Anyone who’s ever picked up a controller knows: single-player can be fun. You can beat the game, explore the world, and complete the missions. But it’s when you switch to multiplayer that the experience really comes alive. Suddenly, you’re strategizing, competing, and unlocking new levels of excitement that just aren’t possible alone.

The same is true with data collaboration.

One-to-one collaborations can be incredibly valuable. But it’s when multiple parties come together that the real magic happens. For CMOs, this distinction isn’t trivial. It’s the difference between data collaboration that delivers incremental gains and technology that fundamentally reshapes how marketing works.

If your data collaboration technology doesn’t allow for seamless multi-party collaboration, it’s flawed by design.

Level 1: Ready player one

Every CMO understands the power of first-party data. A brand working directly with a media owner can achieve something very effective. For example, using your customer data to reconnect with lapsed customers across a media owner’s authenticated audience. Or suppressing existing customers from the audience to acquire new customers. 

Data clean rooms have delivered on this use case, providing a significant step up from traditional targeting. It’s more precise, measurable, and, with the right technology, more privacy-safe. But it’s still just two players.

Think of it like a co-op campaign with a friend. It’s richer than going solo, but you’re still limited by the capabilities of just two characters. You can’t unlock the bigger world.

And this is where many data collaboration technologies fall short. They’re architected for a series of isolated, one-to-one collaborations. Valuable, but fundamentally limited.

Level 2: Another player has joined the party

The real power of data collaboration starts to emerge when you move beyond two players and add additional parties. Each new participant brings unique data, perspective, and capabilities. This multifaceted understanding of the customer transforms what was once a simple collaboration into something far more strategic and effective.

For example, imagine bringing a retailer into the previous collaboration. Suddenly, you’re not just targeting authenticated audiences, you’re enriching that targeting with shopper data. You can understand not just who the customer is, but what they buy, how often, and where.

For a CPG brand, that’s like unlocking rare loot. It turns a good collaboration into a great one. Empowering you to boost targeting relevance, refine creative, and unlock the ability to measure real-world sales outcomes.

It’s like adding a new teammate to your party. Suddenly, the strategy becomes more dynamic. Each player brings something different, and together you’re much stronger than the sum of your parts.

This is why multi-party collaboration isn’t just “nice to have.” It directly drives the CMO metrics that matter: return on ad spend, sales lift, brand loyalty, and long-term growth.

Level 3: Expanding the party further

The real excitement of data collaboration happens when you continue to expand the party. Each new player brings their own unique skills, insights, and perspective, creating a collaboration that becomes exponentially more powerful.

A travel company could introduce booking data that reveals when customers are planning trips, their preferred destinations, and whether they’re traveling solo or as a family. That opens the door for brands to activate at high-intent moments. Think sunscreen before summer holidays, luggage ahead of peak seasons, or financial services tailored to frequent travelers.

A sports rights holder could contribute fan engagement data, including ticket purchases, streaming subscriptions, and merchandise sales. This allows brands to tap into one of the most passionate, loyal audiences in the world, and tailor activations and sponsorships that resonate at precisely the right time.

A gaming platform could layer in engagement and community insights. For example, the types of games people play, their level of activity, or the kinds of digital items they purchase. That unlocks new ways for brands to authentically connect with gaming audiences and tailor creative to reflect real behaviors.

Each new collaborator adds something unique, just like expanding your raid party in a role-playing game. The more diverse the team, the greater the advantage. And for CMOs, that means unlocking scale, precision, and innovation that a one-to-one collaboration simply can’t deliver.

Boss Level: The open world

The ultimate evolution of data collaboration isn’t just about stringing together one-off partnerships. It’s about creating ongoing ecosystems where multiple companies can collaborate safely, repeatedly, and at scale. In these networks, every participant retains full control of their data while contributing to a shared effort. Success isn’t extracted by one player at the expense of another; it’s multiplied across all. Each collaborator benefits, trust is strengthened, and the ecosystem as a whole becomes more valuable with every new connection.

That’s the promise of Private Data Networks.

In a Private Data Network, your brand, media partners, retail partners, and data providers can all connect without ever centralizing or commingling their data. Privacy is preserved, but the possibilities for collaboration are unlimited.

It’s like stepping into a persistent online world. New players can join, new quests (or use cases) can be unlocked, and the collaboration doesn’t end when one campaign wraps.

For CMOs, this is where the biggest strategic advantage lies. Private Data Networks create:

• Sustainable competitive advantage: Your ecosystem becomes a moat that rivals can’t easily replicate.
• Future-proof strategies: You’re not reliant on fragile identifiers or third-party cookies.
• Scalable intelligence: Each collaboration adds more insight, intelligence, and opportunity.

The hidden final level

Occasionally, you’ll think you have beaten the final boss, completed all levels, and unlocked all achievements. Then you discover a final hidden level. 

Once a Private Data Network is established, the next frontier is using AI to model on top of it. It’s like unlocking New Game+: you keep everything you’ve built, but now you play with enhanced abilities, tougher challenges, and bigger rewards.

Suddenly, instead of just looking at what has happened, you can predict what will happen. You can anticipate customer behavior, simulate outcomes, and optimize campaigns before they launch. It’s like revealing the full game map in advance; seeing not just where you’ve been, but every path that lies ahead.

This is where collaboration evolves into collective intelligence. And it’s the foundation of Open Intelligence at WPP. Transforming data networks into living, learning ecosystems that fuel the next era of marketing performance.

Why one-to-one technology is flawed by design

This is the critical takeaway for CMOs evaluating data collaboration technologies: If a platform only enables one-to-one collaboration, it locks you into isolated, limited use cases. It can’t scale with your ambition. And it won’t create the kind of network effects that drive exponential value.

In other words, it’s like buying a console that only plays single-player games. Fine for a while, but you’re missing out on the bigger world.

The reality is that the marketing ecosystem is inherently multi-party. Brands, retailers, media owners, data providers, agencies, and platforms all need to collaborate. Your technology has to reflect that reality, or it will become a bottleneck.