As shoppers face more choices, retail media offers a direct way to influence conversion and build loyalty. It focuses on a small group of high-intent buyers who are already close to making a decision.
Watch the videos below as our CPO, Brian Holmgård Kristensen, explains how retail media supports different customer journeys and helps you, as multi-brand retailer, get more value from each one.
Retail media is becoming the next major channel in digital advertising, giving brands and suppliers a direct way to reach shoppers when buying intent is highest. Unlike ads shown on external channels, retail media placements live inside the retailer’s own environment, such as search results, category pages, or onsite recommendations.
Because these placements sit close to the point of purchase, brands can reach shoppers who are already in a buying mindset, increasing the likelihood of conversion. And when retailers add AI-driven, behavior-aware ranking, these placements become even more relevant. The system learns from real-time signals and predicts which products a shopper is most likely to engage with next, making each impression feel naturally integrated into the journey.
What sets retail media apart is its use of real-time data and AI-driven behavioral signals to keep each placement relevant. By analyzing browsing and purchasing patterns as they happen, retailers and brands can surface products at the moment a shopper shows intent. Instead of spending resources on broad reach, brands focus on consumers who are already looking for products that fit their assortment.
For example, if someone has been searching for a certain type of blender, the predictive layer can surface a well-priced option directly in the search results. The value of this approach is its ability to deliver relevant offers that feel natural in the experience, blending in with organic results instead of distracting shoppers with unrelated ads.
Every interaction a shopper has with a brand generates behavioral signals that help identify intent and predict what they may want next. Below are four example journeys from Mia, Max, Jan, and Eva.
Mia visits Kop & Kande and searches for a coffee machine. With 119 options, the system only knows her intent from this initial query. AI-driven ranking uses real-time behavior patterns to surface products most likely to convert, with select high-value items included. Even with limited data, the results stay relevant by highlighting the strongest matches within “coffee machines.”
Max starts on a search engine, looking for a Siemens espresso machine. After landing on the product page, his next actions, viewing espresso models and later searching for “coffee machine”, add more context. The system combines these signals to push similar espresso options to the top of his results, recognizing Max’s preferences in real time and increasing purchase likelihood.
Jan searches for glasses directly on the site and receives 1,215 results. With little personal data to narrow the selection, the system uses aggregated behavioral trends to highlight currently popular items. This establishes broad relevance early on while waiting for Jan’s next interactions to refine future suggestions.
Eva starts on a search engine with a clear goal: Rosendahl white wine glasses. After reaching the PDP and adding them to her cart, she searches for “glass” to find matching pieces. The system uses her purchase intent and browsing history to surface complementary items from the same brand and series, guiding her toward a coordinated set.
Mia, Max, Jan, and Eva each give subtle signals about their intent and where they are in their journeys. Their paths look similar on the surface, but the products shown to them differ because the system continuously re-evaluates what is most relevant in the moment using real-time intent and predictive scoring. For suppliers like Rosendahl or Siemens, this level of insight is highly valuable when seeking more visibility and sales.
To act on these signals, retailers need technology like Relewise Retail Media, which uses first-party data and AI-driven relevance to personalize the experience while optimizing ad placement dynamically.
Say you're a multi-brand retailer negotiatiating with Kenwood to promote their kitchen machines. They want their products highlighted in search results and PLPs whenever users search for “kitchen machines.” This level of precision can be tailored directly to their needs.
You’ve already defined that the first three placements in search and PLPs can be reserved for sponsored listings, configurable separately for mobile and tablet. Kenwood chooses to bid for the top position in both placements.
You agree on a budget—for example, a CPM of 20 DKK, giving them 1,000 impressions for 20 DKK. Because buyers are already showing high intent at this stage, the investment is efficient. With a total budget of 10,000 DKK, the campaign is activated in Relewise Retail Media. Kenwood’s products now receive premium exposure across key touchpoints until the budget is spent. As new products arrive, the system includes them automatically to keep the campaign current.
As more suppliers bid for the same positions, Relewise Retail Media manages bidding and placement automatically, giving top positions to the highest bidder without manual work.
To support brand and supplier relationships, Relewise Retail Media provides clear reporting on performance. It tracks engagement and impact over time, giving you transparent insights to share with suppliers so they can adjust future campaigns confidently.
Relewise Retail Media strengthens collaboration between retailers and suppliers by creating shared commercial value. Retailers use first-party data to offer tailored experiences that brands and suppliers are willing to pay for without building the infrastructure themselves. Retailers turn their digital real estate into a revenue-generating media channel, while suppliers gain targeted visibility at moments of high intent. The outcome benefits customers, retailers, and suppliers alike.