Retail as an industry battles notoriously thin profit margins, from small businesses to the biggest brands. That’s why many retailers aren’t just relying on their product inventory for profit. They’re increasingly looking to leverage another asset that’s right at their fingertips: first-party customer data. 

Retail media networks (RMNs) allow retailers and marketplaces to monetize data so that other brands can purchase and use it to advertise to audiences that are a great fit based on their browsing and buying history. RMNs benefit everyone: Retailers gain a new revenue stream with higher profit margins, advertisers get a great return on ad spend (ROAS), and customers see ads that better match their preferences and behaviors.

How should retailers build an RMN from scratch or optimize an existing one? It all comes down to your data infrastructure, and a composable CDP is one of the most powerful tools for turning customer data into a revenue-driving RMN. Let’s unpack the value of a retail media network strategy, the reality of RMNs with and without a composable approach, and why composability is the solution to your RMN challenges.

RMNs in action: onsite and offsite use cases

Whether you’re looking to offer ad space or provide advertisers with data for other channels, an RMN lets you monetize data you already have, leverage your existing platform, and give client brands ideal opportunities to reach the right audience. Here’s how onsite and offsite advertising looks in practice. 

Onsite advertising

For marketplaces with a robust platform where brands can advertise their products to ideal audiences, an RMN is an appealing revenue stream for potential clients. Brands can purchase ad space from a network that’s the perfect fit to reach their audience: 

• A consumer packaged goods brand buys ads on a major online shopping marketplace to get in front of audiences within their target demographic while they’re already shopping.
• A destination marketing organization places ads on a travel platform that can reach travelers when they’re already researching flights and hotels.

Advertising to the audiences of online marketplaces with widespread reach and digital real estate is an appealing proposition. But to build an RMN into a powerful revenue channel, retailers need an interface to help advertisers select audiences and target campaigns on their platform seamlessly and scalably.

Offsite advertising

Beyond providing an advertising channel, RMNs also allow retailers to monetize customer data. Online marketplaces glean valuable data from a wide swath of customers based on their behaviors, preferences, and purchases. High-affinity brands are eager to build audiences and target campaigns using that kind of rich data, and an RMN lets them purchase these segments for their advertising efforts on other channels. For instance:

• A fishing gear and apparel brand might purchase customer data and audiences from the RMN of a major outdoor retailer or marketplace. The overlap in their audiences makes this partnership a great fit for the smaller and more niche brand to reach ideal audiences.
• A brand that sells snack food or liquor sponsors a sporting event and wants even more value from the relationship. Through an RMN, the brand receives access to opted-in audiences to advertise to customers they have in common on other channels. When I led sponsorships as a Marketing Director at AB-InBev, I asked for this type of value from our partners, but at the time none of them had the technology or processes in place to facilitate it.

Monetizing customer data involves one of the biggest data challenges across use cases: balancing security with access. Retailers have a responsibility to protect customers’ privacy and personally identifiable information (PII) while allowing advertisers to responsibly leverage the data. Without the right interface to facilitate these transactions, creating and optimizing an RMN can be an insurmountable challenge.

Before: Building an RMN without a composable CDP

Leveraging your customers’ first-party data to share with brands to advertise on your site or offsite on other channels is no small task. It brings a range of security and segmentation challenges and requires a mature, robust data strategy to support the complexities involved. Retailers need a way to create targeted audiences, unlock the data for advertisers, and give them (ideally) self-serve access to activate that data and review results. 

Without a flexible solution to activate the data — one that sits on top of a data cloud to create a flexible, user-friendly interface — building, monetizing, and optimizing an RMN is drastically more difficult.

Here are two of the approaches retailers might take without a composable CDP:

1. The manual, technical approach. IT or data teams at both the advertiser and retailers handle the data exchange for the RMN. The retailer facilitates the data sharing from their warehouse using a data clean room, which contains a subset of the retailer’s data. Only the advertiser can access this data. The advertiser then brings their own data into the clean room to see where the data overlaps and identify targeting opportunities. This process requires major technical resources to write SQL queries that pull the data into the clean room, and it lacks scalability and repeatability.
2. The in-house solution. Some retailers build an RMN by creating their own solution. They implement some aspects of the clean room approach and build a homegrown UI for non-technical users to access RMN data. This approach solves some of the challenges of the first approach. Yet even major retail brands often find that their internal solutions are slow and lack the tracking capabilities advertisers want to ensure ROI and performance with their audiences.

These are fairly complex solutions for solving the basic problem of monetizing your data and making sure that advertisers can take advantage of the audiences you’ve built. Yet neither approach fully meets retailers’ needs when monetizing customer data. They leave ad sales teams facing bottlenecks with their brand partners and data and IT teams overburdened. In many cases, they might leave advertisers dissatisfied with their ability to leverage the data, target campaigns, and report on results.

There’s a better way. A composable CDP is the missing piece in the RMN puzzle.

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After: How a composable CDP drives more value with an RMN

A composable CDP transforms retailers’ capacity to drive value using their RMN. It unlocks all-new use cases that would otherwise be completely manual and hugely challenging — if not impossible — without a composable solution. By sitting on top of the retailer’s customer data in the data cloud, the composable CDP offers the flexibility to freely and securely grant advertisers access to customer data. As a result, they can build audiences, export the data to other channels, and effortlessly track performance. 

Retailers can create an interface for advertisers to securely self-serve on their data for a profitable, scalable RMN that drives revenue for their business and results for users.  

Here are some benefits of taking a composable approach to your RMN. 

1. Better access points for customers

One of the core benefits of the composable CDP has always been its ability to break down data silos within your organization and give data access to customer-facing teams like sales and marketing. When you build your RMN using a composable CDP, these benefits extend to your clients. A composable solution allows retailers to slice and dice data for brand partners in a way they couldn’t with a non-composable option, and integrates with many media network solutions you may already be using.

Let’s say a pet store chain is working with a pet food company and a pet toy brand to help them advertise on its platform using its customer data. A composable CDP lets the pet store seamlessly map the data layer that the pet food company can see (and activate) and keep that completely separate from the data layer that the pet toy brand can see. This data mapping capability is one of the biggest needs for retailers looking to drive more value from their RMN, and getting the right data access to the right customers is incredibly difficult without composability.

2. Better and easier segmentation

Because the composable CDP lets customer data remain in the tech stack and data warehouse, retailers can seamlessly build audiences for advertisers (or let them self-serve and build their own) using comprehensive audience data, without exposing critical PII to users. Using first-party data, they can develop more granular audiences for RMN clients in minutes. These high-value segments maximize your clients’ ROAS, leading them to advertise on your network repeatedly.

Best of all, media teams can do all this without relying on support from the data team.

With GrowthLoop, you can also recruit powerful help from AI. Prompt Marve, our studio audience builder, in natural language to quickly create goal-based segments and high-performing audiences.  

3. Easier measurement

Your advertisers need clear proof that spending money on your RMN is worthwhile. On top of the data cloud, a composable CDP makes it simple for retailers to track and report audience results to advertisers for clear ROI and continuous improvement. 

A composable CDP lets you build a feedback loop for your RMN clients and their marketing campaigns. The platform collects impression data through data ingestion and strategic partnerships with analytics platforms. Then, composability enables a centralized view of campaign performance in a single hub. For instance, the GrowthLoop Insights Hub shows exhaustive audience history, including spend versus return, clicks, impressions, and conversions. 

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Best of all, a composable CDP like GrowthLoop lets you create what we call a “unified loop” — one where every data point on campaign and audience performance feeds better AI-driven audience creation and suggestions. With a composable CDP, you don’t just measure and show data proving the value of advertising on your RMN. You leverage that data to make each campaign better, driving even more value for your customers.

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Monetize your customer data — while keeping it in the cloud

Data is one of the most powerful assets for your retail brand or marketplace. But when you rely on manual processes, homegrown solutions, or unwieldy tech stacks, scaling this revenue channel and delivering value to your RMN clients are huge challenges. 

A composable CDP on the data cloud lets you build repeatable processes and improve audience targeting and ROI for advertisers — all while your data stays in your cloud. Give your clients the self-serve access they want and the measurement and reporting they need to keep investing ad spend on your audiences.

If you’re looking to drive more value from your customer data or improve an existing RMN, composability is the way forward.