Blog

Sep 01, 2023

Make Your Customer Data More Accessible, Actionable and Addressable

The future of addressability is about more than replacing third-party cookies and restricted device IDs. The future is about buyers and sellers finding contemporary ways to identify and reach desired

The future of addressability is about more than replacing third-party cookies and restricted device IDs. The future is about buyers and sellers finding contemporary ways to identify and reach desired audiences.

With the right tools, marketers can enrich data in ways that respect privacy requirements, build trust and enable effective cross-media audience targeting.

The identity narrative is shifting from signal loss to signal enrichment, as the industry adapts to new ways of leveraging data. First-party contextual and behavioral data are key addressability pillars that can be coupled with third-party data to improve efficacy.

Beyond the broad categories of contextual and behavioral data, each platform features specific data types. CTV, for example, features robust registration data, viewership data and signals that highlight content viewing patterns. To create utility from data across media, the industry requires the tools and technology to collect, enrich and activate data. These tools are available as standalone capabilities or packaged together in state-of-the-art data management platforms (DMPs).

In recent years, DMPs have gained adoption as a key instrument for orchestrating first-party data. AI is propelling DMPs to another level. Take data classification as an example. Previously, publishers and DMPs manually managed content categorization to build audiences. DMPs now leverage AI to automate the extraction and categorization of contextual signals in real time. This enables publishers to quickly identify contextual monetization opportunities which deliver a more robust foundation for data enrichment and modeling.

Beyond automating contextual categorization, publishers now tap automated ways to access user behaviors, interests, and brand affinities and highlight valuable audiences in real time. For example, AI might surface an audience of luxury coffee lovers to a publisher based on users’ engagement with articles such as “Top 10 Coffee Beans” or “Finding the Best Coffee Machine for You,” combined with high-income level demographic signals.

Another technique gaining momentum to organize first-party data is data matching (often performed in a clean room-like environment). Also known as a privacy-enhancing technology (PET), publishers and brands now use scaled and encrypted offline data matching to onboard and match identifiers such as emails and phone numbers without the need for a third party in the middle or the raw data leaving the owner’s servers.

Running registration data through PET enables 1:1 targeting between buyers and sellers without identifying the actual users with raw data. PET helps publishers and advertisers maximize value and minimize data leakage risk, because this encryption takes place where the data resides while also making it actionable.

In the real world, a fast-food brand might look to target customers on streaming platforms with a new meal to accompany the latest bingeable show. The streamer’s encrypted registration data is matched to the fast-food brand’s encrypted email list to present a relevant advertisement to the target customers.

Or imagine a skincare brand with a rewards app seeking to advertise other beauty products to its customers. The skincare brand matches its encrypted email list to a streamer’s encrypted registration data to generate an ID to run targeted video ads on a fashion-related TV program. Similarly, the skincare brand matches its encrypted email list to a lifestyle magazine website’s encrypted user logins to run targeted display ads.

Data matching creates actionable data opportunities by helping advertisers with customer data work directly with media owners. Using data matching tech with built-in activation paths, publishers attach matched data to an ad opportunity and present it directly to a buyer in real time without exposing the raw personal data.

According to Nielsen’s 2023 Annual Marketing Report, only 23% of marketers strongly agree that they have the quality audience data needed to get the most out of their media budgets. This suggests a significant lack of high-quality data required to drive improved campaign performance.

Across media, marketers need simple and flexible methods of making data available for forecasting and measurement, segmentation and audience activation. DMPs make it easy for sellers to leverage their first-party audiences to fuel their direct and programmatic businesses or make those audiences available as third-party segments to scale others’ campaigns.

DMPs that are tightly integrated into supply offer the most efficient and effective data activations. Those DMPs that are closely coupled with supply offer the closest connection to running media, retaining audience activation in a world where third-party identifiers are going away. An added benefit to this connection is that it also saves time when launching and optimizing campaigns.

As marketers enter the signal enrichment era, making data more accessible, actionable and addressable is critical. There’s no one answer to the addressability challenge. Marketers must adopt a portfolio of solutions for enriching data to apply data where required.

By embracing DMPs and PET with AI-driven innovation, there is a clear path forward to ensure the industry is well prepared when third-party cookies and other restricted device IDs are no longer available. This new path is built by enriching more quality and reliable signals to continue addressing audiences precisely and at scale. By ensuring interoperability and aligning tools close to activation paths, the media ecosystem will thrive.

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As Magnite’s chief product officer, Adam Soroca is responsible for the company’s strategic product direction, product roadmap and go-to-market initiatives.