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

Summary

The CPG Guys – Total Market Measurement with NielsenIQ's Kim Cox & Richard Pereira (May 6, 2026)

Episode Overview

In this episode, hosts Sri Rajagopalan and Peter V.S. Bond dive into the evolving world of retail and CPG measurement with NielsenIQ’s Kim Cox (Managing Director, Omnichannel Intelligence Solutions) and Richard Pereira (North America Product Leader). As omnichannel consumer behavior rapidly evolves and data volumes explode, the panel explores how brands and retailers are moving beyond legacy ways of measuring success. The discussion focuses on advances in AI-powered analytics, closing data gaps across channels (with a special focus on the Club channel), and the path to truly unified, actionable, and timely market measurement—enabling CPG professionals to move from reaction to real-time agility.

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Key Discussion Points & Insights

The Changing Definition of Market Measurement

• Market Boundaries Are Shattering:
  Kim Cox addresses how the “market” today can no longer be defined by a single point of sale (POS) universe. Instead, omnichannel is the norm—encompassing DTC, marketplaces, and social commerce (e.g., TikTok).
• Brands Seek Incrementality, Not Just Share:
  With share growth critical in stagnant or declining categories, Cox explains that brands are “looking for incrementality because… it’s going to be how you grow. It’s not just about moving volume back and forth” ([10:27]).

AI and Practical Automation in Measurement

• AI Shifts Focus from ‘What Happened’ to ‘What To Do Next’:
  Richard Pereira details how AI and machine learning are making category management “less about asking what happened and more about understanding, well, why did it happen? What should we actually do next based on what happened?” ([11:22]).
• Integrated, Actionable Insights:
  AI is not hype but a practical engine to “shorten the path from data to action” ([12:40]), removing manual drudgery and surfacing guided, automated, and actionable analytics.

Capturing the Fluid Omnicommerce Journey

• Holistic Measurement Across Channels:
  Cox points out that NielsenIQ’s solution fuses omnichannel sales data with the industry’s largest consumer panel to provide insight “not only [on] your sales… going up or down, your share is going up or down—[but] what’s driving that? Which demographics? Is it penetration?” ([14:26]).
• Agility in Trend-Driven Commerce:
  Measurement models must accommodate ephemeral trends in quick commerce, DTC, TikTok Shop, and more.

Shedding Light on the Club Channel

• Why Club is Uniquely Challenging:
  Pereira: “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…” ([16:16]).
• Closing Club Data Gaps:
  NIQ’s solution delivers granular item/account-level visibility, including for exclusive and private label products, breaking the “false sense of certainty” that comes with incomplete data ([19:48]).

Total Market Measurement and Data Fusion

• How Close Are We to Total Visibility?
  Cox says, “We’re actually really close to a total market view,” thanks to fusing demand signals from POS, receipts, inbox/web scraping, and direct retailer data ([21:01]).
• Measuring Digital Influence and Incrementality:
  The panel references a Forrester study: By 2027, 70% of sales will be digitally influenced ([24:25]). Peter contends it’s even higher in practice.

Best Practices for Ecommerce Data Unification

• Three Core Pillars:
  1. Preserve Channel Nuance: Don’t flatten all ecommerce into one model—capture differences in marketplaces, DTC, social, etc.
  2. Data Fusion: Combine observed, retailer, and consumer data with advanced modeling to offset inevitable coverage gaps.
  3. Transparency: Users must know what’s measured vs. modeled to trust and act on the data ([26:28]).

Navigating Retailer First-Party Data & Retail Media

• Integration and Budgeting Complexities:
  Brands face disparate data-sharing approaches from retailers and must break down internal silos to make optimal use of loyalty, sales data, and media platforms ([29:32]).

Future-Focused Measurement Innovation

• Three Must-Haves for Tomorrow:
  1. Data structure—consistent taxonomies and KPIs across datasets
  2. Speed—“A near-perfect answer in two days changes the decision. A perfect answer in nine days is a report card.” ([31:28])
  3. Interpretation/context—Tools should explain not merely “what” changed, but “why” and “what to do about it”

Internal Capabilities for Leading Brands

• Agility & Comfort with Discomfort:
  Cox urges brand teams to “become comfortable with the uncomfortable…understanding how to use AI… to make your life more efficient.” ([32:54])
• Content & Data Fusion:
  Invest in rich product content and first-party data enrichment, as well as fusing with alternative and external datasets.

Culture of Continuous Learning

• Trial, Error, and Networking:
  Both guests emphasize learning through proactive questioning, experimentation, networking, and feedback.
  Cox: “Ask a lot of questions, not being afraid to just look stupid for a minute, get the answer and then you know it.” ([36:13])
  Pereira: “Our approach is very iterative in nature.” ([37:05])

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Notable Quotes & Memorable Moments

• On AI in Measurement:

  “The practical effect is really that AI is moving category management from a more manual interpretation towards really more automated insights and guided decision making.”
  — Richard Pereira ([11:22])

• On Omnichannel Measurement:

  “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.”
  — Kim Cox ([14:26])

• On Club Channel Complexity:

  “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…”
  — Richard Pereira ([16:16])

• On Digital’s Market Impact:

  “In 2025…about 60% of sales were digitally influenced, and by 2027, 70% of sales will be digitally influenced.”
  — Kim Cox ([24:25], referencing Forrester)

• On Agility and Timeliness:

  “A near-perfect answer in two days changes the decision. A perfect answer in nine days is a report card.”
  — Richard Pereira ([31:28])

• On Future-proofing Your Strategy:

  “Be careful not to organize your measurement strategy around your internal org chart… organize it around how consumer demand actually forms and how it moves across channels.”
  — Richard Pereira ([41:43])
  “If you’re obsessed with the consumer and how they’re shopping, then I think naturally everything else starts to fall into place.”
  — Kim Cox ([42:40])

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Timestamps for Key Segments

• Industry Overview, Guest Intros: [02:57]–[04:49]
• Defining Total Market Measurement (Kim): [07:56]–[09:56]
• Incrementality in Share Growth: [09:56]–[10:55]
• Impact of AI & Automation (Richard): [11:22]–[13:01]
• Adapting to Fluid Commerce Models (Kim): [13:59]–[15:43]
• Club Channel Data & Solutions (Richard): [16:16]–[18:02]; deep-dive [19:48]–[20:34]
• How Close Are We to “Total Market” Data? (Kim): [21:01]–[24:10]
• Digital Influence & Measurement Stats: [24:25]–[24:56]
• Ecommerce Data Unification (Richard): [26:28]–[29:06]
• Navigating First-Party Data & Media: [29:32]–[30:45]
• Innovating Measurement for the Future: [31:28]–[32:36]
• Brand Capabilities for Agility (Kim): [32:54]–[35:32]
• Building Comfort with Discomfort: [36:13]–[38:02]
• Vision for the Future (Richard): [40:06]–[41:26]
• Final Advice to Future-Proof Measurement: [41:43]–[43:15]

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Takeaways for CPG Professionals

• Obsess Over Consumer Behavior: Measurement strategies must match consumer fluidity across platforms and channels, not siloed org structures.
• Prioritize Speed & Interpretation: Timely, actionable data matters more than delayed perfection; context and “storytelling” from insight tools will be critical.
• Invest in AI & Data Fusion: Success hinges on embracing AI-powered decision-making and alternative data sources for a holistic, current view.
• Cultivate Agility, Curiosity, and Cross-Functional Collaboration: Brands must continuously learn, experiment, and integrate marketing, trade, and sales efforts to thrive.

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Hosts:
Sri Rajagopalan, Peter V.S. Bond
Guests:
Kim Cox (NielsenIQ), Richard Pereira (NielsenIQ)

For more episodes, visit cpgguys.com

Transcript

[A]

Hi, I'm Richard Pereira, North America Product leader for Nielsen iq.

[B]

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

[C]

Hello and welcome to the CPG Guys Podcast. Set at the intersection of commerce and tech. Your hosts, Sree Rajagopelan and Peter V. S Vaughn explore how brands and retailers engage consumers in a digitally driven world. And now, here are the CPG you guys.

[D]

Hello and welcome to this episode of the CPG Guys Podcast. I'm of course sri, your co host and also CRO and co founder of Think Blue Consulting, your trusted partner in their Omnichannel development journey. Get in touch with me at shinkblue Consulting co. Please do listen to my older daughter's [e-mail] and my younger daughter, Lara Raj of the band Gatsi. We just got done with Coachella 2026. We'll be headed to Lopalooza Chicago and to head to the UK as well as Korea. And we've got a whole fall tour coming up and then lots to announce with Riya as well. I'm joined today by none other than the Notorious B.I.G himself, Mr. PBSP, who also moonlights as head of industry and client engagement at Flywheel Commerce Acceleration Division of Omnicom. Peter, tell all about our visit to Yankee Stadium on None Other Than Jackie Robinson.

[C]

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

[D]

Awesome seats indeed. Watching Judd 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?

[C]

Well, anyone who's watching this on video can see that I am wearing my Dodgers shirt and my Brooklyn Dodgers 50th anniversary of Jackie Robinson Day hat. So, 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, we, we did a little damage to the corporate card street, wouldn't you say? Yeah, I think that was great.

[D]

Actually, let me remind you, this is not a baseball podcast, so I'm gonna.

[C]

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

[D]

we'll come back and ask for sure.

[C]

There we go.

[D]

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 580plus episodes we've already published with who's who in 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 omnichannel 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 for 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 Nielsen 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 Ferreira, Nielsen IQ's North America product leader, period. Richard is the one under the hood driving the innovation in 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.

[B]

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.

[A]

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

[C]

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 checking off. She's three down, two to go. And trust me, she's seen the jacket up close. Our dear friend Liz Buchanan has one of her own, having earned that outright. So it is very coveted piece of swag, to say the least. So good luck.

[D]

Richard got one from rbc.

[C]

He did. We gave it to him down at Cagney and he was the talk of the show.

[D]

Digital. 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. I was actually rooting for him and I couldn't believe they messed up the maintaining not once, but twice.

[C]

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

[D]

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

[C]

But anyway, Shohei Ohtani, greatest baseball player ever.

[D]

Niq's corporate website for listeners to access while we go on with our conversation. And now we're going to jump into the questions. But before we do that, I'll give Peter time to banter back. Go for it, Ben.

[C]

Listen, Shohei Ohtani, greatest baseball player ever. You will feel that this summer when I take you up to the hall of Fame and you see the stats there and you realize Shohei is gonna. They're gonna give a whole wing to Shohei when he retires.

[D]

10 years away from being a whole wing.

[C]

10 years is going to go to Shohei Ohtani. He is the greatest baseball player of all time.

[D]

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

[C]

Good luck, Shrey. Good luck.

[D]

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

[B]

So I live in Columbus, Ohio, so we don't really have a baseball team here. We have some minor league teams, but no professional. I lived in Cincinnati for a while and at that point 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. First dog, Marty Brent was named Brantley after Jeff Brantley. And then the second dog is Marty after Marty Brennaman. So I'd say the Reds.

[C]

Okay, good answer, good answer.

[D]

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

[B]

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

[D]

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

[B]

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 that mid and lower income consumer are really cutting back on food purchases to save money. So share is 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 continu 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, but if you do that you're going to have all these gaps. So we try and look at all of these additional demand signals coming from wherever we can get high quality data so 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.

[D]

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 share, 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?

[B]

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 going to bring on? What are they going to bring on? What are they going to take off? Because you're right, like they all need to look for incrementality because it just is the fat. It's going to be how you grow. It's not going to 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.

[C]

Richard, welcome to the show. We're really happy to have you here. AI and machine learning, those are big buzzwords this year, 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?

[A]

So the practical effect is really that AI is moving category management from a more manual interpretation towards 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, 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 in niq, we're not really chasing AI for, you know, 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 if it improves trust, speed, quality, coverage or the end user experience. If it doesn't do one of those things, it's just decoration.

[D]

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

[A]

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 of a button on the front end. And that's really the experience that we want to offer.

[D]

Does that mean logically it's a movement from dig and Discover.

[A]

It means that 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 to answer that question, piece together a whole story and narrative on your behalf and that's powerful.

[D]

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

[B]

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 omnichannel 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.

[C]

So Richard, I want to talk a little bit about the Club channel. Costco, Sam's, BJ's, wholesale. The growth that's going on there 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 IQ helping brands find the full view of performance in this channel?

[A]

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, typically a much smaller assortment. You can 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 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 false sense of certainty that you get from that can become very expensive very quickly. So our job at 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.

[C]

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[D]

Richard, you know, Peter and I here on the CPG guys have often said you guys have a superior solution to others in the marketplace because with the others you can report, but with the solution you bring, you can actually dig and you can get insights and you can go deeper into the data. Can you explain why that's the case?

[A]

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 they're perhaps exclusive in the club or they have a pack size that would otherwise expose them. 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 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, is a differentiator and we're hearing that directly from our clients in the space. They're getting a lot of utility out of a new, the new four new part solution.

[D]

Yeah, it's important that the industry understands why we say that. So you hear the term total market measurement quite a bit. You've got used to in public forums. In practice, how far away are we from truly achieving full visibility? Let me explain what that, what I mean by that. Consumer behavior directly to purchase and now the all important work.

[B]

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 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 brings to our market is a great way to bring a total view together. So as we launched our Costco launch, it 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 really strong about the incrementality. I'm going to maybe take it in a couple different ways. So you have talked about incrementality as, you know, incrementality adding another item. Does 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, 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 PDP is like 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 2025, about, or I'm sorry, 2021, about 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 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.

[D]

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?

[B]

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

[D]

Interesting. Peter, neat thoughts on that.

[C]

Yeah, I think we're a little more bullish and it really comes down to a matter of degree. They're probably saying that 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 going to stick with our 100% estimate. Sri, I think.

[D]

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 Luddites.

[C]

Yes, they are. That's okay. Let's bring people together. Let's not divide. But I absolutely agree with you and 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 he did a great job of articulating that. Richard, E commerce data is notoriously messy across marketplaces and particularly last mile delivery services. Right. 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 your clients?

[A]

Yeah, so 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 agentic commerce. Those all generate very different signals and they have very different levels of observability. They might have very different definitions of availability, fulfillment, et cetera. 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. It's in 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, 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 the space because of, you know, some 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 got to utilize some more modern kind of modeling methods and statistical approaches to close those coverage gaps. Those coverage gaps aren't going anywhere, right? So we got to 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, 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 where I sit, that means we're focused on delivering a UX that offers far more connected data with more attributes and definitions aligned across all these data sets and that enables basically stronger cross channel comparison 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 an intuitive interface so that clients can actually use it to run their businesses.

[D]

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 asking CPG brands to follow along. So what should brands expect as these retailers integrate loyalty and sales data into the broader measurement ecosystem?

[B]

We'd say that 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 reach. Is it working? Is it not working? I think 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, 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 views within a cpg. Because you can't just have your marketing team involved, just your sales team involved, just your, you know, 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.

[C]

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 is on your mind that you're going to be focusing on to infuse into the product roadmap around measurement.

[A]

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 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.

[D]

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 or data investments should they be prioritizing over the next three to five years? Like where should they be in the

[B]

game 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 going to have such a strong role to play on, 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, 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, you know, consumer targeting through your CRM programs. You mentioned about getting things, you know, nine days later. So we did recently launch an early market delivery which we're really excited about. We have 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 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 because

[D]

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

[B]

It's available on a two day lag.

[D]

Two day lag. Nine minus seven is two. Somebody has to teach three 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 advocate for yourselves to get comfortable with the uncomfortable? What do you do? Like, Peter and I have this platform called the C. You guys, someone's always on the show. We're learning something new. We are 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?

[B]

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 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 going to be fully comfortable if you wait too long. You're going to 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. What keeps me excited to come to work is doing things that are new and different that I'm uncomfortable with.

[A]

Yeah. I would say from a product development standpoint, at an 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. I 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, you know, share with clients to get some feedback and help us help kind of guide us in the right direction. We're going to bump into the walls a little bit along the way, but that's okay. That's. 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.

[C]

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.

[D]

And we're doing that today with these two.

[C]

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

[B]

How do you get comfortable with the uncomfortable.

[D]

Like I said, we have this platform called the CPG guys. We're getting three or four guests every single week or coming and teaching us something new every single week. So it's a little cheat code. Then we know we gotta go study up on a topic they usually dropped here on the CPG guys.

[C]

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.

[B]

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.

[C]

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

[D]

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 fine.

[C]

Sri. 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 to get artist passes? Oh, that. See, I knew that. See, he dangles that in front of me, and then he doesn't offer it.

[B]

That's how I assume Richard and I can come too.

[C]

I know. Trust me. I can't even get him to get a signed T shirt from anyhow.

[B]

All right, Chicago. So Lollapalooza is probably more interesting for you.

[C]

So Sheree was there last year. He loved it.

[D]

His daughter has one of the only four signed copies by all members of Katseye.

[C]

That is true. That is true.

[D]

It's a strong album.

[C]

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 that Nilsen 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?

[A]

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'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. So 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 to make that happen and we have to make sure that they're methodologically strong and actually useful for our clients in real world scenarios.

[D]

Let me wrap this up with both of you with a very simple question and that is I'm going to ask you for some advice if CPG brands and retailers want to to future proof their measurement strategy starting tomorrow, what that one piece of advice would give them.

[A]

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 going to be late in understanding what's actually happening. The other point I make is to not treat product classification, data integration and data quality as backend 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.

[B]

That was such a great answer. I don't have a whole lot to build. I was going to 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. 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.

[D]

Let me remind our listeners, you can find all of our content by going to a web Browser and typing cpguys.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 [e-mail] to our audience. We want to thank you for the clicks, likes, comments, direct messages, meeting us at trade shows, coming to our event, 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.

[A]

Thank you.

[D]

Thank you Peter. Pleasure as always. Give me that big takeaway.

[C]

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 to what Kim said is, you know, following the consumer journey and you have to take different data sets to do that. That full view is what's going to give is going to give CPT marketers and analysts who are leveraging Nielsen IQ the advantage of in going to market. That's my big takeaway.

[D]

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 a hundred percent accurate in the first place other than during the annual bonus measurement time two day lag data. I wish during my third year tenure in CPG I had access to that. I can't even tell you the things that I've done with that in terms of actionability in the marketplace. 9 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 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 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. The CPG Guys.

[B]

Thanks for having us. Have a great weekend.

[D]

And that's a wrap of this episode of the CPG Guys.

[C]

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