6 ways Data Clean Rooms enable effective ad campaigns with first-party data

With the phase-out of third-party cookies, digital advertising is set to change for good. And many brands are looking for ways to fill the gap that third-party cookies will leave behind — with first-party data. Some have already gathered and curated a wealth of information about their own customers that provide deep insights into individual customers’ behaviors and preferences.

But to use this sensitive data for ad campaigns, brands need to partner with publishers in a way that protects it — for customer privacy, for compliance, and to protect valuable information that’s proprietary to their company.

Data clean rooms (DCRs) are a compliant, secure method for brands to connect their data with publishers, retailers, or other data partners to build new insights for advertising. In DCRs built with confidential computing, brands can accomplish this without ever sharing the data itself.

What challenges can brands solve in practice with first-party data and clean rooms? We cover 6 concrete ways brands can use DCRS to plan media, activate audiences and measure ROI to deliver more effective campaigns in the third-party cookie-less era.

1. Create effective media plans

The days of automated cross-media planning may be over for the meantime with the phaseout of third-party cookies, but with a DCR, it’s still possible to discover high-value audiences and even create a reliable comparison of different channels with first-party data. Brands can securely match their customer data against a publisher — or multiple publishers — in a DCR. The platform can return insights about audience overlap and top affinity segmentation to inform where to invest ad budgets best.

2. Run retargeting and exclusion on a publisher’s audience

Retargeting and exclusion are bread-and-butter tactics in advertising that are straightforward to accomplish in a DCR. Brands and publishers upload their respective encrypted datasets to the DCR with at least one matching identifier. The DCR matches the datasets to identify the overlap, and exports audience segments for activation or exclusion. Note that because retargeting and exclusion involve targeting individual users, explicit marketing consent is needed for this use case. For this reason, campaign reach is likely to be small. That’s why at Decentriq, we’ve developed additional privacy-safe activation mechanisms that reduce consent requirements — keep reading to find out more.

3. Activate lookalike audiences in a publisher’s audience

A few DCRs, like Decentriq, are flexible enough for brands to build and activate privacy-preserving lookalike audiences. In this case, the data clean room uses a machine learning model to compare a brand’s customers with a publisher’s readers, identifying traits that signify the reader has a high similarity, or affinity, to the brand’s most valuable customers. Brands receive information about match rates and high-value segments. They can then adjust the size of the audience extension, balancing precision vs. reach depending on the campaign goal. Note that because no personal information from the brand is shared with the publisher (only a model is being trained), this activation mechanism offers the massive advantage of not requiring explicit marketing consent on the brand side.

4. Enrich target audiences with a brand partner

It’s also possible to enrich audience segments with the help of a second brand that has a complementary customer base. Two brands can combine their data securely in a data clean room and enrich the customer data with additional user attributes.

Brands can also augment their product recommendation models with insights they discover by pairing their user data with a partner’s. Through this collaboration, they can better understand which attributes lead a customer to repurchase or purchase a related product and use these next-best-product models for personalized ads, or cross- and upselling tactics.

5. Measure ROI and attribute conversions cross-channel

To measure the ROI of a campaign, brands define a conversion KPI, gather conversion data, and import the encrypted data into the data clean room. Publishers contribute ad impression data from the ad server. The data clean room then calculates the conversion rate and sends aggregated metrics back to the brand, allowing them to measure the effectiveness of a campaign without third-party cookies. If the brand collaborates with multiple publishers, they can use this technique to achieve cross-channel attribution.

6. Unlock second-party data from your partner retailers

CPG and FMCG brands are often low on first-party data because their partner retailers are intermediaries in the customer relationship. Data clean rooms can be an instrumental tool to help them leverage the retailer’s first-party data to achieve all the use cases described above, from consumer market insights to activation and measurement. Data clean rooms enable retailers to participate in clean rooms on behalf of their partner brands. Confidential computing-based clean rooms are even more relevant in this kind of collaboration as they allow retailers to maintain strict control and ownership of their data.

The end of third-party cookies is bringing an onslaught of new challenges to marketers, but data clean rooms can be more than just a tool to solve one or two. A data clean room that offers flexibility for data analysis, ID matching, and integrations can become a strategic component in your adtech stack to future-proof your data strategy.

If you’re interested in learning more about how data clean rooms can improve your marketing and ad effectiveness in a cookie-less world, feel free to get in touch with us.

This is an updated and expanded version of an article with the same title previously published on the Decentriq blog.