Drive Your Retail Media Strategy with Data Clean Rooms 

Retail media is the topic everyone is talking about in the retail and consumer goods industry. And for good reason: the $45 billion U.S. retail media market is surging as retailers capitalize on the consumer shift to ecommerce while offering advertisers access to their unique audiences and data insights. Many retailers developed their own retail media networks over the last few years, from digital marketplaces and department stores to commerce intermediaries.

This trend will continue to grow as retailers look to monetize their rich first-party data and capitalize on companies’ interest in advertising in places where consumers are already interacting with the brand. The goal is to meet consumers where they are with curated advertisements tied to their purchase intent and behavior. For more on retail media and how retailers, brands and advertisers are benefiting from it, check out our “How Leaders Use Retail Media to Drive Profit” ebook.

What’s behind the retail media surge?

So, how did we get here? It all started with cookies

When you visit a brand’s website, the company drops a first-party cookie that allows the site to remember important user information, such as items you add to your cart, username and passwords, and language preferences. This information falls under the brand’s domain and privacy policies. First-party cookies are necessary for the website’s performance as well as the user experience; therefore, they always remain active.

At the same time, there are third-party services that drop third-party cookies on the brand’s website for the purposes of cross-site tracking, retargeting and serving personalized ads and content.

While this additional information is a great resource for advertisers, consumers grew wary about how cookie data was being collected, used and protected. Consumer privacy became the focus, and browser vendors responded: Apple began blocking third-party cookies with Apple Safari ITP 2.0 in 2018, Firefox blocked third-party cookies by default with Firefox ETP in 2019, and Google first announced blocking of third-party cookies on Chrome in 2019. Now we have GDPR and CCPA regulations around cookie transparency, opt-in requirements and data privacy, and it’s clear that privacy protection will remain at the forefront of future cookie conversations.

To sum it up, the third-party cookie signal is deteriorating as consumer privacy concerns and regulations increase. At this point, we’re all just waiting for the day when Google fully blocks third-party cookies on Chrome and closes the book on an interesting era of advertising. 

Hence, the growing importance of first-party data as a retail media resource. 

Retail media networks fill the gap for advertisers

Despite the forthcoming third-party cookie-pocalypse, the pressure to measure advertising outcomes is not subsiding—if anything, it’s growing stronger. So retail companies are standing up retail media networks that leverage their rich first-party data. 

A retail media network is a unified ecosystem set up by a retailer to let brands advertise on their website, app, email distribution and other digital properties. A retailer can sell a variety of ad formats that allow advertisers to hit the shopper with the right message at every point of the buyer’s journey, from product consideration to the point of sale. 

To build a successful retail media network, a company has to be able to differentiate themselves by:

  • Identifying the unique audiences it can activate against
  • Delivering customer insights and measurement in a granular, transparent way that avoids walled gardens
  • Building for scale on a foundation of data privacy

Identity resolution: A retail media network must-have

Retailers must also consider identity resolution, which depends strongly on first-party data. Identity resolution is the ability to recognize an individual by connecting various identifiers from their offline and digital interactions. Ultimately, this allows retailers to build an identity spine and customer 360 view.

Identity data has two categories: pseudonymous and known. Pseudonymous IDs are de-identified and do not contain explicit personal data. Known IDs contain personally identifiable information (PII), which can be used to identify an individual.

Brands’ retail media strategy can include both types of IDs. They collect known data about their customers (including PII such as name, postal address and email addresses) through multiple opt-in channels such as loyalty programs and account creation. Known data can serve as metadata around customers’ purchasing history, affinities and buying intent. Brands also track their customers’ journeys in the digital world via pseudonymous identifiers such as first-party cookies.

Because identity resolution matches all of these identifiers across different touchpoints, retailers can capture the entire customer journey and create a richer customer profile. 

Creating a secure data collaboration environment

In advertising, whether it’s retail media networks or media, the ability to create overlaps between common identifiers sits at the heart of a data clean room, which aims to bring different parties and their data together without exposing PII (known data).

A data clean room can provide a secure environment that gives a brand the ability to plan, buy and measure their advertising investment and allows retailers to protect consumer PII. 

The Interactive Advertising Bureau (IAB) has a great representation of what this could look like:

Source: “How Retailers Are Using Data Clean Rooms,” by Jeffrey Bustos, April 5, 2023

Let’s dive deeper and understand how data clean rooms drive collaborative data partnerships for organizations. 

Data clean rooms facilitate retail media collaboration 

With increasing privacy regulations, the advertising and media industry is looking to embrace privacy enhancing technologies (PETs) to power the promise of activation, measurability and attribution of digital media. Data clean rooms are one of the most viable PETs. They serve as secure environments where companies can aggregate, analyze and model sensitive consumer data from multiple sources without compromising consumer privacy. 

In other words, data clean rooms enable secure collaboration around retail ecosystem use cases and across retailers, ecommerce platforms and CG/brands, without exposing sensitive customer data and without requiring companies to move their data. The following image shows a few of the many use cases that can benefit from using a data clean room to anchor a retail media network.

Data clean rooms can feel like an abstract concept because they involve so many considerations, from organizational alignment and data sources to the underlying tech stack and types of ad inventory. Companies also have to think about data ownership and partnership requirements, and the data clean room’s role as part of their advertiser collaboration strategy. 

In reality, data clean rooms are very much a tangible product. Here are four core foundational features that retailers should look for when evaluating the right data clean room to power their retail media network. 

Strong security paradigms: The less data moves, the less risk of breaches or leakage. A data clean room should not only minimize data movement, but also use strong security measures such as cryptography and MPC techniques to protect valuable first-party data. Keep an eye out for differential privacy and audience thresholding features, as well as abstraction of PII. 

A connected ecosystem: Your data clean room should be part of an existing workflow that includes:

  • Computation and warehousing: Taking compute to the cloud provider data source so that the data does not need to be copied and moved from that environment
  • Identity: The native support of identity providers that resolve 1P assets to an online identifier, at a consumer level, into the same or applicable spaces 
  • Enrichment: The enhancement of existing 1P data assets with additional audience and demographic attributes  
  • Activation: A connection to downstream workflows to activate overlapped audiences for activation 
  • Interoperability: Interoperability across various cloud and data clean rooms to view unified reach

Insights-oriented results: Data clean rooms can solve complex, long-standing media issues, such as multi-touch attribution (MTA), interoperability and so on.

User-friendly experience: Standing up a DCR can be complex but having a UI orchestration layer can make the process easier, especially for non-technical employees.

Summing it up

With new privacy policies changing how data can be used in the advertising ecosystem and the loss of consumer signals in web browsers, the advertising data landscape is going through a paradigm shift. Retailers are now in a unique position: they can take advantage of their user profiles and provide incredibly relevant and actionable targeting for brands in various product categories. The abundant supply of first-party consumer data means they can build advertising networks that can withstand competition from walled gardens.

That said, while scaling the business, retailers also need to protect their customer data by leveraging secure data collaboration. A data clean room securely provides the ability for brands to plan, buy and measure their advertising investment without the retailer exposing consumer PII.

If you’re interested in how data clean rooms support collaboration, check out the upcoming demo from Samooha and Snowflake on secure collaboration in advertising. And stay tuned for more on how to get started with your data clean room journey!

The post Drive Your Retail Media Strategy with Data Clean Rooms  appeared first on Snowflake.

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