While inconsistent measurement across retail media networks is a problem, brands shouldn't wait for an industry standard. Instead, they should define their own measurement methodology and bring it to RMN partners. This allows brands to leverage proprietary consumer insights for a competitive advantage, rather than leveling the playing field with a universal standard.
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To succeed, marketers must stop passively accepting the data they're given. Instead, they must proactively partner with IT and privacy teams to advocate for the specific data collection and governance required to power their growth and personalization initiatives.
New measurement tools are moving beyond probabilistic models (guessing based on IP/device) to deterministic view-through attribution. By using first-party data like platform logins, marketers can now directly match an ad impression to a purchase, solving a major measurement challenge.
To accurately measure brand performance, marketers should create a composite "brand health score." This involves weighting multiple metrics—such as PR, AI visibility, traffic, and social media engagement—into a single, holistic score that provides a more comprehensive view than any individual channel metric could.
Due to signal loss from cookie deprecation, no single model like MTA or MMM is sufficient. The new gold standard is using all available algorithms together in a machine learning framework, allowing them to influence each other for a more accurate ROI picture.
Leaders often view brand metrics as 'fuzzy' for two key reasons: marketers suffer from 'learned helplessness' due to a constant churn of new measurement tools, and they often measure brand performance in an absolute vacuum, failing to provide the competitive, longitudinal insights that boardrooms actually need for decision-making.
Advanced retailers are moving beyond treating retail media as an ad channel for short-term sales. They integrate it with loyalty programs to deliver personalized value, which strengthens long-term customer relationships and retention, making it a strategic lever for growth.
Traditional metrics like reach are becoming obsolete. The new imperative is to measure how AI models interpret and present your brand. This involves tracking a 'share of influence' across earned media, analyst reports, and reviews, as well as monitoring AI prompt results and citations to gauge brand authority and message consistency.
To break down silos between trade and media, brands should avoid overhauling their entire annual plan. Instead, select a major "tentpole" campaign (e.g., the Olympics) to pilot a unified investment strategy. This approach de-risks the change by focusing efforts, defining clear cross-channel KPIs, and forcing collaboration with retail partners on a specific goal.
Shift the mindset from a brand vs. performance dichotomy. All marketing should be measured for performance. For brand initiatives, use metrics like branded search volume per dollar spent to quantify impact and tie "fluffy" activities to tangible growth outcomes.
Retail media network maturity isn't defined by scale but by organizational structure. The most effective RMNs centralize control under a single leader who oversees all brand touchpoints (trade, media, in-store). This "benevolent dictatorship" model prevents internal P&L conflicts and enables the creation of truly holistic, customer-centric solutions.