Kim Cox (3:31)

I'm good, Sri. Good to see you again. And you just gained one more TikTok.

Sree Rajagopalan (3:36)

Follower so you can add that to your 60.001. How about that, huh? And don't forget Instagram 40,000 plus. So we're excited to have you on the podcast, Kim. We'll include the digital show, notes of this episode, links to your LinkedIn profile, and that @NielsenIQ. What I'm excited for is this is a hot topic on the CPG guys omnichannel coverage and you are the queen of it. So let's get straight to the point. Could you walk us through your framework of what is the Nielsen IQ full view measurement? What does it encompass and what, if anything, is still a work in progress?

Kim Cox (4:07)

Yeah, absolutely. So the full view measurement is our commitment to the industry to bring the broadest measurement universe available, but also the most granular. And as a result, if it's the broadest and the most granular, it also becomes the most actionable. We also know that consumers shop in very different ways than they have historically. 10 years ago, 20 years ago, 50 years ago. They're no longer just going into retail locations, but instead they're shopping in a truly omni commerce way. Everything from direct to consumer and online, grocery pickup, social commerce. And because of that, we can't rely only on retail point of sale data. Retail point of sale data is incredible, but there can be gaps in visibility and the consumer signals of buying behavior needed to evolve beyond just retail point of sale data. And so our methods needed to evolve to capture that evolving shopping behavior. So we believe that we are, you know, and we believe and we're now showing that where we have really high quality and granular item level, banner level, point of sale data, that it doesn't exist. That we have to start creating essentially synthetic point of sale data using alternative data sources to fill in some of the holes.

Sree Rajagopalan (5:19)

Yeah, there's no doubt about it, Kim, that if it's POS data only, all someone is working with and reacting to is the final purchase signal, but definitely not working with the buyer behavior, the consumption behavior that drove a certain purchase, or the influencer behavior that drove a certain purchase. So does the full view really take into account. We're really trying to give you a full view way above and beyond just the purchase signal at the end of the day. Is that what the word full view comes from?

Kim Cox (5:49)

Yeah, absolutely. So the full view is Nielsen's. It's the way that we describe all of the different buyer behavior and shopper behavior metrics that you can collect from us. Whether it's point of sale data, whether it's measurement in a broader sense, whether it's shopping behavior from our consumer panels, whether it's insights and analytics from various different ways to to understand consumers in different way, or another space that I'm really passionate about is digital shelf. So being able to understand what exactly the consumer is seeing on the digital shelf and how can that translate into additional data sources that then you can use that to better understand how can I be more visible and more available and more helpful to the consumer who's shopping for products online.

Sree Rajagopalan (6:37)

Awesome. So how has this vision of full fuel measurement evolved over the years? What makes Nielsen IQ's approach uniquely robust in today's omnichannel environment? Because there are others who also provide what they would call their version of a full view. Whatever the names are. I've largely found it's POS and it's very top level. It has excellent coverage, but it's very top level. So you can use that to report against what happened, but you can't really diagnose your business above and beyond that or run your business. So what differentiates Nielsen and how's it evolved over the years?

Kim Cox (7:09)

Yeah, we've been an investment on an investment journey for several years now, really trying to bring together the best consumer signals of buying behavior. And what we do is we pair all of that data of how consumers are shopping those demand signals with advanced data science techniques, AI driven coding, product coding, global technology platforms that have been dramatically enhanced over the last three to five years and 100 years of industry leading experience. To advance our full view measurement solutions, we've had great omnichannel solutions for several years now. But starting last year, we took our efforts even further and we wanted to go beyond just offering a broad universe, but really progressing the idea of creating synthetic POS or POS like data. Because we're used to having data that is item level and account level. You can see it within a retail banner, you can see it at an item level. But where that doesn't exist, we think that we can create it and we've shown that we can do that. So. So we've been on this journey for a while now and what we've done essentially with starting with Amazon, a strategic retailer like Amazon needs to be able to be analyzed at an account level. You need to understand data within Amazon for yourself, but also your categories and be able to compare that against any other retailer. And historically that hasn't been possible. There's been boutique firms that have provided views into Amazon category data, but then they don't have the retail point of sale data. Or there's other companies that might have Amazon inclusion, but you can't see it at an Amazon account level. But Amazon continues to grow about 20% year over year for CPG categories. And so for some categories like food, which is making a lot of waves right now, it's already at 35% unit growth versus prior year. So this is huge and it needs to be visible. So. So really what we've done is we coded millions of Amazon Asins to UPCs, so now it looks just like regular point of sale data. And we lined it all up against our Nielsen syndicated category definitions and then put it into the same data platforms as all of our retail point of sale data so that you can effectively analyze your whole Amazon business the same way you would be able to analyze any other reported retailer through positive. So.

Sree Rajagopalan (9:41)

So Kim, let's talk about that for one second. You're on the CPG guys. You're talking to nearly the entire CPG industry and all of retail in the seat that the CPG industry services. What would you want them to know? One in one statement. Tell me what differentiates Nielsen's Amazon offering on the full view versus everything else available. There's so like you said, there's a million million is an exaggeration, but maybe at least 20 boutique offerings. Then there's your competitors. What is that one statement? Why they should like bind to get the NIQ full view Amazon coverage.

Kim Cox (10:16)

Now, NIQ is the only place that each Monday morning when you log into your data sets that you can analyze your Amazon sales and share performance, pricing, promotion pricing, promotional performance, alongside any other retailer, Walmart, Target.

Sree Rajagopalan (10:32)

Wait, wait, wait, wait. Jim Way. So that means on Monday morning, when a key account manager walks in, Amazon, key account manager or any other business, because everyone's looking at competitive, no matter what customer they work on, retail customer, they work on all the metrics that traditionally have with their key account data. Let's say Snooks, Supermarkets, let's say Ahold, could be anybody, Giant Eagle. They can actually put up Amazon against that and they can actually compare against competition.

Kim Cox (11:01)

Yes, absolutely. Every Monday compared against competition level at an ASIN level. So upc ASIN level. So you'll be able to see you're.

Sree Rajagopalan (11:10)

The only one offering that in the market. Sorry, I don't mean to cut you off, but this is exciting.

Kim Cox (11:14)

The only one. Yeah, absolutely. Yeah. I think about you and your, you know, previous roles and how it would be helpful if you're the head of sales or if you're the head of insights, to not have to spend all this time trying to cobble together an Amazon view and then bring it together with your viewer.

Sree Rajagopalan (11:31)

I'll tell you where the Achilles hill was in my previous roles. Not just General Mills, but prior to as well. I'd be pretty frustrated with my account teams when I'd ask them, I want to start looking competitively, like the leading UPCs, the laggard UPCs, one market versus another market. And the answer again is, with Amazon, we get share data so we can get total US level share, which is great for Wall street reporting, but beyond that, twiddle my thumbs. You're saying you can solve that?

Kim Cox (12:01)

Absolutely. You can look at leading and lagging UPCs, and then for your competitors, you know, what was the price point that they were offering last week? On average, did they grow at 20% and you grew at 15%? What are the new items that launched on Amazon that aren't selling anywhere else in traditional bricks and mortar retail? At this point point, you can even look at things like nutritional trends because all the data is tied to a upc. There might be certain trends that are emerging on Amazon. High protein trends, low sugar trends, you know, any, any type of nutritional sustainability trends that are emerging on Amazon that haven't gotten picked up yet. In traditional grocery, for example, you'll be able to see all of that with the characteristic data that normally Nielsen shares for any retailer, but now we've added it for Amazon too. So it's really.

Sree Rajagopalan (12:53)

So you're saying within one platform you can actually diagnose and run your business versus just reporting out share to Wall Street. That's the major difference.

Kim Cox (13:02)

Exactly.

Sree Rajagopalan (13:02)

Yeah, I got you, I got you. What about Costco?

Kim Cox (13:05)

Yeah, the second. So we launched this Amazon REIT about a year ago and then maybe three, four months ago we launched Costco. Market was extremely excited about Costco. It is strategically important to retailers and manufacturers because it's growing about 5% a year for CPG on a MA massive base. But Costco has always had really big gaps in the data availability and visibility that they will share out freely with the marketplace. Oftentimes manufacturers that are selling in Costco can't see how their competitors are performing or how private label is performing. They have to cobble together what their competitor private label price points are. They don't have visibility into new launches that are happening within their categories. And so really what we wanted to do is bring that, that to light too. And we've also done that in the same way that we described for Amazon. Everything is released and updated on your Monday morning share reporting day. Everything is at an item level. We coded all of the Costco items to UPCs so that you can look at things like equivalized volume and compare that versus Sam's Club or versus Walmart or anywhere else to understand your, your business in Costco and your opportunity in Costco.

Sree Rajagopalan (14:25)

How awesome. So Amazon, Costco, y' all are muscled up. So let's jump into other pieces. I'm going to clearly say it's top tier coverage across online club, D2C Social Quick Commerce account level insights, which means again, I'll repeat it, you can run your business versus report against it. Can you highlight our Integrating the largest US club retailer strengthened the overall measurement ecosystem because for most, I would say mid tier and large CPG manufacturers, you know, a handful of SKUs represents close to 5 to 7% of their entire business. Just Costco alone.

Kim Cox (14:59)

Yeah, across Costco and Amazon. Together we offer now nine points of additional visible coverage across all of cpg. And I say it's visible because again, you can see it at an account level, at an item level. It's not masked in some huge number that you can't act on. Our clients don't want to cobble together data sets that they can't, you know, that they have to spend all of these resources on every week, every month. And so full view measurement helps them with that. And it's really important depending on your category too. So you mentioned that certain categories and certain brands really have a lot of business in Costco or A lot of business in Amazon. We're seeing that some categories have 30 to 40% of their sales in Costco and in Amazon. So imagine not being able to see all of that data in one view Monday morning when you start looking at your business.

Sree Rajagopalan (15:54)

Yeah, special specially native online businesses which are now scaled to in store a very large percent of the the first thing there are two retailers they go for first outside of Amazon. One is Costco, one is Target, they make an exclusive skewer two for Costco and then try to get everything they have on Amazon on Target and then they scale to the rest of the country with Walmart being the ideal case win situation for them. So Costco, Amazon, without that coverage you're pretty much doomed. So you've also emphasized deeper private label performance insights which is a big deal. You know I still remember that day, March 17th. I don't know how many times I've said it to you. March 17, 2023. Business completely changed. It was heydays since March 2020-23. Never had a bad week. It was grow 5%, 8%. 8% wasn't good enough. And then suddenly you saw negative. Largely driven by inflation and price. Private labels moment in the last two years private labels has really gotten some out, you know, unfair or let's, I shouldn't say unfair, but a very out outspoken share of growth than it traditionally have in that environment. You have also been emphasizing private label insights. How are manufacturing leveraging manufacturers leveraging that particular data to inform product strategy and positioning? What are you aware of?

Kim Cox (17:11)

Yeah, so we all know how powerful of a brand Kirkland is. I'm a fan of the brand, I think it's a great brand and it's continuing to grow across all of the categories really that it participates in. At Costco, what we can do is we can help manufacturers and retailers because it's not sourced from cooperative data. We can help retailers to understand the size of the Kirkland brand and Amazon's private label brands price points, which items are selling the best. We find that Costco now represents about 35% of or I'm sorry, Kirkland now represents about 35% of Costco's CPG sales and that increased two share points over the past year. So we're going to continue to watch that and take a look at how much Kirkland continues to steal share from the manufacturers. But if you're running a business and you're trying to gain distribution within Costco, first you want to understand how is your product going to be positioned relative to what's already on the shelf, whether it's national brands or whether it's private label brands. And I think having better data helps you do that. So of course your product benefits are going to help you do that. But also being able to understand growth rates and price points and, you know, promotional activity that's running across national and private label brands helps too. And then if you want to go in and tell a story about, you know, growing the category, not just taking share space or taking shelf space, palette space from national brands, I think you need to think about how are you going to position yourself alongside Kirkland's private label products, because that's not going to go away. Like they're going to continue to advance their private label initiatives. So you need to figure out, okay, what are the unique benefits that I offer compared to private label? And I think that this data can help with too. If Kirkland, for example, is selling four different flavors of sparkling water, you might be able to look at the sales for each of those four different versions of sparkling water and figure out, okay, well, maybe my product can be the fifth one. And here's why. Because I'm seeing these trends within the data that I can back up that recommendation with Baby care.

Sree Rajagopalan (19:18)

Is that one of the most profound private label items at Costco? Is that what the data say?

Kim Cox (19:23)

Yeah, it is. Good question. So baby care is about 48% share. Private label right now. Kirkland has a 48% share. Yeah, it's really big. There's some other ones left the category. I left the category.

Sree Rajagopalan (19:37)

No, I'm saying it's half the category.

Kim Cox (19:39)

Oh, it's half the category. Yeah, exactly. It is. I have little kids at home, so I have left the category. But they're 8 and 10 now, so that's what I thought you said. Yeah, it's half the category. And it continues to grow. But there's other ones. Household care is in the 40s as well. But then there's other categories like vitamins and supplements where it's in the teens, 13, 14%, something to that effect. But yeah, it's half the category. But we can also take a look at like your price gap compared to the private label brand and help you just kind of drill into really any categories. Baby care, hard seltzers, chicken, anything within the CPG space we have private label data on for Costco.

Sree Rajagopalan (20:20)

So let's, let's dive into that a little bit more. Again, just like I asked you about Amazon, what's the primary difference in the offering between a lot of Others in the marketplace and what Nielsen IQ has to offer. Is it the same? You can go deeper. You just talked about how you can analyze chicken as an example. And you can look at private label as well. You can look at SKU level as well, your own SKUs and you can look at private label SKUs. Are most of the other offerings not doing that? It's still again just a share play.

Kim Cox (20:50)

Absolutely. A shareplay. So I think there's two different ways that right now manufacturers can get access to data. The first would be through collaboration programs that you might be able to get a view of your performance relative to a high level, high level category total. It's very expensive from what I'm told and it is oftentimes has gaps. You can't see private label, you can't see the competitive set. All you know is your share relative to a very high total. So you might be interested in chicken and you might get, you know, an overall meat department view as your share base, which doesn't really help you. The other way that manufacturers and retailers look at Costco data would be through panel solutions. So panel solutions are great. They're intended to be a longitudinal view of how a consumer is shopping. We're not doing it that way. As a part of this measurement solution, we're taking literally all of the transactions we're seeing and that through, through consumer source methods. And we're using millions and millions of those receipts to project out to the totals there. So that allows us, because we have that massive scale of receipts in order to. It allows us with that massive scale of receipts to be able to look at data on an item level weekly basis because the scale is just so big.

Zamo Representative (22:18)

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Sree Rajagopalan (23:45)

Awesome. So pretty clear to audience. Let me remind our audience that I'm actually speaking to Kim Cox, who's the MD of the Omnichannel business at Nielsen iq, but also represents most importantly the Full View measurement, one of Nielsen's IQ's most important offerings. As we've been discussing thoroughly again and again, depth of coverage, what you can do with the coverage as opposed to just reporting top line share in the first place. So as we keep moving on here, Kim, with 91% of consumers now shopping both in store and online, what emerging behavioral trends should brands be paying attention to as they optimize omnichannel approaches?

Kim Cox (24:24)

I'm particularly intrigued to see what happens to Amazon's perishables business. So as consumers now are going to have more access to fresh products via Amazon, I think it's going to be really an interesting place that Amazon has a lot of room to grow. When we looked at Amazon's perishables business compared to the top seven leading retailers, we found some huge differences. And I think some of this is expectable. Most people aren't thinking about their Amazon purchase behavior and thinking like, oh, I'm going to add chicken, I'm going to add bananas. But when we compared the food department, we saw that food accounts for just 18% of Amazon's total sales sales today, compared to 35% for total US online sales. That includes online grocery pickup and it's 58% share for the top seven retailers. So Amazon has 18% of their sales coming from food. Top US retailers has 58% of their sales coming from food. So a huge, huge difference and a huge white space for Amazon to capture more share. And when you look at those top seven retailers meets the number one online super category because of the dollars that are spent against the meat department. That includes online grocery pickup there too. But it ranks 70 for Amazon. So I personally don't think that a lot of consumers are thinking about Amazon for their meat, their vegetables, their fruit purchases. I do live in Columbus, Ohio, which is one of the test markets. So as I make any Amazon purchase, I am reminded that I can also add some bananas or add, you know, some raspberries and strawberries to my order. But I think as this as Amazon tries to gain share here, I think it's going to be a little bit tricky. I think they have a little Bit of a ways to go still to convince consumers that they can deliver fresh products really safely. I think we're used to, at this point, the trend of, you know, Instacart or online grocery pickup. It's no longer a trend. It's more of a proven delivery or fulfillment model. So I think everyone understands, okay, you know, in Instacart, they go to a store, they. There's a shopper that goes to a store that pick up the groceries, they bring it home. That's just like how I would do it. It makes sense, but it feels a little bit black box that you can purchase something on Amazon and it's supposed to be your hair in two hours. Where is it coming from? Are there several other stops along the way? Is my fresh chicken really going to stay fresh? So I think, I think that's a very interesting emerging trend. I'm curious to see how it plays out and how Amazon can work to gain trust and start to develop some new buying habits from consumers.

Sree Rajagopalan (27:08)

If there's one thing that's clear, Kim, Amazon is a strength and a muscle for y' all from a coverage perspective and the data insights you can get out of what you. True or false?

Kim Cox (27:20)

True, I think. Definitely. We haven't even talked about our digital shelf capabilities, but yeah, we can help brands really win on Amazon and are happy to do it.

Sree Rajagopalan (27:29)

So digital shelf capabilities. Right, let's go right there. Since you bought it up. I'm sorry, Oops. Moment. Digital experiments. Digital engagement is no longer a complementary strategy. It's just essentially, it's just life at this point. It's just essential to growth. If you're not Omnichannel, you are the dinosaur that'll slow your brand or your retail environment down. And I know plenty of those dinosaurs, by the way. I engage with them on a daily basis. With growth in some categories slowing, what strategic pivots which CPG and retail leaders consider over the next few years. I mean, let's talk about your digital coverage at this point. Let's get into it.

Kim Cox (28:02)

Yeah, great question. So our. We have some unique strengths that we can help to help brands and retailers break out. How they're performing in total online, how they're performing in bricks and mortar, and then dig into all of those different growth spaces within online. And we continue to see places like TikTok come up to the top, especially in health and beauty, but in other places, too. So right now, TikTok Shop is the number eight health and beauty retailer across the US and number 43 for food. And so I do think that if you're looking for growth and thinking about how do we stay ahead of consumer trends and our competitors, really having a TikTok strategy and having visibility into what's working and what's not is so important. If you're not doing that, I think you're going to be left behind. It's a great opportunity for sales, but also an incredible engagement vehicle. A lot of the times when consumers see something on TikTok, they don't buy in the TikTok shop. They go to Walmart or they go to TikTok, they go to Target and other retailers to pick up those products. And so I think it, it truly emphasizes that idea of omni channel omnichannel marketing, which translates into omnichannel sales because of those different exposure vehicles on TikTok.

Sree Rajagopalan (29:20)

I'm actually an active TikTok shopper. I buy a lot of stuff on TikTok just as I do from other social platforms as well. It's a good learning. So you do. So as the MD and captain of this area, you know, Amazon and Costco, it's kind of very clear what you offer and why your offering kind of rises up to be superior in the industry because you can run your business. But all this social side, do you feel the same way? Is it work in progress? Much more to come. Where are you all on that cycle? Based on what you just said on.

Kim Cox (29:49)

Social commerce, I think we're going to continue to expand. So we've got a really good view into TikTok shop today and for sales. But most of those, most of that sales measurement is still more at a brand and a category level. It's not to the same degree that I just mentioned we have for Amazon and Costco. So as it continues to become important to our manufacturer base, I can imagine us like continuing to expand. How do we get more granular, get more visible, provide more transparency into social, including TikTok. Beyond that, we do also look at different social cues that are happening on the digital shelf. So in some markets and we have TikTok digital shelf data so you can start to TikTok shop digital shelf data so you can start to understand, you know, what selling price assortment. But also even for just traditional retail media, we also have ratings and reviews, which I know isn't entirely social, but you can still get a view of okay, within, you know, the reviews on Target.com, what is the total number of reviews for your competitor items? What's the sentiment and how does that translate into your. Your effectively, like how you're growing your business indeed.

Sree Rajagopalan (31:05)

You know, I still believe, just as word of word of mouth was so powerful for innovation in the past, ratings and reviews has become the tool of today. How many times in your own life, Kim, when you want to try a new innovation, what's the first thing you do? You whip out your phone and you're checking the ratings and reviews on multiple platforms to feel good about it or on the platform that you actually want to buy. So going beyond traditional pos, what next gen data sources or technologies is NIQ kind of exploring to expand omnichannel signal capture, especially in emerging channels like quick commerce, social commerce. I'm particularly intrigued if you guys are working with artificial intelligence as a tech, then of course clean rooms. And I'm not referring to the clean rooms that require Clorox bleaches.

Kim Cox (31:52)

Great question. So we're using everything from consumer sourcing millions of receipts to email mail scraping 24 hours a day at a store level, at a, you know, banner level, across a variety of different retailers. Web, we have clients that also are very committed to helping us. They we do shipment pooling with them. So really if there are ways to get good demand signals that help predict sales with high quality, we evaluate them and oftentimes we use them. You mentioned clean rooms. One of the great data assets that we have within our disposable is a 3 million person receipt panel. So it is tied to consumer email inboxes. All of those consumers give us the ability to scrape their inboxes to find receipts. We normally use those for measurement purposes, but we can also use them for consumer profiling and for clean room matching. So imagine you're a big retailer or a big manufacturer and you have a huge CRM program of your own or a loyalty card program of your own. But you only really know what's happening within your four walls or within your space of the consumers based on the, you know, with the signals that you get through our 3 million person panel, we can match it up with yours. And we're doing this with a variety of retailers and manufacturers today so that we can expand your view and now give you interesting informations around. Information around, like where else are they shopping? What else are they buying? Longitudinal analysis. How are they coming in and out of the category segment by heav Medium light. What other advertising or emails are they being exposed to through their inboxes? It's really, it opens up a wealth of analytical possibilities. Really interesting if you're in like a role that cares about consumer segmentation or activating against your CRM in particular.

Sree Rajagopalan (33:46)

You know, my mind just goes on a head spin when I think about the amount of data you'll have to work with, the amount of integrations you'll have to do, you know, reporting against one sku. I asked you a question earlier. Hey, you can actually report competitively Amazon against another key account, but the amount of back end stuff that has to go into doing that has got to be absolutely insane.

Kim Cox (34:07)

I'm so lucky to not have to manage any of that data on the back end. I'm more of a, you know, platform user, interface user and we have amazing product.

Sree Rajagopalan (34:18)

Let's talk about the platform and the user interface, etc. Right. I originally thought I'd ask you this question about what kind of metrics are available, but talk to us about the platform and the interface. How is it to use the user friendliness? Is it the same as everything else in Nielsen iq? What can one expect with the full view coverage?

Kim Cox (34:35)

It's so funny. So I've been at Nielsen Nielsen IQ for about 18 years now and there are some people that have been in the industry like you. You're an OG and you've been here for a long time. So you probably remember Nitro. Do you remember nitrogen?

Sree Rajagopalan (34:47)

Very well.

Kim Cox (34:47)

Yeah. So nitro looked a lot like. Looked a lot like Excel. It had a Blueberry. You could refresh things. There was really no visualizations. And then we moved to a different platform and now our platform is so advanced versus Nitro. We still have clients that want to do everything in Excel. So we have a Nitro like plugin. But the platform that we have now, we really moved all of our clients around the globe to this platform about two years ago. So now if you're a global manufacturer, you can look at your business globally within one platform. But it is highly visual and intuitive. Amazing visualizations. Everything from bubble charts, which are hard to create in Excel, to you know, your regular like trends graphs, anything that you can really imagine. It's really nice. And then one of our newest enhancements over the last year or so is our Ask Arthur functionality. So we have an AI essentially enabled interface that you can ask questions to ask Arthur. Arthur is a nod to our founder Art Nielsen 100 years ago. And Arthur will help you navigate through the various different data sets that you see on your screen. So because the platform is really easy to use and also integrates data sources, everything from your consumer panel data to your to your measurement data, you can bring it all together and then ask our AI agent to help you interpret those results and then create new results too.

Sree Rajagopalan (36:20)

So you mentioned AI and ask Arthur, is it already in the marketplace? Are clients already using it? What's the very early feedback? You know, AI is one of those things where everyone wants to talk about it, everyone wants it, but then you largely realize the real number one goal of AI is really ML, to harness a lot of data sets. And then there's the front end interfaces like ChatGPT. So is this like the ChatGPT of actually analyzing your POS data?

Kim Cox (36:48)

It is live and in the market probably. Has it launched maybe a year and a half ago, when we've been doing training against it ever since and continue to create new advancements. Every two weeks our Discover platform discovers what the platform's called, introduces new code and new features and enhancements. So we continue to make the AI capabilities even better. And then on the back end you mentioned, you know, it's really like AI is great for ML. We've been using AI and ML for, I would say, decades. This is not my area of expertise, but decades to make sure that we are coding new products as they launch very quickly and bringing them to market, placing items in the right spots on databases so clients can have the customization they need.

Sree Rajagopalan (37:35)

How awesome. So I wouldn't have expected anything less. And I wish you all much luck as you continue to develop the AI engine. You did mention that there are frequent code updates, etc. But it's great now because another challenge I faced at General Mills is being in the C suite as the CCO was. I had a lot of questions, but I had to go to levels, downs and teams to actually answer those questions. And one question was on another question spot, another question. Hopefully at some point through Ask Author, a senior leader can simply put a statement out there and get relevant information that they can actually work with them. So let's jump to the next one. How can Fullview, you know, along the lines of what I just said to you, how can Fullview and related tools empower sales teams to conduct causal analyses or shopper behavior on shopper behavior, like identifying why casual buyers aren't converting or where growth is stalling, who's new to that particular retailer or the brand, et cetera, at that retailer there?

Kim Cox (38:31)

Yeah, I think that's a really good question. So we, because we can bring together things like the shopper data and the measurement data, you can very easily in one platform, in one data flow, on one screen, help to understand, okay, sales are up or down, and then why are they up or down? Who are they up or down with? Is it my heavy households, my light households? Is it, you know, households over 50, et cetera. So I think we can really help, help diagnose very quickly within the platform. All of the data is very easily extractable, extracts into PowerPoints or is available in many different ways to bring it into client interfaces or do it on our side. But I think one of the more interesting examples that I saw recently was with combining some of the digital causal data with sales data. We were doing a project for a client recently and they were very interested in understanding their retail media spending and then the impact of the retail media spend on their sales. Everyone's interested in this, right? So what we were seeing is, is as a part of their share of voice, they were seeing as they were investing more and more in retail media, their share of voice is going up, some weeks it goes down. But when we were looking at their share of voice correlated alongside of their sales, there were such clear signs of hey, when your share of voice increases, your sales also increase. When your share of voice declines, your sales also decline. And then we could dig into. Here are the specific keywords that you either are sponsored on or not sponsored on and which ones you should be investing more in to drive sales. So I'd say that's one causal analysis that I'm really interested in is just share a voice and the impact on sales that we can help clients with. And I think again, we're really one of those few companies that can bring together really high quality sales data and digital causals like this.

Sree Rajagopalan (40:32)

One of the most important metrics for salespeople, it's a hidden metric actually that salespeople, even if there's business decline, as long as share is steady, salespeople can wink, wink, get away with it. But there's one metric that's absolutely unforgivable within the sales community and it's distribution. Talk to us about how focused you all are on distribution as a causal and whether within full view you can actually talk to distribution at the SKU level.

Kim Cox (40:59)

Yeah. So really good. We with both Amazon and Costco, we have distribution metrics that are included. They're both create like Amazon distributions a little bit more complex. But you can absolutely analyze your distribution, your pricing, your promotions. In Costco, the member coupons is a big driver of sales. And so you can analyze, okay, how are my price points different over time? Are those MVMs generating a lot of sales for me or not? So yes, we can help you with those causal analyses too so that you can build a better strategy for next month, next quarter, next year.

Sree Rajagopalan (41:37)

How awesome, Kim. So again, that's a hidden metric. Don't give away the plot. We're only talking about it in a podcast. So let's see if you can keep it a secret. So this last question I'm going to ask you is a little future forward. Where do you see the biggest opportunity for omnicommerce measurement? We should stop today just talking about brick and mortar anymore because everything is omnicommerce. I'm going to use that word purposefully. So what's the biggest opportunity for omnicommerce measurement to evolve over the next, say, year and a half, two years, 18, 24 months? How will it reshape strategic planning for brands and retailers and the industry? Really getting it based on your regular conversations?

Kim Cox (42:14)

Because everything is moving so fast at this point. Technology is moving fast, consumers are moving faster, trends are evolving faster. I think we're going to need to to see or we're going to see the continued need for fast integrated, high quality, granular data, integrated digital causals alongside of the rest of the causal universe that we've had for decades. I think that as companies are going to continue to focus on using AI, especially AI within their own four walls over the next three years, they're going to look for data sets that help help for a purpose. So having the right data sets to help them advance their RGM capabilities, their sales analytics capabilities, category management capabilities, of course, supply chain and other things as well. But I think like having that really robust, granular, high quality, fast to update data set without a lot of holes is going to really help them advance that AI journey that they're going to be on over the next three to five years.

Sree Rajagopalan (43:13)

Let's go on that AI journey as an industry. So what a terrific conversation. Let me now thank our audience for listening to this wonderful episode. Do leave us a rating and review on Apple Podcasts Spotify, a favorite listening platform as it informs us how we're doing as well as having the right conversations with the right folks like we did on measurement, which we haven't done really on the CPG guys, to all of you, thank you from Peter and me. You make the show happen to all the sponsors, whether this podcast, our parties, events, hosted dinners, having us the panels. Thank you, thank you, thank you Kim. Thank you for joining us on the CPG guys.

Kim Cox (43:46)

Thanks for having me. Glad to be here.

Sree Rajagopalan (43:49)

So as I wrap this up, we always wrap up the episode with the one big takeaway. This one is actually a very easy one for me. While we need to continuously keep emphasizing Omni Commerce measurement, the full view is what comes to the top of my head is the big takeaway. And the difference is with full view you can actually run your business business by measuring Understanding the casuals on a weekly basis at the UPC level is required on parts of the industry that most don't cover, which is Amazon and the Club channel AKA Costco, which happens to be large parts of someone's business versus Whereas just reporting Share that's a wrap of this episode of the CPG Guys. See you soon on the CPG Guys.

Kim Cox (44:37)

Foreign.

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