As retail media experts, we hear a lot about brands’ and retailers’ goals – and as you may expect, they vary based on the company’s industry, size, digital maturity, and more. However, over the past few years there are two pursuits that come up time and again:
- How can I better meet my shoppers’ needs?
- How can I diversify my revenue to fuel initiatives across marketing and other business areas?
These are big business challenges – but there is a solution. First-party data, when collected and used correctly, can help brands and retailers alike create new revenue streams and better serve their customers.
There are three main areas where first-party data can help companies turn this opportunity into reality across the retail media landscape:
1. Media
For retailers: This is the primary way we see companies create alternative revenue with their first-party data: creating a retail media network (RMN). To make the most of their first-party data assets, retailers must curate their offering around what brands are asking for. In our 2022 research, brands expressed self-service options and being easy to work with as two key features they look for in an RMN. That means retailers who can set up easy-to-use, self-service audience deployment in their media offering can stand out in the increasingly crowded RMN landscape.
For brands: Though they may not have the scale and depth of offering of an RMN, brands can still use their owned and operated properties and global sites as an ad network. This drives media efficiencies because media placements stay within the brand ecosystem versus prospecting with a third-party media platform. They can use their own consumer first-party data, combined with purchase behavior across owned and operated, to curate a frictionless experience for a qualified shopper. Alternatively, brands can use this space to cross-sell their own products. Take a CPG brand, for example, that sells coffee makers. They could use their thank-you page to promote their own creamer product, which delivers a helpful experience to the shopper while also saving on ad fees and keeping the user on-site.
2. Partnerships
For retailers: Retailers can use a privacy-safe clean room environment to co-mingle their first-party data with others to create better shopper experiences. The partnership could be between a retailer and a brand who co-mingle their first-party assets to build a better picture of the shopper and meet their needs more holistically. The partnership might also be between the retailer and a tech partner to gain access to additional customer data, like life event information, visitation behaviors, and more – again enabling the retailer to better serve the shopper in their journey. The retailer would receive revenue through the licensing of their data to the clean room which can then be used for insights and/or activation against publishers. Visit our webpage to learn about Merkle’s Data Solutions offering that provides insight into these attributes and others.
For brands: This is an untapped area so far in the retail media landscape, but brands could agree to partially or fully fund an RMN in exchange for their first-party data assets. This can help them reach more qualified users and create mutually beneficial outcomes for both the retailer and brand. It also strengthens their partnership and sets the groundwork for future collaboration across the RMN.
3. Monetization
For retailers: First-party data assets are in high demand. Our research showed that more than half of brands believe RMNs can add more value by providing data and insights with media buying optional. Make sure you have this available to sell to brands for them to get a better understanding of their customers and how they engage with you. Remember that how you package the data can influence how valuable it is for brands. Quality trumps quantity: a curated audience with relevant attributes can be easier to handle and use than a full customer file.
For brands: Brands have valuable first-party data assets, too – particularly in the form of loyalty data. They can similarly package their audiences to sell to relevant parties. Here’s a real-life example: a pregnancy app working with a tech partner may learn that one of the first items expecting parents purchase is a new car. Armed with that research, the pregnancy app can approach car brands with their first-party data assets to allow the car brand to reach users of their platform.
Conclusion
First-party data is the key for brands and retailers that want to add new revenue streams to their business while also amplifying retail media programs. By doing so, retailers differentiate themselves in a complex landscape, while brands create stronger partnerships with companies with a similar audience. All of this translates to better experiences for shoppers – whether that is through more robust customer profiles or a new budget that enables other innovations across the business. By investing in first-party data assets and monetizing them appropriately, everybody wins.