4 ways AI is transforming retail media

What factors are driving momentum for non-endemic advertising? JULY 8, 2024 [4 ways AI is transforming retail media]( Some 53% of marketers believe AI will significantly enhance the way shoppers are targeted and served relevant ads, per a survey from Cooler Screens. Both AI and [retail media]( are still developing. As both of these areas mature, AI will make retail media data even more powerful. Here are some ways AI is improving retail media. Ad-targeting and personalization: 52% of marketers predict AI will enable highly personalized shopper experiences, according to Cooler Screens. - Brands using AI and machine learning to personalize ads have seen a 1.3 times increase in incremental return on ad spend, according to data from 84.51°. - For Kroger Precision Marketing, personalizing ads looks like adjusting copy and imagery based on whether an ad is [targeting]( pet owners, eco-friendly shoppers, or health-conscious consumers. - Generative AI can be used to adjust campaigns based on contextual data like location. For example, the same ad for beer could be adjusted from one state to another to feature a different football team’s fans. - Generative AI can also be used to generate entire images, as is the case for Amazon Ads. Story continues below. Marrying in-store and online data: 54% of marketers view AI as crucial for seamless integration of online and offline data, according to Cooler Screens. - In-store advertising will make up just 0.7% of US omnichannel retail media ad spend this year, per our March 2024 forecast. - But 83.7% of total US retail sales will happen in-store, per our February 2024 forecast. - There is massive potential for retail media advertising in-store, but it’s more difficult for advertisers to measure the success of omnichannel and in-store campaigns on physical retail sales than to measure how an online campaign results in an ecommerce sale. - As AI evolves, marketers are optimistic about its ability to make sense of in-store and online data, telling a complete customer story, which could unlock more in-store retail media ad spend. Incorporating inventory data into ads: Ads for products that aren’t in stock are wasteful for [retailers]( and brands. - [Walmart Connect and Walmart Luminate]( have combined ad and inventory efforts to help refine ad messaging. For example, advertisers can target segments of a brand’s customer base that are trading down and target them with value-based messaging. - AI can monitor these inventory levels and adjust ads based on availability. - Walmart expects AI to enhance these insights in the year ahead, as Walmart Data Ventures’s Mark Hardy said in an interview with Retail TouchPoints. Making sense of the wealth of retail media data: Retail media offers extensive data to brands, but even savvy marketers can have trouble making sense of the volume of information collected. - Brands working with multiple retail media networks have the added challenge of making sense of data across platforms using different metrics. - Focusing on the metrics that are most important for your brand, rather than looking at every channel and data point, is the best way to prioritize retail media data, said Kristina Ciampi, head of measurement, go-to-market, for [Amazon]( at [Advertising Week New York]( in October. - AI can help drill down what the best data points are to focus on. It can also summarize large quantities of data to build a broader image. [Read online]( [What factors are driving momentum for non-endemic advertising?]( - Retailers’ first-party data has value that extends beyond endemic brands. With the success of retail media playing out under the looming shadow of third-party cookie deprecation, retailers are well positioned to make a case for the value of their data for non-endemic brands. In an April 2024 report by LiveIntent, more than 8 in 10 (84%) US marketers said they are more likely to invest in retail media because of third-party cookie deprecation. - The transaction-based data retailers collect over time enables them to create highly targeted audiences. Reaching audiences with proven purchase behavior holds appeal for advertisers that want to ensure the efficacy of their digital ad spend. And retailers with well-developed loyalty programs are especially well positioned to create qualified audiences, given their even deeper insights and knowledge about their customers. - Non-endemic advertising has the potential to help retailers of all sizes overcome barriers to scaling revenues. Large retailers operating in commodity categories such as consumer packaged goods (CPG) are often competing for advertising budgets from the same pool of endemic advertisers, while smaller specialty retailers have fewer endemic advertisers to choose from in the first place. Extending ad inventory to non-endemic advertisers is one way to broaden the pool of potential revenues. - Retailers’ owned and operated properties provide greater security for advertisers. Ads that appear alongside risky content or fake news are among the biggest media challenges facing US publishers, according to a September 2023 study from Integral Ad Science and YouGov. But ads on retailers’ owned properties, whether digital or physical, provide advertisers with a high degree of confidence in the contextual safety of the surrounding content. - Retail media’s off-site and up-funnel shift has created more available ad inventory. Off-site ad spend is forecast to grow at a faster rate than on-site through 2028, and it will represent more than 20% of total retail media ad spend by 2025. Consequently, many retailers are finding themselves with an increased supply of ad inventory free from the constraints of their finite, on-site digital real estate. - The emergence of commerce media will increase the prevalence and practice of non-endemic advertising. Verticals outside of retail, such as financial services (e.g., Chase, PayPal) and travel (e.g., Lyft, Expedia), are increasingly leveraging their first-party transaction-based data to launch media offerings of their own. Non-endemic advertising is a natural fit for sectors that have access to purchase-based data but don’t sell products directly to consumers. [Read online]( Email sent to: {EMAIL} If you cannot view the HTML newsletter, [please read it in your browser here](. 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