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In the 1980s, a popular TV commercial showed two consumers bumping into each other, one eating chocolate, the other peanut butter. Thanks to that mashup, the ad implies, Reese's Peanut Butter Cups were invented.

Of course, brands have never relied on serendipity to make strategic product decisions. Rather, they build data science teams that glean insights about customer tastes, their propensity to try a new product, and the best pathways (read: retailer partners) for selling. Sometimes they take a gamble, such as Hershey's decision to partner with Yuengling to offer chocolate porter, but it's never without methodical research.

The challenge for many manufacturers is that they rely on their network of retailers and media partners to get their products in the hands of the end customers, which means they don't have as much first-party data as they'd like.

Retailers and media companies have rich transaction and loyalty data assets that are incredibly valuable and highly coveted by CPG and other companies because they provide a view into consumer behavior that CPG companies are otherwise blind to.

Previously, retailers and media companies may have been hesitant to share data because of privacy concerns and lack of data control. However, new opportunities are opening up as data clean rooms empower companies to have full control over what data can be shared with whom, for how long, and for what purposes. That creates a whole new world of possibilities and mutually beneficial business growth for CPG companies, retailers, and media companies alike.

Many media companies and retailers are now setting up their own clean room environments similar to Google's and Amazon's clean room offerings (ADH and Amazon Marketing Cloud) so they can collaborate with their advertising partners. There's no reason CPG companies and manufacturers can't follow suit and create their own, as well.

The assumption we tend to make is that the party with the most data serves as the nexus—the one that other parties must come to. But that's not the case at all. Innovative CPG companies are setting up their own secure environments to maximize the opportunities of partners they can collaborate with and the use-cases they can achieve.

Where CPG Brands and Other Manufacturers Are Strong

Although many CPG companies are short on first-party customer data, they're famously long in analytics, including a range of propensity models—e.g., customers who purchase dairy alternative milk products are X% more likely to purchase nondairy frozen treats, and consumers who respond to digital ad campaigns for nondairy products are 3x more likely to seek out a retail outlet that carries them.

Those kinds of analytics are immensely valuable on their own, but they become even more powerful when combined with the manufacturer's retail transaction data and media partners' consumption data. Knowing which consumers will try new products based on purchasing habits helps the retailer boost foot traffic and basket size, just as knowing which readers or viewers to target for a media campaign leads to higher success and repeat business for the media company.

A mashup is in order. Collaboration will ensure that manufacturers will have greater control over their data destinies.

But how do they get there?

Getting to Data Collaboration

If you're not familiar with data clean rooms, here is a three-sentence overview: Clean rooms are tightly controlled environments in which multiple data sets—or one data set plus one set of algorithms, propensity models, or machine-learning—can come together for analysis purposes.

Disney recently launched its clean room solution, powered by Disney Select, which offers clients advanced preplanning insights, activation, and cross-portfolio measurement built with evolving data and privacy trends in mind. The CPG brand knows whom it wants to target, and Disney knows its audience. By inviting the CPG brand to combine its first-party data with Disney's audience data in tightly governed environments, everybody concerned benefits.

As I mentioned earlier, we intuitively see media companies and retailers as the nexus of such data applications because they own the data. But data isn't that useful in modern-day marketing and advertising without analytics.

So, what if CPG brands and manufacturers took the same approach as retailers and media companies by standing up their own data clean rooms and inviting their partners to collaborate?

Be the Space Where Partners Work With Data

Data collaboration is the art of the possible, and it's a huge opportunity to form more meaningful and mutually beneficial relationships with business partners. By deploying a solution of their own, CPG brands and manufacturers can create a secure environment to run their analytics on their partner's first-party data.

For instance, they can provide their retailer partners insight into whom they should target with a new product to prompt additional store visits and bigger basket sizes. They can also gain a better understanding of campaign effectiveness. Let's say I advertise a new breakfast cereal on USA Today. I can—without ever seeing any PII data—compare the consumers who saw my ad on USA Today, visited my website, and redeemed a coupon at a partner retailer.

Until recently, there hasn't been a responsible or safe way for retailers to share their first-party data or for manufacturers to use their analytics on a partner's data. Data clean rooms are now providing a privacy-centric mechanism for those data collaborations to occur more frequently, and to build strategic bridges between CPG brands and other manufacturers with their retail and media partners.

Some people say the deprecation of the third-party cookie will bring an end to data-driven growth. I see it as the spark for something new.

More Resources on Data Solutions

Three Must-Have Capabilities for Your Attribution Solution

CDPs, DMPs, CRMs... Oh My! Which Data Solution Is Right for You? (A Guide for Marketers)

How B2B Marketers Can Absorb and Apply Data Effectively: Six Questions Answered

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image of Matt Kilmartin

Matt Kilmartin is a co-founder and the CEO of Habu, a data clean room software company. He is passionate about entrepreneurship and developing technology to help brands in their digital transformation. He has held a variety of executive leadership roles at Salesforce, Krux, and Akamai.

LinkedIn: Matt Kilmartin