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Measurement and ROI in Commerce Media | Behind the Numbers Special Edition

2025/5/22
logo of podcast Behind the Numbers: an EMARKETER Podcast

Behind the Numbers: an EMARKETER Podcast

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Christine Grimere
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Michael Campy
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Mike Glasser
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Christine Grimere: 我认为零售商转型为技术公司是行业成熟的必经之路,而缺乏标准是这一过程中的挑战。通过建立数据架构标准,我们可以提高数据共享的安全性,简化资金流动,从而促进整个行业的发展。 Mike Glasser: 作为品牌方,我认为标准化至关重要。它不仅能帮助我们覆盖更广泛的消费者,还能让我们更快地应用经验,提升效率。我很高兴看到 IAB 和 MRC 在认证方面所做的工作,以及我们与媒体网络伙伴之间更开放的对话。 Michael Campy: 对于像我们这样的小公司来说,标准化非常重要,但也很困难。零售媒体网络的归因方式各不相同,这使得我们很难做出决策。如果能简化数据分析,更高效地部署资源,标准化对我们来说将非常有益。

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Welcome to a special edition episode of the eMarketer podcast Behind the Numbers. I'm Marcus and today we have another special episode from the eMarketer Summit, Commerce Media Trends 2025 held at the start of May. We have for you a panel discussion that examines sophisticated approaches to measuring commerce media success, maximizing return on investment. Our experts discuss attribution approaches, cross-channel measurement strategies and KPI selection for optimal performance tracking. We

eMarketer's Principal Analyst, Sky Canavis, hosts Christine Grameer, Vice President of Global Measurement Products at LiveRamp, and Mike Glasser, Vice President of Commerce Media at PepsiCo, and Michael Campy, Senior Vice President, Marketing for Maeve. Enjoy the panel. For those of you who are just joining us now, welcome. I'm Sky Canavis, and I'm a Principal Analyst here at eMarketer.

I'll be moderating this session made possible by LiveRamp on measurement and ROI in commerce media. It's one of the most complex problems facing advertisers today, so I'm very glad to be joined by an expert panel of speakers who have deep experience and will be sharing some terrific insights. So before we begin, let's do a round of introductions. Can each of you tell me who you are, what you do, and where you're joining us from?

- Hi there, I am Christine Grimere. I lead the insights pillar at the LiveRamp product team. We have the pleasure of working with most of the media networks out there across all the different ways that they might be working. So I'm really excited to dig in today and I am joining you from the beautiful city of Los Angeles. - Hey Sky, thanks for having me. My name is Michael Campy. I'm calling in from Austin, Texas where it's already summer.

and excited to be with you guys. So I lead the marketing team at Maeve. Maeve is for dog lovers out there, it's the best possible food you can give your dog. We're a digitally native company, so we sell primarily online. We make human grade raw dog food, treats, supplements,

And seriously, if you have a dog, check it out. It is the best. I've been in the CPG industry for about 20 years. The first 10, I was in what I call big CPG. I was in market research and brand management. And then about 10 years ago,

I made the switch over to growth stage companies where I'm really excited by the opportunities that growth stage companies have in partnering with founders and trying to create insurgent brands and take advantage of some of these things we'll talk about today in terms of measurement. So yeah, happy to be here.

Hi, Scott. Hi, everyone. My name is Mike Glasser. I lead the commerce media team at PepsiCo. Our teams are responsible for end to end strategy planning and execution of media in support of the full beverages and foods portfolio wherever and however our consumer prefers to shop. So that could be grocery or e-grocery, convenience, aggregators.

direct commerce. We do that in partnership with our retailers, their media networks, as well as some great media and technology partners out in the industry. And I am joining here today from New York where it's not quite yet summer, Michael, but we are holding out and excited.

I'm with you, Michael, here in Austin, and it's great to have you all. So now let's dive in. And I want to start with one of the foundational issues, and that's that as retail media has grown, the landscape has become increasingly complex and fragmented, and comparisons are hard when standards vary across channels and platforms. According to a survey research from the Association of National Advertisers,

More than half of retail media advertisers identified the lack of standardization as their biggest retail media related challenge. So I'll start with you, Christine, since you have like that big picture view of what truly needs to be standardized and what are some of the biggest obstacles you're seeing today and where's progress coming from in this area?

Okay, well, I'm excited to kick off with a big challenging question. Really, I think that when we look at this ecosystem, we see companies who are not technology companies necessarily having to dive in and become technology companies, measurement companies, advertising companies, all of the sudden. And so really, the lack of standards we see as part of the maturing process of this industry.

And so when we took a good look at the challenges that we're facing, suppliers in these retailers and the retailers themselves, we identified a place that we could really help was in what we would consider the architecture. So the architecture of how data is being shared across companies, how measurement is being executed, how publishers, retailers, and suppliers are all working together.

So we do think it's solvable, Sky, to address that part of your question. And we really see that by creating some standards around the architecture, it helps legal feel more comfortable with how data is maybe moving between companies. Legal and compliance, it also creates the money flow

in a more streamlined way. So a lot of these budgets are coming from different places inside of retailers or inside of suppliers. And so by creating an architecture in a way of thinking about it for everybody, for how money and data flows, we've really seen a lot more commonality start to grease the wheels and help data move between companies.

We actually built a steering committee of publishers, retailers, and suppliers to help this over the last six months. And really it's to compliment many of the other things going on out there. And we've run a lot of pilots to show everybody how easy it can be. So that's how we're investing time and energy. We are supporting lots of different types of measurements specifically, but we see the architecture as the place that really we could help everybody move the quickest first.

- Hey, Christine, I'll build on that, maybe offer sort of the brand perspective. We're navigating broad portfolios across a whole different number of retail partners. Again, we kind of want to be wherever our consumer prefers to shop. So standardization for us is critical, right? Standard ways to build audiences, to bid and buy on media, to target, and certainly from a measurement perspective. I think the sooner and the more progress we can make there,

A, the more ground we can cover, we can reach our consumers in more places and engage them. But B, it allows us to adopt learnings and apply them to different parts of the industry. And so I think where, Sky, you asked about where progress is being made. Christine, you have a great example on sort of data infrastructure and frameworks there. I think the work that the IAB and MRC are doing around accreditation is really good. And we're generally excited about that movement.

And even outside of that, just the more open and honest and transparent conversations we're starting to have with our media network partners about measurement methodologies and attribution, what brands and SKUs get credit. I think that's how we make progress to this space where it becomes easier and more efficient to be doing media planning buying here.

Michael, anything to add on that front and what you're seeing or interested in? No, that's great advice. I think that I'm coming from a company where we have about 20 people. We have to make really difficult decisions around where we're putting time, money, resources, effort.

And when it comes to standardization, it is really difficult for an earlier stage operator because a lot of times retail media networks, they may have their, you know, a very specific attribution window like Mike touched on, like how do they actually attribute data?

sales to certain products. So then there's nuances to each and it can become overwhelming for a small team to feel like you have to become an expert of all these different methodologies or attribution or metrics. And so standardization would, for us, would be

that we get to a point where we can more quickly make decisions. The data analysis is much more simple for us. Ultimately, at the end of the day, we can just deploy resources much more efficiently. And as we've been talking about today, there's been this huge proliferation of retail media networks, just dozens of them. And with this long tail of retail media networks now competing for the attention of brands,

I want to ask, what are some of the attributes or features that a retail media network can offer that would make it attractive to you and more compelling for you to spend your ad dollars? Maybe, Mike, I'll start with you since you work with a lot of retail media networks. And then, Michael, you can jump in because you work with one and what you would be looking for to grow your presence on retail media.

Yeah, thanks Guy. And I think this flows nicely from the standardization question, because I do think that's a big part of what we look for is a good understanding. Is this a common way to build audiences? Think audience targeting and display or even search bidding and buying models. Think second price auction for search.

And so that gets us part of the way there. But from where I sit, where we generally are very pro retail media networks, again, we want to invest where we see our consumers shopping. For me, we're managing a portfolio of thousands of SKUs, dozens of brands, thousands of SKUs. And our team is largely hands-on keyboard. And so any day there are millions of decisions that could be made. Obviously no human or a team of humans could do that. And so we do lean on automation capabilities.

And we're fortunate at PepsiCo to have an in-house product and engineering and data science team that builds out capabilities. We also partner externally with some of the best technology platforms that allow us to operate very, very complex scale marketing campaigns.

And so I see them almost as two sides of the same coin sky. You've got standardization allows us to operate sort of at scale and speed and understand what the opportunity is. And then automation allows us to make decisions to really deploy our resources in the most efficient and effective way.

Yeah, that's great. I think, you know, if I could call the person in charge of the retail media network we partner with, I think the things that are most important to me at the end of the day is just, I mean, the highest level thing is simplicity and predictability. So when, you know, when we're investing in a retail media network, we're doing it because we want to drive trial, get our product, you know, in more households.

And sometimes the link between the advertising on the retail media network, as it then shows to like scan throughs at a checkout, they don't they don't always sync correctly. And so there's a level of understanding predictability. So like if I put in X amount of dollars, how much sales am I going to get out?

And that simplicity of then taking the data extraction from that, we use a lot of the native tools within retail media networks for reporting, dashboarding,

And sometimes retail media networks make it kind of complicated to pull data out in a way to manipulate. And so some of the ones that I've worked with in the past that are most useful to us is just when we can take that data and put it into the way, you know, our system and the way that we're looking at the data to do analysis. And the last thing, which I think a lot of them seem to be lacking this, is that, you

There there's really a lack of ability to test and iterate within a campaign and do these like small tests in a structured way where you have a control on a test and you can a be test to treatments across both maybe you're testing different ad creative maybe you're testing different bidding strategies a lot of them really lack that so if you want to test something you're kind of exposing your whole business to the test and

And that's risky for smaller businesses like my company. And then I think apart from the retail media networks, the theme of this year's summit is commerce media, because that's what we're talking a lot about today. We've seen the rapid rise of commerce media networks that are non-retailers, the financial services, travel and hospitality players, transportation and delivery intermediaries, and

What would you say is the value that they would offer your brands that's distinct from what retailers have on offer today? Michael or Mike, let's start with you. Yeah, I'll jump in. It's a space we're really excited about. I think clearly, whether it was COVID kind of accelerated the behavior, we see the rise of what we'll call aggregators. So the DoorDash's, Uber Eats and the Instacarts of the world. Again, I think this is the consumer voting with

his or her wallet on where they prefer to shop and those platforms are growing and because they're growing we want to make sure we meet our consumers there so they're an important part of our uh marketing approach and our media investment and i think will continue to be i think the financial services part of its guy is really interesting truthfully it's not an area we've gotten into as much but i think what intrigues me about that is we're often looking at a narrower

opportunity to engage with these consumers, obviously that the Chase Media Networks or the PayPal ads are seeing a much broader journey before shopping and after shopping that could truly help you understand what does a consumer want or need. And so I think it'll be interesting as that opportunity grows and we find ways to bring more engaging and more relevant advertising to our shoppers, that becomes an interesting opportunity for us.

I think this movement of really, I've been in the industry for 20 years and data quality is a foundational issue that we've all struggled with for a very long time. And digital advertising brought this amazing opportunity to have, you know, target consumers in a one-to-one kind of approach. But then it got really messy with like all of these different kinds of data approaches, whether it was cookie-based targeting or tracking people when they didn't know it.

What I find absolutely just motivating about this era is this data from each of these different data owners is authenticated, it's consented, they're exchanging the value with the consumer on the other end, getting the agreement, and then they're really making advertising better for the consumer in the end.

Mike's examples he just used, Uber, JPMC, United, really delivering better experiences with advertising, with high quality data. And then the measurement, Michael, I promise you, we can get you good incrementality tests. I'm not sure who's not getting them for you, but

But good incrementality tests built right into that structure. Transparency is there, the data is there. It's just a really exciting time to be in this industry. I think we all kind of shuddered at the thought of cookies going away and privacy really impacting our industry in a negative way, you know, five years ago. But I really think it's actually created a much brighter day of better data for all of us to be using and more transparency across the board.

And I think now adding to the complexity is that some of the biggest growth opportunities for commerce media networks are those offsite and upper funnel opportunities as we move more into social and streaming and in-store. And then measuring campaign success looks different from lower in the funnel where you'd have a different focus, for example, on conversion-based metrics.

So I want to ask how some of the metrics you use to evaluate campaign performance vary across these channels, the ones that are more geared towards awareness or consideration. Yeah, I can jump in on that. Perfect. Yeah, we're kind of in the thick of this now. We may have launched on Chewy in January and Chewy is developing their advertising solutions for vendors and

There's on-site advertising, which is really similar to what you'd expect on Amazon with sponsored search, sponsored brands. We were bidding on keywords. But for us to, as a smaller brand, how can we use Chewy to help build awareness of the brand? And so we do utilize their off-site advertising capabilities. It's primarily through Meta.

And we think about the way we measure different steps of this campaign as we're trying to build awareness of the brand. So therefore, what's the right metric? It's probably not the cost per new subscriber on Chewy. We're looking a lot more at the cost per click metrics, engagement metrics around the ads. And then we're using Chewy's, their zero P data to target against people

people who we think would be open to Maeve mid funnel, that's where we start to look more at cost per order information, new to brand buyer information. So what was the cost to actually get someone who buys other better for your dog products to purchase Maeve? And how does that compare to other places we advertise to understand, is this a place that we can continue to use to grow

awareness of the brand, even beyond just purchasing on Chewy as a whole, but just awareness of the brand. And then on the bottom funnel tactics, it's really simple. It is, you know, this is someone who's considered and shopped the brand on Chewy. What is the cost to convert that customer?

Michael, I can build and maybe give the larger CPG, you know, sort of multi-brand perspective. Sky, the first way I think about it is sort of the measurement

KPI really has to be aligned to the brief. And so whatever the program is, if it's onsite, offsite, we'll bring in our measurement science team. We're making sure that brief is very clear and the KPI is aligned back to the brief. If it's a more of a brand awareness and equity campaign, inclusive of retail media, we'll look at reach and resonance and short-term ROI as measured by our internal MMM models.

If it's more sales driven, then we probably like many, many CPGs are pushing hard to get to an incrementality understanding and from incremental ROAS to get to understanding how lifetime value changes over time, right? Are we bringing people into the portfolio or are they wanting to come back and everything? And so Michael, the reason why I add that is I think in your D2C world, we're taking inspiration by a lot of the way classic D2C brands operate.

looking at cost of acquisition and lifetime value and saying, how can we replicate some of that in the retail media world when admittedly we might not have all the same data sets, but I think importantly with certain partners, with certain clean room solutions, right? We are getting there. We can start to build that understanding of understanding if they're a new shopper in our portfolio, are they coming back? Are they buying more of the brand? And I think that's where some of the really exciting work is happening right now.

And in this space, what's the state of collaboration now to support measurement or how do you see that evolving? Christine, what's your take? I think a perfect setup from those examples Michael and Mike just used in the last question

We see publishers, suppliers, and retailers coming together in really, really collaborative ways. We offer a clean room architecture that makes it easy for them all to come together in a very neutral way. A really simple application that hits on this is there's a public case study that's widely available, the Albertsons Media Collective, along with Pinterest.

for Mondelez, the brand you all probably know, Triscuit Crackers. And so think about this as off-site advertising. So Albertsons took their really rich data about people who've bought crackers in the category and then specific to the brand. They created a set of audiences that were exactly aligned to a Triscuit program. That program was all about recipes. And

And really that program, they were able to measure a direct sales increase together where Pinterest allowed the ad exposure data shared into a clean room. Albertsons allowed the audience data and the conversion events allowed into the clean room. And they were able to measure that sales lift with an incrementality structure, as well as look at some of those longer term lifetime value metrics because we were able to hold the data in the clean room architecture. So these are

these processes are becoming more and more standardized, more and more regular. They don't just have to be a special case study. They're really starting to happen 365 days a year. And that's like the right now, I think what's maturing. One of the things I'm really excited about on the horizon

is really this concept of retailers sharing their conversion data, their sales data, and allowing the suppliers to measure full funnel their brand marketing. So maybe what they spend on meta, what they spend on their programmatic, and really understanding how all

of that different upper funnel brand spend along with the retail media networks brand spend then drive sales for that brand in that retailer. So really excited about where we are now and getting the wheels greased, but as well looking at what's around the corner, the safety of the clean room architecture and the transparency is really allowing people to do things I never really thought I would see in my career to be transparent. Hey,

Hey, Christine, I'll build on that just from the brand perspective. I think we're equally excited. For a long period, what we'd often find ourselves in is a situation, you know, we build our MMM models in-house. It is very much the yardstick against which all of our brand media and retail media gets evaluated. It's incredibly important. But we also know that our retail media partners are building their own in-house measurement solution. And at times we'll come to the room with our best data and our best

you know, marketing science folks, and it might tell two different stories. And to a degree, each of us is grading our own homework. And so I think what you're articulating, Christine, is perhaps that sort of third solution in a more neutral space.

Where if we all provision our data and look objectively, we can get to maybe a more true or more accurate understanding of what's happening. Again, with the spirit of we have the same goal. We want to improve the shopping experience. We want to grow the business in the most sort of efficient way. And I think what you're articulating, Christine, is A, where we're going as an industry, but B, allows us to start to answer those questions. 100%.

And in terms of looking ahead or what we're seeing so far with AI, what are some of the top use cases you're seeing there to support or enhance measurement capabilities? Who wants to jump on that one? I'll go first. I'll go first. So two places that we are really excited about AI helping brands who are really suppliers and retailers who've brought their data together. One is particularly for smaller companies like Michael talked about, the big

mid to long tail suppliers, they don't have time to be in there spending a bunch of time. They just need it to work. So two of the ways we've really seen that help, one is data normalization, data categorization. Nobody wants to mess around with a different taxonomy from Pinterest than from Meta than from you name it. So normalization and just the data cleaning and data organization is a big spot that we've already made investments and seen it really help.

And then two is a fun one just beginning to happen around signals for optimization. So if you can really create a good measurement architecture, you can then use the AI to then identify which people you might want to target on Pinterest versus meta versus...

I keep using those examples, Amazon, Google, all of the different publishers that are out there. So signals for optimization is the other spot we really see AI starting to make some great impacts. Yeah, I would say we're not cutting edge on AI. There's too many other things we're trying to be cutting edge on. And when it comes to integrating AI, I think it goes back to what I said earlier, which is we use AI.

AI-enabled tools mostly because it's just a faster speed to insights. I think Christine gave a great example about how you can categorize information faster. And we work with a couple measurement partners that they use AI as a way to just help us get to faster data analysis, synthesis, and then we can make decisions faster. And that's primarily in our mixed modeling and coming from

Mix modeling 10 years ago, where you're looking at like the past six months of spend and there's a lot of channels that it doesn't always get a good read on. The speed iteration we can get now through AI allows us to get model updates a lot more frequently. We can make business decisions faster. We're talking about like spend optimizations a week out now versus spend optimizations that may not be impacted for the next three to four months.

I'll give just quick, just to round it out. I think Christine, like you said, we're using it to

you know, comb through myriad data to try and find, you know, patterns and insights that allow us to take what's working and apply it across the business. And then similarly, we're finding a lot of great use cases when it comes to, you know, budget forecasting, bid strategies, all that kind of good stuff. So just two very top level ones, there's probably a ton more, but obviously an area that we're investing in, excited about and, you know, leaning hard on.

So we have time for one more question. And I think I'd be remiss not to talk a little about or ask about the largest player in retail media space, which is Amazon, which commands the lion's share of US retail media spending around 75%. And that's not something that we see changing much in the near future, according to our forecasts. So Mike and Michael, I wanted to ask a bit about your experience with Amazon and how some of the advantages of working with

the platform outweigh the drawbacks? Yeah, maybe I'll start and then Michael pass to you. I mean, Amazon is a phenomenal partner of ours. It's an important part of our business. Again, it's where the consumer is shopping. So we want to make sure we're there.

I think if I take a step back and I just look at the broader retail media space, I think Amazon is very much sort of innovating and setting a lot of the pace for this industry. And that's exciting. It's important for us to watch and understand. So not only do they have a massive audience that we can go reach and engage,

but they have all sorts of formats on-site, off-site. They've got devices in your living room. They've got great content opportunities. And then I think perhaps most relevant, if not important for this conversation is when you look at the power of Amazon Marketing Cloud and how we can leverage that tool to bring it all together, our brand media investment, our commerce media investment, understand how is the consumer shopping? How is she engaging with our products? And how can we better deploy our resources? That is the opportunity. And so I would say,

probably, Sky, the pros far outweigh any cons if there are. And I think we often look to Amazon and our strategies on Amazon to say, where do we anticipate parts of the retail media industry to go and how can we prepare for that?

Yeah, I don't have too much to add. I think the one thing to call out is that, you know, like what Mike said, like where the consumer shops is where we want to make sure that we are. And it's clear with Amazon scale, that's where consumers are shopping. I guess the drawbacks from earlier stage company is that

There's less of a browsing behavior on Amazon and people tend to look for very specific things on Amazon. So for a brand that's in the raw dog food space, you know, we, in order for us to break through, we're competing against

keywords on Amazon that are gigantic and the entire pet industry is probably bidding on them. And so as an early stage brand, it is very hard to break through that. That's one of the biggest drawbacks for an earlier stage company with Amazon is that

It's hard to actually realize any sales that are not from an ad click. And so the cost of doing business for an early stage business is very high. But like I said, balanced with what I said earlier around the scale, and that's where people are shopping. And so there's a ton of consumers out there that you can reach through their through their tools as well.

well thank you that's all we have time for michael mike and christine i want to thank you again for this great conversation i and all of us in the audience i think really appreciated it