Third-party cookies are disappearing–but your customer data isn’t. Loyalty apps, websites, in-store WiFi—there are lots of ways to still collect this value data. And one of the best things you can do with it is transform it into a revenue engine. The companies that do this are more likely to grow. Two proven models—data co-ops and media networks (MNs)—can get you there.

A data co-op is a group of organizations that pool their customer data for each other’s benefit, while a media network is an entire advertising platform that one organization owns. Each model has its own advantages and challenges. It’s not an either/or decision: Data co-ops and MNs are geared toward different goals and key performance indicators (KPIs), and some companies may incorporate both models into their strategy. Which one is right for you?

Primary goal

Data co-op: You want to expand reach and brand awareness by sharing anonymized customer data

Media network: Drive measurable sales and create a high-margin revenue stream through targeted advertising

How it works

Data co-op: Members securely share privacy-protected first-party data in a data clean room to identify overlapping audiences and insights

Media network: Company-owned advertising platform uses first-party data (and sometimes second- and third-party data) to target likely customers and measure conversions

Best for

Data co-op: Brands or suppliers selling through shared retail or digital channels; endemic partners

Media network: Suppliers aiming to boost sales through a specific retailer, brand, or partner; ideal for closed-loop measurement

Example

Data co-op: A hotel chain and an airline share anonymized guest and flyer data to cross-promote offers

Media network: A cosmetics brand advertises on a retailer’s website, app, and paid channels, measuring direct sales lift from the campaign

Complexity to build

Data co-op: Lower – typically subscription-based and less tech-intensive

Media network: Higher – requires tech integration, ad operations, analytics and change management

Revenue potential

Data co-op: Modest, steady recurring revenue

Media network: High

Key KPIs

Data co-op: Customer awareness, reach, new customer acquisition, sales lift from targeted campaigns

Media network: Incrementality (sales directly tied to ad exposure), campaign ROI, partner revenue growth

Time to value

Data co-op: Shorter – can be stood up quickly with the right data governance in place

Media network: Longer – often takes years to scale and maximize revenue

Investment required

Data co-op: Lower – mainly data governance and platform subscription costs

Media network: Higher – significant upfront investment in tech, talent, and partner onboarding

Data co-ops are the digital equivalent of marketing co-ops. While marketing co-ops share advertising costs, such as a perfume TV spot ending with “Available at Retailer A,” data co-ops share first-party customer data that’s been stripped of personally identifiable information (PII) in a data clean room. Artificial intelligence (AI) can turbocharge this process and enable co-ops to identify deeper insights from combined datasets. Ultimately, this means that members can better target their market and improve KPIs like customer awareness, reach and acquisition.

The company that operates the co-op typically charges a subscription fee to other members, helping to convert customer data storage from something that costs them money to something that generates it. What members pay and how they allocate revenue varies.

Membership in a data co-op will appeal most to brands and suppliers that sell through shared stores or digital properties, so-called endemic companies. These companies are focused on KPIs like awareness, reach and new customer acquisition. Sometimes they are also looking for a sales lift, for example, by identifying lapsed buyers of a particular product to target in an email campaign.

MNs can be far more lucrative than data co-ops, though they are also more challenging to build. A MN is a company owned advertising platform that uses the company’s privacy-protected first-party data (and sometimes second- and third party data) to identify advertisers’ likely customers and give them near real-time insights about how a campaign is performing. Brands monetize their first-party audience data by allowing advertisers to deliver more targeted advertising through external channels.  

Although commonly referred to as retail media networks (RMNs), they aren't only for retailers–any business with a cache of customer data can use it to open up a new revenue stream. Organizations are pouring billions into building their MNs––eMarketer predicts  that MN ad spending in the United States will swell 88.5 percent between 2024 and 2028, reaching $97.91 billion. 

Think of the MN as the digital equivalent of physical marketing displays, like endcaps, tent pole events and shelf tags. Ads appear on owned channels—such as the MN operator’s websites, apps, in-store kiosks and check-out terminals—as well as paid channels, like Meta. A major retailer we worked with earns nearly half of its RMN revenues from paid channels. By one estimate, the retail media market will grow reach $100 billion in 2027.

Where companies join data co-ops to expand reach and awareness, they advertise on MNs to drive incrementality. What does that mean? Advertising in a targeted way to encourage consumers to make one more purchase that they wouldn’t otherwise have made. But to measure this, they need to directly tie the purchase to the ad through data and tracking. MN advertising is most valuable for suppliers looking to boost sales through a specific partner: the company that operates the MN.

Data co-ops and MNs don’t have to compete––they are complementary. By building both, you could position yourself to earn revenue from companies looking to expand their reach and awareness through data co-ops, as well as drive incrementality through MNs. While significantly more complicated and costly to build, MNs have the potential to bring in exponentially more revenue—20 times more for one major retailer. Where a company decides to start depends on its appetite for technology integration and change management, senior leadership’s commitment and cost considerations.

How organizations design and manage their offering will have an enduring impact on their competitive advantage, costs and lifetime revenues. Use the following best practices to build a successful data co-op or MN, no matter your industry.

At the outset, it’s important to ensure that executives and all affected departments understand the value of the data co-op or MN to the organization and to individual departments, as well as how processes will change. Get buy-in from the heads of digital marketing, data and analytics, MarTech, owned experiences, digital advertising and digital transformation. Organizational alignment is crucial. For example, merchandising teams that have offered free digital advertising as a deal sweetener to suppliers who purchase physical marketing displays need to understand the value of the MN to the company, which ultimately benefits their team.

Whether starting with a data co-op or MN, set expectations with all stakeholders that revenues may take several years to reach their full potential. For example, a RMN that we built for a major U.S. retailer brought in $24 million in revenue in its first year, which grew to $150 million by the fourth year—a 625 percent increase. In general, MNs require a significantly larger investment than data co-ops and bring in more revenue potential. Another Publicis Sapient client saw $5 million in year-one revenues from its data co-op and $100 million from its MN.

Data is like crude oil in that it needs to be discovered, extracted and refined before it’s taken to market. Whether starting with a data co-op or MN, organizations should invest in data modernization to improve data quality, adopting best practices for extract, transform and load (ETL) processes.  This involves bringing in data from various sources, including the loyalty app, website, in-store transactions and actions taken in response to ad impressions. Identity resolution software enables this while also stripping PII from customer data to comply with privacy requirements.

In addition, the following success factors are important to consider specifically for MNs:

With advertising options ranging from Google Ads to social media, why would brands and suppliers spend their ad budget on a particular MN? In a word, incrementality—metrics showing whether an ad impression seen by a customer directly resulted in the desired conversion action and how much of the sale is a result of the ad. Advertisers can benefit from a centralized planning portal for audience targeting and reporting, such as our Retail Media Network Accelerator. Advertisers can use the portal to identify their target audience, such as lapsed buyers or households with two children under 18 and a certain income. They can also conveniently generate performance reports that compare conversions for different audiences, messages, calls to action and more.

Many of today’s MNs give advertisers a 30-day lookback window. But attributing a customer’s latte purchase to an ad seen 30 days earlier is a stretch. Similarly, data syndicates typically report on sales lift four to eight weeks after the campaign’s end, too late for advertisers to apply insights. To set MNs apart, businesses should design them to support a shorter—and therefore more relevant—attribution lookback window.

Imagine a campaign aimed at successfully reactivating lapsed buyers of a chocolate bar brand. With real-time incrementality measurements, the marketer can run experiments to see if reactivated customers will continue purchasing the item without the need for additional discount offers.

A successful data co-op or MN requires the right technology and the right processes.  While some companies may already have digital media teams with the necessary skills and scale, others may need to work with an experienced IT services provider that offers a build-operate-transfer service. With this arrangement, the partner sets up, optimizes and runs the media network for a set period of time while the company’s team learns, and then transfers over operations.

Reach out today to discover the transformative power of data co-ops or MNs and how Publicis Sapient supports businesses on every step of their journey.