Retail media networks use first-party data such as transaction history to connect brands with prospects close to the moment of purchase, driving revenue.
RMNs can produce relatively low customer-acquisition costs and may disrupt other forms of advertising or even traditional retail co-op relationships. But they are not perfect.
RMNs on the Rise
Amazon was among the first marketplaces to experiment with retail media. From the beginning, Amazon collected first-party data such as customer behavior and purchases with unparalleled precision.
Through RMNs such as Amazon, Walmart, and many others, brands can reach consumers in decision-making modes. A shopper looking for shampoo on the Walmart marketplace is an opportunity for a brand to pitch its related (or competitive) product. The result is often very low customer acquisition costs.
The impact of RMNs is more than cost efficiency. As they expand from mere product providers to ad platforms, retailers challenge traditional co-op relationships.
Retailers and manufacturers have traditionally shared marketing costs for mutual benefit. But retailers with their own media networks might not need that co-op funding. Instead, they can generate ad revenue independently, disrupting the conventional marketing model (and supply chain).
These advantages are counterbalanced by potential problems, including privacy concerns, data management, and an evolving digital landscape. The hurdles are significant but surmountable.
RMNs’ ecosystems are different from other digital ad platforms.
First, there’s the precise targeting built on first-party data. RMNs identify shoppers likely to buy certain products in the next few seconds.
The result is a win-win-win. Retailers profit from ads, brands enjoy improved conversions, and consumers see relevant product promotions just when they need them.
The uniqueness of RMNs extends beyond precision to a virtuous sales cycle. More sales generate more data, leading to better targeting. Better targeting boosts sales.
Moreover, RMNs offer ad diversification. Brands can utilize many and varied RMN channels and ad types.
Despite their promise, RMNs face challenges.
Among those are privacy concerns, advertising standards, tech compatibility issues, and the struggle to maintain relevance amid dynamic consumer behavior.
Privacy is a significant worry despite RMNs’ reliance on first-party data. Laws and regulations could apply, such as the E.U.’s General Data Protection Regulation, the California Consumer Privacy Act, the Colorado Privacy Act, and Virginia Consumer Data Protection Act. Thus RMNs must strike a critical balance between data thriftiness and effective targeting.
Tech compatibility poses another challenge. Data must flow smoothly between retailers, brands, and other participants. Achieving this integration can be complex given the many systems in use. There is no common language or industry standard for retail media.
Keeping up with dynamic consumer behavior is difficult too. Relevant and engaging ad creative is a continual effort. RMNs must be agile, ready to respond to market shifts.
Opportunities and Trends
Despite the challenges, the RMN landscape is ripe with opportunities and promising trends.
Data privacy regulations impact other advertising platforms much more. That alone could push advertisers towards RMNs. The impending demise of third-party cookies coupled with increasingly stringent privacy regulations could make first-party data options more appealing.
Further, RMNs can take advantage of the growing demand for personalized advertising. Consumers increasingly expect personalized experiences, and RMNs can deliver highly targeted, relevant ads that meet this expectation.
Also, RMNs can leverage emerging tech trends. Artificial intelligence and machine learning can improve targeting, while augmented reality can enhance ads.
Lastly, the creation of common standards could boost RMNs. Developing a shared language and protocol could ease many compatibility hurdles.
In short, the future looks promising for retail media networks.