Retail media for mid-sized markets: monetizing the relationship with the shopper

A channel that changed advertising

McKinsey estimated that advertising spend on retail media networks in the United States could reach USD 100 billion in 2026, and that these networks operate with margins of 50% to 70%. In its survey of more than 180 advertisers, about 70% rated the performance of these networks as better than that of other channels, and more than 80% said their spending on them came from new budgets (McKinsey).

The reason for the growth is simple. The retailer knows who buys, what they buy and when. That information lets a brand target its ad to the right shopper and, above all, prove that the ad produced a sale. No other channel offers that traceability with the same precision.

It’s not just for the big players

The conversation about retail media usually centers on large global retailers. But the logic applies to any company with a direct, repeated relationship with shoppers: regional chains, niche e-commerce platforms, distributors with a network of points of sale, service operators with visitor traffic.

In our work with a distributor, we explored the use of artificial intelligence to place outdoor advertising more efficiently, by cross-referencing foot-traffic and point-of-sale data. The initial lesson was that a mid-sized company’s advertising inventory is broader than it seems: it includes physical spaces, packaging, customer communications, owned digital channels and presence at third-party points of sale.

The asset is the data

What sets a media network apart from a simple ad space is data. A retailer that sells space without data competes with any billboard or digital medium. A retailer that offers audiences defined by their purchasing behavior, and that measures the ad’s effect on sales, offers something nobody else has.

That requires three capabilities. The first is identifying the shopper consistently across channels, usually through a loyalty program or a digital registration. The second is a platform that allows audiences to be segmented and campaigns to be activated. The third is incremental sales measurement that the advertiser finds credible. Without the third, the advertiser buys once and doesn’t come back.

What the advertiser is looking for

The McKinsey study shows that 71% of consumers expect personalized interactions, but only 23% believe retailers do it well. That gap is the opportunity. The advertiser wants to reach the right shopper with a relevant message and know what return it got.

In our work with the sales teams of consumer companies, we found that measuring advertising spend was often the weakest link. Brands invested without monitoring the return in real time. A retailer that offers that measurement solves a real problem for the advertiser.

Where to start

For a mid-sized player, the recommendation is to start with what it already has. First, take stock of the touchpoints with the shopper and estimate their reach. Second, identify the supplier brands that already invest in promotion at your points of sale, because they are the first natural advertisers. Third, offer a pilot with clear measurement, even a simple one, such as comparing sales at locations with and without a campaign.

The right order is the reverse: advertisers, data, measurement and then the platform.

The most common mistake is starting with technology. Buying a retail media platform before having advertisers, data and a dedicated sales team produces a fixed cost with no revenue. The right order is the reverse: advertisers, data, measurement and then the platform.

Governance and trust

Monetizing shopper data requires rigorous governance. In Colombia, the processing of personal data is regulated by Law 1581 of 2012. Any media network must have the authorization of the data subjects, clear usage policies and mechanisms for shoppers to exercise their rights. Shopper trust is the asset that makes the model possible; losing it destroys the model.

The economic model

The appeal of retail media lies in its economic structure. Advertising revenue carries margins far higher than those of the product-selling business, because it rests on assets the retailer already has: traffic, space and data. For a retailer or distributor with tight margins in its core operation, even modest advertising revenue can have a meaningful effect on profitability.

That appeal comes with a condition: the media network must not cannibalize the commercial relationship with suppliers. In many cases, brands already pay the retailer for displays, promotions or preferred placement. A well-designed media network turns part of those payments into measurable advertising investment, with more value for the brand, instead of adding a new charge on top of the existing ones. The conversation with suppliers should be framed as an improvement in the return on what they already invest.

The role of AI

Artificial intelligence is expanding the possibilities of retail media. It allows audiences to be segmented more precisely, recommends where to place each piece (in-store, onsite or in outdoor media), personalizes messages and measures effects with more sophisticated models. In our exploration with a distributor, using AI to place outdoor advertising showed that the value lies in cross-referencing information sources that used to be analyzed separately: foot traffic, point-of-sale locations and commercial performance.

As in other areas, AI amplifies what exists. Without reliable purchase data and clear governance of its use, its recommendations are no better than intuition.