From carts to clicks: Why clean rooms unlock the future of Retail Media

<div class="insights_cta-component">This is the second article in our series covering Retail Media. See the full series below.</div>

We've all heard the buzz – retail media networks (RMNs) are exploding in popularity. But what exactly makes them so attractive to advertisers compared to traditional advertising channels? Often, the advantages include superior audience targeting and the ability to precisely measure campaign effectiveness. But how exactly do RMNs achieve these benefits?

Delving deeper: Precision targeting and measurable results

This is where things get interesting. While RMNs offer extraordinary advantages, it's important to understand how they operate. One key aspect is the concept of "walled gardens." These are closed ecosystems where data remains within the network and its trusted partners, offering a unique environment for targeting and measurement.

Here's how walled gardens work:

• Target's Roundel works with Google's ad network. This lets them offer advertisers access to Google search ads alongside their own targeted campaigns.

• Walmart Connect doesn't have a similar partnership with Google, so they can't offer those search ads.

• Kroger has teamed up with Disney+ and Roku, allowing advertisers to target viewers on those streaming services through Kroger's platform.

• Amazon, on the other hand, has its own streaming platforms like Prime Video, so advertisers can reach viewers directly through Amazon.

Since many retailers keep their data within their walled gardens, advertisers need to carefully choose which RMNs to partner with in order to reach their target audience effectively.

So, how do RMNs overcome the challenge of a cookie-less future while enabling these valuable benefits? The answer lies in “data clean rooms.” Let’s explore those next.

Cracking the code: Data clean rooms and the future of RMNs

Data clean rooms function as secure environments where anonymized user-level data from various sources is aggregated, compared, and analyzed. This allows retailers and their partners to collaborate on data-driven insights while adhering to privacy regulations and safeguarding consumer data. This technology underpins RMNs, enabling the responsible use of customer data for targeted advertising and effective measurement.

It's important to note that data availability within clean rooms hinges on agreements between partners. Industry leaders like The Trade Desk advocate for a more open network, championing the implementation of UID2 identifiers across clean rooms.

UID2 here refers to Unified ID 2.0, a framework developed by The Trade Desk, which aims to provide an alternative approach to tracking users' online activities in a more privacy-conscious manner. UID2 generates pseudonymous identifiers for users, allowing advertisers and platforms to recognize and target them across different websites and platforms without directly accessing their personal information.

UID2 identifiers are implemented across cleanrooms, which are secure environments for analyzing aggregated and anonymized user-level data. By incorporating UID2 identifiers into cleanrooms, advertisers can activate their campaigns against this data while maintaining privacy compliance and safeguarding user information.

For example, if a platform like Disney+ participates in UID2, advertisers using The Trade Desk can target audiences on Disney+ without accessing individual users' personal data. This means that advertisers can reach relevant audiences without compromising user privacy, as the identifiers used are pseudonymous and do not directly identify individuals.

However, some data owners remain hesitant about UID2 integration due to privacy and ownership concerns. As a result, walled gardens persist for now.

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Beyond the walls: How clean rooms unlock powerful targeting

Data clean rooms empower advertisers to leverage matched data across platforms for on-platform and off-platform targeting. This unlocks the ability to identify overlapping audiences and target them based on actual purchase history and behavioural data.

What’s more, the aggregate analysis of clean room data facilitates a range of targeting strategies:

• Audience segmentation: Segmenting audiences based on real purchasing habits and behaviours, such as lapsed buyers, high-value customers, or those who haven't purchased before. You can also target those who buy from competitors or complementary products.

• Lookalike modelling: Matching anonymized customer profiles with anonymized profiles within the retailer's or partnered platform's database. This helps identify potential customers with characteristics similar to your existing ones.

• Profile enrichment: Enhancing existing customer data with insights from third parties, providing a deeper understanding of your audience with data points that were previously unavailable.

Consider this real-world example: In 2022, amidst a nationwide baby formula shortage compounded by substantial recalls, Reckitt Nutrition sought to reassure parents about the safety and availability of their Enfamil brand. Their goals were clear: raise awareness, attract new buyers, and drive in-store sales at Walmart.

To achieve these objectives, Reckitt collaborated with Walmart Connect, leveraging Walmart's extensive first-party shopper data to execute a precise and impactful off-platform connected TV (CTV) campaign. The campaign, facilitated through Walmart DSP, aimed to deliver targeted messaging to audiences of new parents, nurturing healthy results.

The results speak for themselves:

• Total impressions reached 10 million, engaging 4.3 million unique viewers.

• Remarkably, 48% of viewers were new buyers, while 27% were loyalists who had purchased Enfamil products multiple times in the previous year.

• The return on advertising spend (ROAS) surpassed benchmarks, achieving a remarkable $10.97, exceeding expectations by 7X.

In response to the crisis, Enfamil capitalized on the opportunity to connect with customers seeking safe formula options. Although traditional linear TV ads were not their norm, leveraging Walmart DSP and CTV solutions enabled Enfamil to not only effectively target and engage the right audience at the right moment but also track the campaign's impact on sales at Walmart, providing valuable insights for future strategies.

The targeting toolbox: Strategies activated in clean rooms

RMNs can match shopper and user data between retailers and off-platform touchpoints at the user level within data clean rooms. This enables the analysis of the overlap between ad impressions and conversions, allowing for the reconstruction of complete customer journeys to inform attribution models.

Imagine a sports drink brand, XYZ Sports, targeting John, a Walmart shopper who uses TikTok and watches Roku TV. John's Walmart shopping data indicates his interest in sports drinks, prompting XYZ Sports to target him with ads:

• A TikTok ad for XYZ Sports

• An ad for XYZ Sports on Roku

• A coupon for XYZ Sports displayed on his Walmart app homepage

John then purchases XYZ Sports in-store using the app discount. Since users like John can be identified across touchpoints within the RMN, brands can execute closed-loop measurement, tracing the journey from the initial ad to conversion, evaluating ad performance, and calculating actual return on ad spend (ROAS).

Full circle: Closing the loop on measurement with RMNs

Closed-loop measurement unlocks deeper insights into buyer behaviour. In the aforementioned Walmart example, Reckitt gained valuable metrics beyond ROAS, such as:

• The number of new customers acquired

• Customer repeat purchase behaviour

Furthermore, by employing control groups alongside test groups, RMNs can account for incrementality and pinpoint the incremental sales and ROAS generated by a campaign. These benefits of RMNs directly contribute to further analyses like Media Mix Modelling.

While walled gardens present a hurdle, RMNs already offer significant advantages for advertisers. As data clean rooms evolve and privacy-focused solutions like UID2 gain traction, walled gardens may loosen their grip which in turn will open doors for even more granular audience targeting and seamless campaign measurement across platforms.

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NEXT UP IN THIS ARTICLE SERIES

We have learned a lot through helping our clients over the years, and we’ll be sharing our key insights with you in a number of articles – see below the list of topics this series covers:

• From shelves to screens: How Retail Media transformed marketing for CPGs

Stay tuned!

We hope you’re as excited as we are and please let us know if you have specific topics or questions you would like us to share with you.

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