Marketers at retail media networks are at a crossroads.

Online retail sales are booming and offer the potential for high-margin revenue even as profit margins in traditional retail get thinner. But to realize this potential, retailers (and other enterprises with a large ecommerce business) must find ways to monetize the mountains of valuable first-party customer data at their disposal. By offering brands access to audiences built from their first-party data, they can develop a parallel revenue stream, capturing ad dollars from brand partners to supplement their product- and service-based sales by offering ad placement on their retail media networks (RMNs). 

The decline of third-party cookies and data privacy regulations have only increased the value of RMN real estate. That’s because without these cookies, it’s becoming harder for advertisers to collect the first-party data needed to meet the level of personalization that consumers have come to expect.

But an RMN’s value depends on an advertiser’s ability to create and sell precisely targeted audiences — and, ideally, measure the success of campaigns and optimize those campaigns continuously. 

The rise (and fall) of manual and in-house solutions

RMNs have traditionally relied on manual data transfers or a semi-automated system built in-house to deliver a dataset of customers from which advertisers can create targeted audiences and orchestrate marketing and advertising campaigns. 

Unfortunately, these solutions bring a host of challenges that impede a retailer’s ability to capitalize on the potential of its first-party data. 

The manual approach is arduous. It requires IT and data teams at both the retailer and the advertiser to manage the data exchange. The process involves exporting the subset of first-party data from the retailer’s data management platform to a shared clean room accessible only by this advertiser. The advertiser then imports its own data to the clean room, finds relevant overlaps through identity resolution, and identifies the best customers with which to build an audience.

Not only is this approach time-consuming, it’s also difficult to automate or scale: Updating the data to reflect new information from a campaign must once again be transferred manually from customer database to clean room.

There’s also no easy way to activate the data once it’s in the clean room; it must be exported to martech systems that handle audience building, journey orchestration, and analytics reporting.

Solutions built by in-house engineering teams also leverage a clean room — one fitted with a homegrown user interface that lets non-technical users access and activate the customer data. While this approach may help with activation, in practice these systems are expensive to build and maintain while still requiring engineering support.

The evolution of the Compound Marketing Engine for RMNs 

The GrowthLoop Compound Marketing Engine is an enterprise-grade platform for retail media networks that solves these problems. 

By accelerating the marketing cycle, a Compound Marketing Engine drives compound growth — much like compound interest increases a bank deposit in value more quickly. The GrowthLoop Compound Marketing Engine does this by working from data in a cloud-based enterprise data warehouse. With the cloud at the center of the platform, all first-party customer data — as well as sales, profitability, and campaign performance analytics — can be integrated, linked to any marketing channel, segmented for precision audience-building, activated, and updated continuously with customer data gleaned from ongoing campaigns. 

This cloud-native model provides several benefits for RMNs:

• By operating on a cloud-based data warehouse rather than a manually aggregated and updated database, GrowthLoop makes data management more efficient because the data never leaves the cloud, reducing data governance and compliance risks. 
• Implementations are also faster because data never needs to be reformatted, making it easier for retailers to provide access to the customer data advertisers need to build the audiences of prospects most likely to convert. 
• The ability to sync across any marketing channel delivers a cohesive multichannel journey, ensuring consistent branding, messaging, and personalization throughout a campaign. 

Designed for marketers, added value for advertisers

Built by marketers for marketers, GrowthLoop enables non-technical users to easily manipulate data and scale datasets as needed without the intervention of an IT or data team. This is key for a retail media network, whose sales and marketing teams can make available only the first-party customer data appropriate for each advertiser. That data can be as granular as individual attributes — from number of website visits to whether they opened an email — without the need for SQL or data science team support. 

In addition, GrowthLoop’s easy-to-use, no-code interface empowers marketers with drag-and-drop tools for journey orchestration, channel selection, campaign execution, and audience-building. Marketers can even build audiences using natural-language queries, then review, edit, and templatize them easily. 

With the GrowthLoop Compound Marketing Engine, advertisers will see a higher return on ad spend (ROAS) because they’re executing campaigns against audiences designed specifically for that brand’s goals. A high-performing retail media network that can prove its value to its partners — and prove it through platform-based analytics — attracts more brands and keeps existing advertisers loyal. 

The ascent of agentic AI 

To put the “loop” in the GrowthLoop Compound Marketing Engine — and accelerate the marketing cycle — the platform uses agentic AI alongside first-party data in the enterprise cloud. Agentic artificial intelligence operates in the background, analyzing first-party customer data in a retailer’s data cloud in real time. 

After automatically syncing customer interaction information and ad campaign performance data back into the data cloud, GrowthLoop suggests optimized RMN audiences and campaigns by refining the audience, journey, and channel strategy. AI agents then prompt the marketer with these recommendations, and with just a few clicks any marketer can adjust or accept, and then activate, these campaign improvements.

Combining first-party data with agentic AI supercharges the marketing and advertising cycle, letting marketers build audiences more accurately, launch journeys more quickly, get faster insights, and optimize campaigns continuously, so they perform better with each iteration. This accelerated iteration creates audiences with a higher propensity to convert and reduces work that once took weeks to mere hours. 

That makes GrowthLoop the most effective way to increase — and compound — growth for an RMN. Put another way, GrowthLoop is the engine behind compound marketing.

Cloud technology + compound marketing engine = accelerated growth x higher ROAS + ROI

The GrowthLoop compound marketing engine:

• Improves retail media network ROI by accelerating time to value through a straightforward integration with any preexisting data warehouse, rather than relying on manual data transfer from disparate systems that increase data storage costs.
• Keeps data compliant with privacy laws and regulations, enabling retailers to assemble and advertisers to activate first-party data without clumsy data transfers to and from third-party systems.
• Ensures scalability and flexibility through a self-service platform that enables retailers to serve more clients without involving IT or data teams that may slow down the process or add to operational costs.
• Puts marketers in control by enabling them to accept or reject solutions proposed by agentic AI before executing a campaign and build out retail media campaign strategies themselves through a no-code interface and natural-language queries that deepen product usage, further improving ROI.
• Attracts more advertisers by delivering AI-optimized audiences that improve ROAS and campaign efficiency.

Retail media networks are at a crossroads — will you choose the right path forward? Whether you’re looking for a way to maximize the value of your first-party data, evolve beyond the limitations of a manual or in-house solution, or in the market for an AI-enabled way to generate more ad revenue on your RMN, the GrowthLoop Compound Marketing Engine can power it. Sign up for our upcoming webinar on May 14 at 1pm ET to see a live demo and learn more