Director of Omnichannel Intelligence Solutions for NielsenIQ, and you're listening to the CPG Guys Podcast.

PVSB 0:14

Hello and welcome to the CPG Guys Podcast, set at the intersection of commerce and tech. Your hosts, Sri Raja Gopelin and Peter V. S. Bond, explore how brands and retailers engage consumers in a digitally driven world. And now, here are the CPG Guys.

SPEAKER_05 0:33

Hello and welcome to this episode of the CPG Guys Podcast. And of course, Sri, your co-host and also CRO and co-founder at ThinkBlue Consulting, your trusted partner in their omnichannel development journey. Get in touch with me at Sri at thinkblueconsulting.co. Please do listen to my older daughter's music at www.rearaj.com and my younger daughter, Lara Raj of the band GapShi. We just got done with Coachella 2026. We'll be headed to Lapalooza, Chicago, and they're headed to the UK as well as Korea, and we've got a whole fall tour coming up. And then lots to announce with RIA as well. I'm joined today by none other than the notorious PIG himself, Mr. PBSP, who also moonlights as head of industry and client engagement at Flywheel, Commerce Acceleration Division of Omnikom. Peter, tell all about our visit to Yankee Stadium on none other than Jackie Robinson Day.

SPEAKER_02 1:31

You are the notorious, you're the actually the Tupac to my notorious VSP, but it's good to see you, Sri. Yeah, we we managed to make our way over to the Bronx and Yankee Stadium for Jackie Robinson Day. It's great when you and I can put aside our baseball rivalry differences and regale in everything that Jackie Robinson stood for, his contribution to the game, and both of us wearing our number 42 on our jersey. It was uh it was a pretty phenomenal evening, and we had front row tickets. It was pretty good seats, Sri, don't you think?

SPEAKER_05 2:04

Awesome seats indeed. Watching Judge that close up yet again for the 50th time, it never gets never gets old. And then how about the exploits at our favorite store? What is what would that be?

SPEAKER_02 2:14

Well, uh anyone who's watching this on video can see that I am wearing my my Dodgers shirt and my Brooklyn Dodgers 50th uh anniversary of Jackie Robinson Day hat. So uh yeah, saying that to our accountant because that makes this a deductible expense. But yeah, we we did manage to make it over to the MLB flagship store on Avenue of the Americas, and we uh we we did a little damage to the corporate card shrewd, wouldn't you say? Yeah, I think that was great.

SPEAKER_05 2:43

Actually, let me remind you this is not a baseball podcast. So I'm gonna go to the case.

SPEAKER_02 2:46

No, it is. It is. No, it's baseball. Uh well, you know what? We're gonna we're gonna ask one of our guests if if he thinks it is or isn't.

SPEAKER_05 2:54

We it will come back and ask for sure. There we go. So make sure you're subscribing to our podcast on your preferred listening platform where you can get our latest episodes, go back and consume the 580 plus episodes we've already published with who's owned retail and CPG, and now let's jump right in as promised. Phenomenal show lined up today. If you've been paying attention to the retail landscape lately, you know that the old way of measuring success is officially moving out the window between the explosion of army channel behavior, the rise of retail media, the shift towards first party data, ecosystems, brands are finding themselves swimming in the sea of data but starving actual alignment. The question isn't just how did we sell, how much did we sell anymore? It's where do we sell, how did the shopper find us, what part of our tech stack actually moved the needle? You heard me right, Peter. Tech stack moving the needle. To help us cut through that noise and find the signal, we're joined by two absolute powerhouses from NIQ, who are essentially building the dashboard for the future of our industry. First up, we have Kim Cox, as mentioned, the managing director of Omnichannel Solutions at Nielson IQ. Kim is a total heavy hitter when it comes to strategic thought leadership and understanding the why behind the shifting consumer joining. Joining us Richard Pereira, Nielson IQ's North America product leader, period. Richard is the one under the hood driving the innovation analytics, AI, and measurement tools that are going to separate the leaders from the laggards over the next few years. Join us in welcoming to the CPG Guys, Richard and Kim. How are you both? Welcome to the show.

SPEAKER_00 4:27

Good. Excited to be here. This is my third time on the CPG Guys podcast. I'm going after that jacket. But it's exciting to be here with Richard, too. Richard and I have worked very closely together, pretty much tied at the hip for the last five years or so, bringing some really cool things to market. He does the hard work. I talk to the clients, but really exciting to be here today.

SPEAKER_03 4:47

It's my first time. Thanks for having us. Really excited to be here.

SPEAKER_02 4:49

Well, Richard, you know, five times on the show, it's like Saturday Night Live. You get the coveted five-timer varsity jacket here on the CPG guys. So Kim's Kim's checking off. She's she's three down, two to go. And trust me, she uh she she's seen the jacket up close. Uh our our our dear friend Liz Buchanan has one of her own, having earned that outright. So it is it is uh a very coveted piece of of swag, to say the least. So good luck, Richard. He did. We gave it to him down at Cagney, and he was the talk of the show.

SPEAKER_05 5:26

All right, it's digital sh wait, wait, wait. First we got to welcome. And for the record, we have a Dodgers fan, Yankees fan, and a Toronto Blue Jays fan who nearly pulled it off last year, and I was actually rooting for him, and I couldn't believe they messed up the ninth inning. Not once, but twice.

SPEAKER_02 5:44

It was heartbreaking for me, Shri, because like that's my favorite American league team, and I would have loved in any other year to root for the Blue Jays. But my blood, you know, my blood runs Dodger Blue.

SPEAKER_05 5:56

Very quickly I switched to he's got 17 more championships to strive for before he can talk to me about a winning legacy. But anyway.

SPEAKER_02 6:03

Shohe Otani, greatest baseball player ever.

SPEAKER_05 6:08

And IQ's corporate website for listeners to access while we go on with that conversation. And now we're gonna jump into the questions, but before we do that, I'll give Peters time to panther back. Go for it, Ben.

SPEAKER_02 6:19

Listen, Shoei Otani, greatest baseball player ever. You will feel that the summer when I take you up to the Hall of Fame and you see the the stats there and you realize Shoei is gonna they're gonna give a whole wing to Shoei when he returns. A whole wing is going to go to Shoei Otani. He is he is the greatest baseball player of all time.

SPEAKER_05 6:41

No, they'll be AI players by the time 10 years happen.

SPEAKER_02 6:44

So good luck.

SPEAKER_05 6:45

Let me jump into our questions, Peter. It's about done. So let me first start with Kim. And the first question is who's your baseball team?

SPEAKER_00 6:53

So I live in Columbus, Ohio. So we don't really have a baseball team here. We have some minor league teams, but no uh professional. I lived in Cincinnati for a while and at that point um did kind of fall in love with the Reds for a little bit. We actually named our dogs after two of the announcers for the Reds. Uh, first dog, Marty Brennan, was named um Brantley after uh Jeff Brantley, and then the second dog is Marty after Marty Brennan. So I have to say the Reds.

SPEAKER_02 7:21

Okay, good answer. Good answer.

SPEAKER_05 7:23

It's a very announcer, a true baseball fan. So we've got four baseball champions here.

SPEAKER_00 7:29

Yeah, it's my husband who's a huge fan. I just kind of went along for the ride.

SPEAKER_05 7:34

That's what they say when they name their dogs off the announcers. They're not fans. Yeah, sure. We're buying that. But Kim, I'm gonna jump into share measurement here. We often talk about winning share, but the definition of a market is changing by the day. From your seed leading omni-channel solutions, how is retail measurement fundamentally changing in terms of how brands now have to think about competitive visibility?

SPEAKER_00 7:56

Share growth is very important right now for a lot of categories. As we've been talking to customers, of course, they're talking to us about the baby category and the declining birth rates that they're seeing. So growing share is incredibly important across the food channel. We're seeing a lot of research, especially pertaining to the K-shaped economy, that mid and lower income consumer are really cutting back on food purchases to save money. So shares are incredibly important, but you're also right that the market is changed and can't be defined by a single point of sale universe anymore. Consumers are shopping in a truly omnicommerce way, which has been that way for a little while now, but it just continues to evolve. Direct-to-consumer continues to be important, third-party marketplaces more important than ever. Social commerce like TikTok is continuing to be not just a great place to buy products, but also a huge influencer on consumers. So the market has changed, but on top of that, not all retailers, Nielsen's known for our cooperation with retailers and the POS universe that we've built over many, many decades. But not all retailers want to share point of sale data in a very visible way so that you can see data at an account level and that you can act on it to try and impact your share. It's not just about reading your share, it's also about how you can impact and grow your share. So, our belief and what we've been working on over the last several years is really making sure that not only are you looking at traditional retail point of sale data as your foundation on foundation, but if you do that, you're gonna have all of these gaps. So we try and look at all of these additional demand signals coming from wherever we can get high-quality data so that we can create the broadest measurement universe available, but also a very granular item level, banner level view that creates more actionability than if you just have a universe that is large and you can't actually see what's in it.

SPEAKER_05 9:56

I just have a quick follow-up to that, Kim. So, anywhere in these conversations with CPG or retail, is a conversation coming up about share of market, the incrementality piece of this, because for a long time now it's been quite a zero-sum game from a volume perspective, which means if someone's winning, someone's losing pretty badly. And are people curious? Can I drive incremental share, grow the whole total store, things of that nature? Just that word incremental does it come up and what do they ask if it does?

SPEAKER_00 10:27

Yeah, it comes up constantly, especially as companies are trying to get additional space on shelves, thinking about their innovation portfolio and what are they gonna bring on, what are they gonna bring on, what are they gonna take off? Because you're right, like they they all need to look for incrementality because it's just is the fact it's gonna be how you grow. It's not gonna be just taking volume back and forth across each other. Everybody's trying to find that next incremental item that a consumer will put in their basket.

SPEAKER_02 10:55

Richard, welcome to the show. We're really happy to have you here. AI and machine learning, those are big buzzwords this year. Uh, but I'd like us to get a little more practical in understanding what those mean. How are these capabilities actually changing day-to-day experience for a category manager doing their job leveraging Nielsen IQ tools right now?

SPEAKER_03 11:22

So the practical effect is really that AI is moving category management from a more manual interpretation towards uh really more automated insights and guided decision making. Historically, if you look at it, a category manager would have had to spend quite a bit of time stitching together a bunch of data themselves. So not only syndicated data, but also e-commerce data, uh, direct retailer input data, right? Maybe some panel data added on top of that to provide some context. And that takes a lot of time, right? It's really not the best use of time for the very talented people that you meet who hold those roles, right? So, what AI and machine learning are really doing here is reducing the burden on those teams significantly. And we see that across the board in all sorts of different tasks, right? So there's anomaly detection, there's prediction of product attributes, there's normalizing all the messy e-commerce data sources that exist out there. And increasingly those technologies are being used to quickly take care of all of that so that the users can actually focus on the drivers of the change rather than pouring over all that different data manually. So in practice, the day-to-day experience becomes less about asking what happened and more about understanding, well, why did it happen? What should we actually do next based on what happened? And I think that's the real unlock here. So at NIQ, we're not really chasing AI for the flashy aspect of it or for novelty. We've been working with AI for a long time, and we're focused on using AI to basically shorten the path from data to action. It really only matters that it improves trust, speed, quality, coverage, or the end user experience. If it doesn't do one of those things, it's just decoration and all the things.

SPEAKER_05 13:01

So, Richard, does that mean as you work with AI more and more and its prevalence in the day-to-day use of category management just becomes normal, that the tools you continue to build and put out in the marketplace will automatically have an infusion of AI in it?

SPEAKER_03 13:19

Absolutely. You see that in some of our other capabilities in the Discover platform right now, it's going the direction everyone thought it would go, which is these capabilities are just going to become more like the push push of a button on the front end. And that's really the experience that we want to offer.

SPEAKER_05 13:32

Does that mean logically it's a movement from dig and discover to insights?

SPEAKER_03 13:40

It means the the insights will be surfaced more naturally within the tool. You're still able to go in and make your own selections and whatnot, but you're getting to the point now where you can simply ask a question. Discover is going to go in, find the data that's relevant and answer that question, piece together a whole story and narrative on your behalf. And that's powerful.

SPEAKER_05 13:59

Thanks, Richard. So, Kim, consumer behavior is fragmenting across QuickCommerce, DDC, TikTok shop, social commerce. How are your strategic models adapting to end-shop brands aren't just seeing data snapshots, but actually ensuring measurement of a fluid omni-commerce, omni-channel journey in a world where trends come and go and are born and die so fast within weeks and months.

SPEAKER_00 14:26

I 100% agree with you that the shopping journey is complicated. It's not linear anymore. So, not only do we want our clients to be able to see the full sales universe, like I had mentioned before, with robust omni-channel sales universe with high degrees of visibility at an accountant item level. We also want to enable our customers to be able to look at a consumer panel lens. So you know your sales are going up or down, your share is going up or down, but what's driving that? What are the consumers, which demographics? Are they increasing penetration? Is it improvements in buy rate that's driving those share changes? And our approach is to make sure that we're measuring the full consumer. We have the largest panel on the market, and it's built so that it not only captures the in-store purchases, but also those digital purchases. And when you bring that all together in one platform, like Richard was talking about, you not only have all of this great sales data, but all of this great consumer level data coupled with AI in one place allows you to just be able to get to insights in a very fast way. So our clients have been really happy with the experience that they've been seeing, and it's been fun to bring it to life.

SPEAKER_02 15:43

So, Richard, uh I want to talk a little bit about the club channel, Costco, Sam's, BJ's wholesale. The the growth that's going on there is is quite impressive. But historically, club has been a bit of a black box for CPG analysts. What makes club measurement so uniquely challenging? And how is Nielsen iCube helping brands find the full view of performance in this channel?

SPEAKER_03 16:16

Yeah, club's uniquely, uniquely difficult because it's not just another retailer. It actually behaves very differently at almost every level. You're dealing with very different pack sizes, uh typically a much smaller assortment. Uh you could see much bigger swings on any given item. There's quicker rotation, a lot of in-and-outs in the club space. And that generally leads to a much tighter relationship between your product's distribution and ultimately its its performance. So in Club, what we find is that all it takes is one item, right? One item gaining or losing traction in the club space can move your business in a way that is much more consequential than when you compare it to traditional channels, right? The second big ch challenge in the club space, in terms of data availability and current measurement solutions, is that most views of that channel are pretty incomplete, right? When you're making these high-stakes decisions then in this channel, from what's actually a pretty incomplete view, that that false sense of certainty that you get from that can become very expensive very quickly. So our job in NIQ is not to be okay and kind of accept that there are these opaque solutions that exist in the market. The job really becomes about developing the most complete and actionable view of club, which we've done last year, right, through our through our full view solution. Because what we find that the brands really need in this space is not that false sense of certainty, but rather a more granular and complete view of the channel so that they can answer these day-to-day questions that are coming at them, right? Am I growing because of real consumer demand? Or is it because of my pack size dynamic versus a competitor, or because of a certain promotion that was run, right? Commercially, those are the distinctions that you need to make to help you do your job.

SPEAKER_05 19:22

Richard, you know, Peter and I, you know, the CPG guys have often said you guys have a superior solution to others and the marketplace.

SPEAKER_04 19:29

Because with the others you can report with the solution that you bring, you can actually take and you can get insights and you can go deeper into the data. Can you explain why that's the case?

SPEAKER_03 19:41

Yeah, it's critical. And our solution is differentiated in that regard. You can go down to the individual account level, you can go down to items that are typically masked because uh they're perhaps exclusive in the club or they have a pack size that would otherwise expose them. Uh even private label is visible in our solution, and it's critical for all those reasons that I mentioned. Particularly, you know, if you look at the smaller assortment and you you can't really see the one or two items that you're competing with against the space, you're flying completely blind in the club space. And that's not exactly useful as a brand. So the visibility that you get from our solution uniquely and the ability to view that all in an unmasked manner and run analytics at that level is uh is a differentiator, and we're we're hearing that directly from our clients in the space. They're getting a lot of utility out of a new full.

SPEAKER_04 20:27

It's important that the industry understands why we say that. And the other dumb market measurement quite a bit before using it on the tools. In practice, how far away are we from truly achieving full-fluid visibility? What I mean by that consumer behavior, directly to purchase and allow the all-important word to become a value.

SPEAKER_00 20:53

Yeah, when it comes to total market measurement, we're actually really close to a total market view. And we do that because of all of the different ways that we've started to describe looking at different demand signals, whether it's from receipt panels, whether it's from um inbox scraping, whether it's from web scraping. There are so many great ways to collect data and using really strong data coupled with really strong measurement science and product leadership capabilities, like Richard Branks's our market, is a great way to bring a total view together. So as we launched our Costco launch, it's sourced mainly from consumer receipts, but from millions and millions and millions of receipts. And when you have that level of receipts all coded to a UPC, it looks just like synthetic point of sale data. So I feel really good about total market measurement. We've got great coverage of direct-to-consumer brands, Amazon 3P, as well as you know, major powerhouses like Walmart, Amazon 1P, Target, and others. So I think that's that I feel uh really strong about the um incrementality. I'm gonna maybe take it in a couple different ways. So you have talked about incrementality as you know, incrementality adding another item. Does um the shelf get an incremental sale for the category? Do you get an incremental sale for the brand? We have great capabilities that do that today. We have a platform called our assortment analytics capability. And as a part of that, like that's a capability that can help you help manufacturers get visibility into which items are incremental. But I think sometimes we also think about like incremental, are we getting incremental value from our retail media activities or from the investments that we're putting into making sure that our PDPs look really good or our TikTok campaigns really resonate with the consumer? Is that an incremental sale, or would I have got that anyway just by putting a product on a shelf? So that one's a little bit harder to measure. There are some companies that we're partnering with and providing data to that help us and help our clients measure incrementality. We're exploring it, of course, because we do know that all of those things that I just mentioned, your PDP, your TikTok campaigns, they do influence sales too. There was a really interesting Forrester article that I was reading recently that had said that in um 2025, about or I'm sorry, 2021, about um 60% of sales were digitally influenced. And by 2027, 70% of sales will be digitally influenced. And I think that makes sense. You know, we see something, we might buy it online automatically. We might wait because we see it on TikTok, but we don't want to wait seven days or five days for it to come and we might go to Target and buy it there instead. So I do think it's harder to measure. It's important to measure. We're exploring how do we um how do we do that? Because we know through talking with a lot of our clients, that's what they need. They need some help measuring this space so that they're spending correctly and spending in a way that's going to help them grow share or grow profitability.

SPEAKER_05 24:03

So Kim, here on the CPG guys, Peter and I have often said the path to purchase is almost nearly 100% digitally influenced. And I heard you say closer to 70% numbers, but did you say that was a 2024 number?

SPEAKER_00 24:17

So the it's a Forester study that had said that in 2027, 70% of sales will be digitally influenced. Yeah.

SPEAKER_05 24:24

Interesting Peter, any thoughts on that?

SPEAKER_02 24:26

Yeah, I I think I think we're a little more bullish. And it really comes down to a matter of degree. They're probably saying that they can it's a it's a measurable 70%. But I think that at this point everything touches digital. We all carry around these devices that put information in our hands. So I'm I'm gonna stick with our 100% estimate, Sharia.

SPEAKER_05 24:49

But Peter, on every episode of the show, we have to quote a word, did you forget what it is? Which means there's a 30% universe that lives out there who are Luddite.

SPEAKER_02 24:58

Yes, they they they are. That's okay. Let's let's not let's bring people together. Let's not divide. Um, but I absolutely agree with you. And I Kim, I will just say your articulation of how Nielsen IQ uses the best available data coupled with the right techniques to bring the full view together is really what is the secret sauce that Nielsen IQ brings to the industry. So if we sit around waiting for everyone to hand over what is the equivalent of club data, where you have 100% of all items purchased associated at the household level, that's just not realistic. And we can't let perfection be the enemy of progress. And I think what Nielsen IQ has done is really put together incredibly good techniques to take the best available data from multiple sources to create that full view. And I think you did a great job of articulating that. What are the current, what are the current best practices or innovations around product that you're really trying to lead that will produce a more unified and full view picture for for your clients?

SPEAKER_03 26:20

Yeah. So the the first the first best practice, and we learned this over time, is to avoid pretending that all of e-commerce is one big thing. If you look at it, there's marketplaces, there's direct to consumer, there's social commerce. More recently, we're talking a lot about the rise of agent e commerce. Those all generate very different signals, and they have very different levels of observability. They might have very different definitions of availability, fulfillment, etc. And if too earlier in your process you start to force that into an overly simplified model, you lose a lot of important context within the data. So the real work here starts up front. Uh it's it about it's in having a disciplined approach to normalization and figuring out kind of all the back-end plumbing to support all of that. So that means a lot of things. It means having a consistent product taxonomy and running classification models over that. It means entity resolution, product matching, uh, having attributes that are relevant for a given channel. You need your data model to preserve all that nuance where it matters, but also be smart enough to enable comparison and benchmarking in a simple way. The second element then is about fusing all those different data sources together. So no serious player in this space, because of some of what you just mentioned, no serious player is relying on a single source here, right? You need to combine observed data, retailer data, digital signals, consumer signals where they're relevant. And basically you gotta utilize some more modern kind of modeling methods and statistical approaches to close those coverage gaps. Those coverage gaps aren't going anywhere, right? And so we gotta we gotta use those techniques to close them. The third critical piece then on top of all of that is transparency. When you have that unified view of e-commerce, it's only useful if the user really understands what's measured through direct observation, uh, what's measured through a more modeled approach, and what that all actually means for how they think about the data, how they should interpret the data, and really what that means for the final recommendations, conclusions, and actions they're going to take based on the data. So from a product standpoint and and where I sit, that means we're focused on delivering a UX that's that offers far more connected data, uh, with more attributes and definitions aligned across all these data sets, and that enables basically stronger cross-channel repair than even within the e-commerce space and faster insight to performance. And that's what that's what unified should mean to me. Not removing all that nuance, but organizing all that complexity and offering it into an intuitive intuitive interface so that clients can actually use it to run it.

SPEAKER_05 28:59

Let me remind our audience that we're speaking with Kim Cox and Richard Pereira from Nielsen IQ measurement ecosystem. Kim, this one's for you. Retailers are going deep on first-party data and retail media and uh asking CPG brands to follow along.

SPEAKER_04 29:17

So, what should brands expect as these retailers integrate loyalty and sales data into the broader measurement ecosystem?

SPEAKER_00 29:25

We'd say that um it doesn't feel like it's a brand new phenomenon. The retailers have been asking the manufacturers for a handful of years now to go ahead and help invest in the retail media programs, get data in return, first-party data, data to help them understand which audiences are they reaching, is it working, is it not working? I think um what becomes a challenge for the manufacturers is that they all do it differently. And they have to figure out exactly where do they pull that budget from? Do they pull it from a marketing budget? Do they pull it from a trade budget? And so, and then, you know, does it create incrementality for them? So I think it's not an easy, um, an easy question for everyone to answer right now. And it feels like a natural evolution of trade and a natural evolution of marketing, but I do think it requires thoughtfulness from the organizations and probably really good cross-functional alignment across different BUs within a CPG because you can't just have your marketing team involved, just your sales team involved, just your shopper marketing, your trade development teams involved. You probably need to think of new ways of working to support the retailer, but also to make sure that you're not creating chaos within your own organization.

SPEAKER_02 30:38

So, Richard, looking out over the next two to three years, right? What specific capabilities, unified taxonomies, real-time signals, do you think are going to define the next chapter of measurement innovation? Because let's be honest, measurement of contribution is at the particularly transparent measurement is table stakes for these brand budgets that are looking at all these new marketing channels to invest against. So, what are what what is on your mind that you're going to be focusing on to infuse into the into the product roadmap around measurement?

SPEAKER_03 31:21

I think there are a few things, maybe three things that'll matter the most, right? And the first one isn't really glamorous at all, but it's about getting the underlying data structure correct, right? So products, attributes, KPIs defined consistently, across channels, data sources. Without that, nothing that you build on top of that is really comparable, right? And every AI insight that you generate then downstream, it ends up built on a bit of a rocky foundation. So you got to get the data structure right to start, right? The second, I think, is speed. And that's not speed just for the sake of being fast, but getting to insights in time to actually change a pricing decision, right? A media plan, address an out-of-stock, right, before the window of opportunity actually closes to do that. We really we work in a world where a perfect answer in nine days is a bit of a report card, a near-perfect answer in two days changes the decision. And third is, I think, uh this idea of stronger interpretation and context. So not only reporting a number that moved, but helping our clients understand, well, why did it move? And again, what to do about it next. That's where I think we're we're really heading.

SPEAKER_05 32:29

Well said indeed. And Kim, so for the brands listening who want to do exactly what Richard said, which is lead rather than get the report card nine days later, which is lag, what internal skill sets of data investments should they be prioritizing over the next three to five years? Like where should they be in the game?

SPEAKER_00 32:48

In terms of skills, I would say definitely agility. Everything's moving faster than ever before. Becoming comfortable with the uncomfortable, understanding how to use AI in whatever format and whatever platforms you want to use it to, but in order to make your life more efficient and more enjoyable. We've all found those wins where an AI prompt can help us get to a space that's incredibly enjoyable because it made a task that was otherwise so hard, so much more easy. I would say, in terms of investments, I have to go back to some of the data investments, of course, but making sure that you have the right content, whether it's through content on your website or content on your PDPs or content that's fueling your data lakes, because content is just gonna have such a strong role to play in making sure that you're findable within all of the different LLMs. I also like the idea of enriching your own first-party data. So manufacturers are sitting on these huge treasure chests of first-party data, but oftentimes you just get to see exactly what you have within your walls and not necessarily beyond that. You had talked before and asked me a question about investing in retail or first-party data, which I think is also important and valuable, but the ability to fuse the two together or even fuse them with data sets like we have. We also have large consumer data sets that are robust in nature and can all get fused together. I think that gives you a really good view of the world. And you can also use that for audience targeting and other purposes or consumer targeting through your CRM programs. You mentioned about um getting things, you know, nine days later. So we did recently launch an early market delivery, which we're really excited about. We have uh Jack O'Leary, who's our thought leader right now in this space, has been creating a lot of content and giving everybody a sneak peek into what they'll see seven days later using traditional plus nine latencies. But um, to give you a little bit of background on that, essentially what it is is it's just the point of sale data that you usually get on Sunday nights or Monday nights for your Monday morning reporting. It's instead delivered seven days earlier. So because of that, you get to move faster than your competitors. You get to adjust things that you might have otherwise waited another week to move on, whether it's you know, supply chain issues, pricing or promotion issues, or you know, just traditional uses that you would have for point of sale data a week later, but you can do it faster.

SPEAKER_05 35:20

Because we want to get that right. Does that mean it'll be available in a three-day lag?

SPEAKER_00 35:24

It's uh available on a two-day lag.

SPEAKER_05 35:27

Two-day lag. Like nine minus seven is two. Somebody has to teach mathematics. I want to go back to being comfortable with the uncomfortable because our industry has traditionally struggled with that. And a large part of the reason why it struggled with that is the nine-day lag. How do you both how do you both advocate for yourselves to get comfortable with the uncomfortable? What do you do? Like Peter and I have this platform called the C guys. Someone's always on the show. We're learning something new, we're learning where to focus because they come here and preach. So we have a natural advantage here. But how do you guys do that? Do you read articles? Like, how do you get comfortable with the uncomfortable?

SPEAKER_00 36:05

A couple of things that makes me feel more comfortable with the uncomfortable. One, asking a lot of questions, not being afraid to just look stupid for a minute, get the answer, and then you know it, moving on. So I think creating a network of people that you're uh able to ask any question to and then write it down so that you don't have to ask them again later. That's one of my tricks. And I would say just jump right in. You're never gonna be fully comfortable. If you wait too long, you're gonna end up in a place where you're overly comfortable and stagnant. Every job that I've had at Nielsen IQ, and I've been here for 18 years, has been one that somebody kind of pushed me into, including my current job. Someone said, Hey, I think you need to go do this thing over here and let's do it different than we've done it in the past. And it's what keeps me excited to come to work is doing things that are new and different and that I'm uncomfortable with.

SPEAKER_03 36:58

Yeah, I would say from a product development standpoint, I don't IQ, it's all about trial and error. Our clients are really good with giving us feedback on early prototypes, POCs, things that we're kind of thinking of but need a little bit of guidance on. We're never afraid to kind of take on a new challenge like that and produce an early view that we then share with clients to get some feedback and help us kind, help kind of guide us in the right direction. We're gonna bump into the walls a little bit along the way, but that's okay. That's uh that's kind of how we how we iterate on our products and get to something that's ultimately very useful for clients at the end of the day. So that's just kind of the general approach that we take. It's very iterative in nature.

SPEAKER_02 37:35

For what it's worth, my approach surround myself with people that are a lot smarter than me in areas that I don't have expertise, which is why I partner with this guy on the podcast.

SPEAKER_05 37:46

And we're doing that today with these two.

SPEAKER_02 37:49

Exactly. Exactly. I couldn't agree with that.

SPEAKER_00 37:51

How do you get comfortable with the uncomfortable?

SPEAKER_05 37:54

Like I said, we have this platform called the CPG guys where we're getting us for three or four guests every single week who are coming and teaching us something new every single week. So it's a little cheat code, then we know we got to go study up on a topic they usually drop to you on the CPG guys.

SPEAKER_02 38:10

Yep. That's how we that's how we keep on top of things, is we let other people tell us what they're thinking about and the stuff that really resonates with us. We just go and dig in a little deeper after the episode's over.

SPEAKER_00 38:22

Yeah, that's cool. And then you have this incredible network of people that as as you learn a little or you forget a little, you can always go back to them and ask more questions.

SPEAKER_02 38:30

It is great to have the uh the digital Rolodex uh that we've built up through this through this podcast.

SPEAKER_05 38:39

Or Peter, you can also go to Coachella with me next year and ask Trent Tresner like I did about how Nine Inch Nails was formed.

SPEAKER_02 38:46

Shree, is that a formal invitation to join you at Coachella? Am I getting invited to Coachella next year? Is that what you're telling me? Oh, that's see, I knew that. See, he dangles that in front of me and then he doesn't offer it. That's how this is.

SPEAKER_00 38:59

I assume Richard and I can come too.

SPEAKER_02 39:02

I know, trust me. I I can't I can't even get him to get a signed t-shirt from anyhow.

SPEAKER_00 39:08

Richard's in Chicago, so Lollapalooza is probably more interesting for you.

SPEAKER_02 39:11

So Sheree was there last year. That is true. That is true.

SPEAKER_05 39:20

It's a strong L.

SPEAKER_02 39:22

Richard, as the product leader for North America, would really appreciate you sharing about Nielsen IQ's vision for the future. And as you know, the powerful tools the Nielsen IQ offers are driven by very great partnerships with companies that have capabilities that enrich the ones that you bring to the table, plus the commitment to innovation. So, to that end, people that are listening to this podcast in the industry, what should they be paying attention to coming out of Nielsen in the near future?

SPEAKER_03 39:58

So, at a high level, our vision continues to be to provide clients with the most complete and clear understanding of consumer behavior. And what that really means in practice is that we're going to continue to do a lot of the things that we that we've been doing. So we're expanding coverage to address known blind spots in the market. We're improving how different data sets are connected to one another, and we're offering a much more cohesive analytics experience through our Discover platform, basically trying to get to a point where clients are spending less time reconciling the data and more time acting on the data. So, from an innovation standpoint, there are a few key themes to keep an eye on with all that. One is the continued fusion of measurement, the bringing together measurement, consumer behavior, digital signals into a more connected view of performance and commerce at large. Another that we've touched on is AI. Okay, so using AI and advanced modeling, not as a marketing story, but as an actual engine to address some of the basics, the foundational layer, classification, modeling methods, data validation. I think another major theme here is more decision-oriented products. And that means focusing not only on what changed, but also what drove it and where to focus next. So what matters to me is building products that are commercially relevant. We are well partnered across the industry with making to make that happen. Uh, and we we have to make sure that they're methodologically strong and actually useful for our clients in real-world scenarios.

SPEAKER_04 41:18

Let me uh wrap this up with both of you with a very simple question. And then I'm gonna ask you for some advice. If we brands and retailers want to future proof their measurement strategies running tomorrow, what that one piece of advice should be given.

SPEAKER_03 41:36

I'd say be careful not to organize your measurement strategy around your internal, internal org chart. We see that happen often. You really need to organize it around how consumer demand actually forms and how it moves across channels. Because consumers don't behave in silos and consumer demand doesn't really respect your reporting lines, right? People move across stores, across e-commerce, search, social, different loyalty programs. They behave much more fluidly than many legacy reporting systems were actually designed to handle. And so if your reporting is still designed around this very disparate channel reporting, can't bring things together, you're gonna be late in understanding what's actually happening. The other point is I make is to not treat product classification, data integration, and data quality as back-end functions. I've been doing that stuff for a long time now, but those have become differentiators. That's really what's determining how quickly you can detect a change and how confidently you can take action.

SPEAKER_00 42:33

That was such a great answer. I don't have a whole lot to build. I was gonna also say something along the lines of following the consumer wherever they go. If you're obsessed with the consumer and how they're shopping, then I think naturally everything else starts to fall into place. Um, and don't be afraid to use alternative data sources. Honestly, the way that the industry has evolved over the last 10 years to and the amount of data, really strong quality data that's available is really going to help customers eliminate blind spots and be able to get closer to their own consumers and their retail customers too.

SPEAKER_05 43:07

Let me remind our listeners you can find all of our content by going to a web browser and typing cpgguys.com as the URL. If you are someone you don't want something to contribute to this ongoing discussion on the CPG Guys, please do send us an email at contact at cpgguys.com to our audience. We want to thank you for the clicks, likes, comments, direct messages, meeting us at trade shows, coming to our events, recording as well with us and our sponsors. We are always grateful for you. The show doesn't exist without all of you. You work with us all year. We're grateful to have you as our audience and partners. Thank you, thank you, thank you. Peter, pleasure as always. Give me that big takeaway.

SPEAKER_02 43:42

I think Richard said it when he talked about the commitment to fusing data sources, the what, where, when of point of sale with the who and why of behavioral and attitudinal data to get a complete picture that uh to what Kim said is you know, following the consumer journey, and you have to take different data sets to do that. That that full view is what's going to give um give CPG marketers and analysts who are leveraging Nielsen IQ the advantage in going to market. That's my big takeaway.

SPEAKER_05 44:18

For me, somewhere hidden in this episode is the mention of a two-day lag of receiving market measurement. The industry really has to now understand that with the availability of two-day lag, why would you buy anything or why would you not focus on getting two-day lag and run run to other areas? You may talk about a one or two-point better quality somewhere else, but if you're getting none of these data sets need to be 100% accurate in the first place, other than during the annual bonus measurement time. Two-day lag data, I wish during my 30 years tenure in CPG I had access to that. I can't even tell you the things that would have done with that in terms of actionability in the marketplace. Uh nine day lag, what happens is often by the time you can take action in store, a promo might have already expired. But with two day lag, uh uh, you can act on the spot. Game changer, and I hope Nielsen IQ's communication with the industry has been that way, and that's how the industry is receiving it. Because if the industry is not, I'd love to ask people who come on the show from C. CPG and retail, why not? So, Richard and Kim, fantastic episode on measurement. I want to thank you both for joining us on a late Friday afternoon on the CPG Guys.

SPEAKER_00 45:32

Thanks for having us. Have a great weekend.

SPEAKER_05 45:35

That's a wrap of this episode of the CPG Guys.