Mrunal Bhagat, Retail Media Lead at Pearson, talks about her career shift from agency-side digital marketing into retail media and how AI is creating a new “recommendation economy.”
What is your role at Pearson, and what does your day-to-day work involve?
I’m the retail media lead at Pearson, handling all the retail channels across the UK, EU and US. But I would say my mission is wider than my title.
I help the brand, as well as a few smaller brands, understand where there is a gap and why there is a gap between their marketing metrics and their commercial numbers. I diagnose why there is a difference between what the marketing team is saying and the sales reality. Then I build a framework or strategy that connects the right data signals with the marketing plans, which yields commercial success beyond a good-looking dashboard.
In a sense, I turn data into dollars.
Pearson is an interesting proposition in retail media. How does the business fit into the space?
Pearson within retail media is an interesting case because no one would necessarily imagine that a B2B or education publisher has anything to do with running ads on Amazon.
But when a parent or student types “GCSE history revision guide” or “workbook” into Amazon’s search bar, that is a highly specific, intentional, needs-based query. Retail media was designed to capture exactly that.
Pearson sits at the intersection of education and commerce. Even though it is a needs-based brand, the stakes involved in choosing the right product to promote, in front of the right customer, at the right moment, are high.
Retail media gives us a platform through which we can reach broader audiences who might not have purchased from us if it wasn’t for the retail channel.
Which retail partners do you work with?
We work across multiple retail channels, including Amazon, Costco and WHSmith.
How did you first move into retail media?
It all started with my dad. He’s a creative director on the agency side and now owns a homegrown agency.
In the early 2000s, I used to accompany him to his office every other Friday or once or twice a month. In those days, directors had private offices and the team worked in cubicles. I would watch his team brainstorming around client briefs and storytelling.
There was a lot of passion. Every media strategy they designed was a piece of art in my eyes. A few years later, they went to Cannes and won a Cannes Lions Gold. When I watched my dad walk through the door afterwards, I saw a sense of satisfaction. He loved what he was doing.
I think very few people have the opportunity to do what they love. That was when the seed was planted in me: I didn’t know what it was, but I wanted to fall in love with what I did.
I joined Ogilvy in around 2015, at a time when the agency was creating a parallel vertical for digital marketing because it was booming. I decided that if digital marketing was booming while traditional marketing was changing, I wanted a formal education in digital marketing, so I moved to the UK to do my master’s.
Then Covid hit, and I landed at Pearson.
For the first year or two at Pearson, I didn’t really know what I was doing in industry terms. I was running ads and managing the channel, but I didn’t know what that meant in an industry language.
I went to an event at Amazon’s office and someone asked me what I did. I explained my role and they said, “That’s retail media.” I thought: I understand retail, I understand media, but what is that together?
I went down the rabbit hole. As I started to understand the industry, I realised that retail media had enormous untapped potential, but also an enormous amount of confusion. I think confusion and opportunity have an equal slice.
Brands are still figuring retail media out. They feel they should use each and every ad type the industry offers to be relevant, while agencies are often reporting back on a limited metric of ROAS, which is essentially existing sales.
I realised this was systematic chaos. I decided to dedicate my career to decoding that mess and helping brands and the industry as a whole to be more than they are now, and to give them a directional pathway for commercial growth.
What excites you most about retail media?
What excites me is that the walls between retail and media have collapsed, and data sits somewhere in the middle.
If we go back to the early 2000s, brands were hitting in the dark. A baby-product brand might send a marketing flyer to a household that actually required adult diapers. It was a hit-and-miss, “spray and pray” approach to broader audience targeting, which required a lot of trial and error and investment.
Today, retailers possess incredibly interesting insights. They know who the customer is, what they buy, when they buy, how they buy, how often they return and so on.
Brands can leverage that information, plug it into their media plans and create a strategy that is personalised to the customer, with content that resonates. The customer can feel that the brand knows them well, which wasn’t possible before.
What do you think brands are getting wrong?
I would say measurement. Brands are making a mistake because, proudly, I say that ROAS is a fraud metric because it’s limited. It doesn’t tell you anything about whether the sale would have happened anyway, whether you showed an ad or not. It simply claims credit for a sale. It fits at the lower funnel.
Today we can’t necessarily track a consumer’s buying journey in the same way because those journeys are happening within well-guarded AI and LLM environments. I think we have moved from the digital economy to the creator economy and now into the recommendation economy.
People are using ChatGPT and other AI tools for product recommendations. So the recommendation economy is entering from two directions: an LLM such as ChatGPT acting as an influencer for consumers, and AI being integrated within retail channels and partners, such as Amazon’s AI shopping tools.
Because of AI and LLMs, the market and consumer behaviour are being disrupted. It will be a challenge, but also an exciting opportunity, for brands to make sure they are within those answers – and not simply present, but being spoken about positively.
How does that thinking influence your own retail media strategy?
The problem is that people understand that ROAS is a limited metric, but they then ask: “If not ROAS, then what?”
That’s why I created our Trojan Horse model, to provide a directional framework for commercial success. It helps brands move away from ROAS and gives them a way of influencing senior decision-makers who base commercial decisions on that metric.
Can you explain the Trojan Horse model?
The Trojan Horse model came directly from a critical industry challenge: brands are making major commercial and strategic decisions based purely on a lagging media metric – ROAS.
ROAS tells you about existing sales and what happened after the media plan was executed. It doesn’t tell you what you should be doing before you invest that capital in advertising.
The Trojan Horse model is a directional framework designed to look beyond the outer shell of ROAS. It focuses on three “Trojan soldier” metrics that I believe drive real growth.
The first is customer value, which informs the brand about its commercial headroom – where and on whom it should spend its money.
The second is incrementality, which tells you whether your media strategy is attracting and driving net-new customers, or simply claiming credit for an existing sale.
The third is share of model: are you present within LLM recommendations and, if you are, how highly is the LLM speaking about your brand?
In a nutshell, the Trojan Horse model directs the media strategy, which then influences execution and ultimately commercial success.
How has the model resonated with brands?
I mentor smaller brands and startups, and it has been helpful for them. I worked with a small, family-run chocolate business that was targeting people who would purchase from them anyway. Even if they stopped advertising, those customers were so loyal that they would keep coming back.
The customer-value element of the Trojan Horse model helped them understand that they needed to reach different people. We incorporated negative targeting to stop showing ads to certain customers and then looked at incrementality. That helped them grow sales.
It also helped them think differently about content. They had been using the same content for every ad type and every customer. They realised that a particular customer segment, such as dark-chocolate buyers, might need a different tone of content, while consumers who had clicked on an ad but not purchased needed another.
So the Trojan Horse model becomes both a diagnostic framework and a reporting framework.
Who has inspired you during your career?
My inspiration doesn’t entirely come from retail media. I’m a huge admirer of two people in my life.
The first is Peyush Pandey, the former Chief Creative Officer at Ogilvy. One thing I learned from him was the art of storytelling.
At the end of the day, we are promoting a product to a consumer, but the way we create that content and the storytelling behind an ad is what stays with the consumer.
It’s important how you reach the consumer, but it’s equally important what message and what content you use to reach them. “Have a break, have a KitKat” is instantly recognisable. KitKat has become part of our lives.
The second is Anna Wintour. I see her as a disruptor. Vogue before Anna Wintour and Vogue after Anna Wintour are completely different.
She looked at an established way of doing business and challenged it. Just because Vogue had been doing something for many years didn’t mean it was necessarily doing it right.
I took that inspiration when I realised that ROAS was a flawed metric. I didn’t want simply to say it was wrong; I wanted to provide a solution. That’s why I want to dedicate my career to improving the industry.
What are you most proud of in your retail media career so far?
In terms of strategy, I’m proud of the Trojan Horse model.
It came from identifying a critical industry problem and trying to solve it. I don’t want brands to make major commercial decisions based purely on a lagging media metric.
The framework is designed to make them look beyond ROAS and consider customer value, incrementality and share of model – and use those insights to determine the right media strategy.
What do you see as the next big development in retail media?
AI disruption and the recommendation economy.
There is already a question floating around the industry: how do you measure an LLM-influenced sale? What is the attribution?
I don’t think there is currently a direct or accurate way to say that an LLM or ChatGPT influenced a sale, or to calculate the ROAS of a ChatGPT sale.
The major AI companies aren’t going to provide that kind of granular insight. So the best way to work with ChatGPT or another AI system is to understand how it works and what influences it – what kinds of citations and associations influence its recommendations.
That means focusing on organic content, because AI models were trained on content that leaves a permanent digital footprint, rather than on an ad. I think that’s the future: brands need to understand how these systems work and how they should work with them.
Finally, what is the one thing you would most like brands to understand about retail media?
Brands are making the mistake of basing commercial decisions on a media metric.
A brand’s dashboard might contain 100 data insights, but when it comes to making a commercial strategic decision for the next year, the second half or the next quarter, they look at ROAS.
They might see that sponsored product ads have a high ROAS and decide to invest more because that’s where the money appears to be. But sponsored product ads are designed to deliver a higher conversion rate. That doesn’t necessarily mean you are growing.
Brands need to differentiate between their growth strategy and their media strategy.
The growth strategy comes from the business objective and first-party data. That growth strategy should then influence the media strategy.
I always think of retail media like a sushi platter. When you get one, you pick and choose. I don’t eat sashimi; I love a dragon roll, so I’m going to eat that.
Retail media offers a variety of media touchpoints. It’s the brand’s job to pick and choose. The way to do that is through a framework such as the Trojan Horse model, which helps identify the right media touchpoint, ad type, retail partner and content for the audience.
