Retail Media Networks: A Call For Measurement, Transparency and Consistency

Return on Ad Spend (ROAS) vs. Incremental Return on Ad Spend (iROAS) 

"Half my advertising spend is wasted; the trouble is, I don't know which half." The old Wanamaker quote still holds true when it comes to RMNs. Because their primary measure of success is ROAS, networks aren’t providing brands and agencies with a full picture of how their ad dollars are working for them. Insights into incrementality and new consumer growth are critical to effectively driving new sales, but most networks stop short of providing those advanced measurements. And the platforms that have started offering incrementality testing, like Instacart and Walmart, have yet to be finetuned enough to discern between key facets such as brand affinities, propensity to purchase, recency and demographics. For the health and wellness of their brands, advertisers should keep pushing for incremental return to become standard in RMN measurement. 

Attribution and Revenue Recording

Retailers attribute purchases to ads inconsistently, with most RMNs defaulting to last-click attribution, which credits a sale to the last ad a shopper engaged with before their purchase. This narrow approach to attribution doesn’t consider the impact of multiple exposures or interactions along the consumer journey. Instead, RMNs could be leveraging a data-driven attribution method, which would give credit to the touchpoints based upon their contribution to the sale. Additionally, rather than a preset length of time for a consumer to convert (e.g., 7, 14, 30 days), they can use a data-driven attribution window based on the actual product purchase cycles—meaning the longer a product takes to be purchased, the longer its attribution window. This data-driven approach to attribution methods and windows, informed by the retailer’s own data, would allow brands to manage and scale large product portfolios effectively. 

RMNs also record and apply revenue inconsistently. They either record revenue at the time of sale or retroactively apply it to the date of the ad click or view, making it more difficult for analysts to properly extract and store data that is dependent on attribution windows. This inconsistency could be resolved through industry-wide adoption of a single method. 

New-to-Brand Metrics

Increasing household penetration is key for many CPG brands, and RMNs have the unique opportunity to provide historical purchase data at the consumer level. Some platforms, like Instacart, have adopted new-to-brand sales metrics, providing brands with visibility into purchases made by existing customers and new shoppers. To make the most of this metric, RMNs should adopt measuring the number of new households, as opposed to total purchases, to refine targeting and reduce waste. Providing advanced measurement for new households and enabling brands to suppress ads for consumers who have recently made a purchase would allow for further extended reach and reduction in wasted dollars on a consumer who is less likely to purchase.

Transparency and Verification

Historically, RMNs have operated as walled gardens, lush menageries of data kept guarded from brands, limiting their ability to track performance. This includes restrictions on tagging with third-party verification partners like DCM, MOAT or IAS. Although media onsite faces fewer brand-safety risks than on the open web, other verification measures like viewability are critical to advertisers. By adopting industry standards for verification and collaborating with brands to establish appropriate terms and conditions for payment, RMNs would clearly define billable events, such as clicks for sponsored search campaigns or impressions for display campaigns. Verification standards will ensure accountability, transparency in performance, and the ability to optimize effectively.

Looking Ahead

Industry standardization is within reach, but it’s up to brands, agencies and solution providers to band together and demand more from retailers and their media networks. For a truly beneficial relationship between RMNs and brands, RMNs should enhance transparency of results and implement more effective measurement. Allowing brands access to more data will only increase the value of RMNs, leading brands to invest even further in them—a true win-win situation.