TLDR
- Dun & Bradstreet helps marketers target audiences by using AI and cloud-based data, as third-party cookies are being phased out.
- The company’s ID Graph Plus combines offline and online data for more precise, privacy-safe targeting.
- A composite identity links consumer and professional personas, enabling highly nuanced targeting.
With third-party cookies being phased out, marketers are scrambling for ways to maintain precise targeting while respecting consumer privacy. For Dun & Bradstreet, a nearly 200-year-old data and analytics company, the answer lies in a fusion of data, AI and cloud-based marketing infrastructure.
In an interview with The AI Innovator, Nate Carter, vice president of global sales, agency and identity at Dun & Bradstreet, explained how the company is reshaping business-to-business (B2B) marketing with its ID Graph Plus, to resolve digital identity without relying on cookies.
Traditionally, marketers leaned on spreadsheets, emails and pre-built audience segments like ‘IT decision makers’ to drive campaign targeting. Dun & Bradstreet’s new approach, Carter explained, skips the manual process by embedding their data assets into cloud environments such as Snowflake, Google BigQuery, and Databricks.
Instead of emailing spreadsheets to ad agencies, for example, “what we want to do is get this data and let brands start working with it more in that layer of cloud collaboration,” he said. Then, the thinking is “I’m going to build with these data assets. Here’s everyone who is a really good prospect for me.”
This integration effectively repositions the brand from a static data provider to a dynamic intelligence partner. Marketers can now analyze, model and deploy customized audience segments from within their own first-party ecosystems, turning marketing from a guessing game to a bull’s eye.
The rise of AI-driven identity profiles
Cookies were never meant to handle the complex task of delivering personalized B2B marketing at scale, Carter argued. They served a purpose but they were being stretched beyond their capabilities and there needed to be a better bridge between offline and online identities.
That bridge is built on fusing identities – combining Dun & Bradstreet’s longstanding business database with consumer household data. By anchoring marketing identity in offline records – like address files, warranty data and even vehicle registrations – then layering digital signals such as IP addresses and device IDs, the company offers marketers a 360-degree view of a prospect.
This composite identity links the consumer persona (say, a person who buys takeout and rents in Los Angeles) with the professional persona (a procurement officer at a logistics firm), enabling highly nuanced targeting. All of this is achieved, Carter noted, within privacy-safe environments using de-identified data and clean room technology.
AI makes it all work
While generative AI is getting the spotlight, Dun & Bradstreet is betting on machine learning and fuzzy logic in AI to power the backend of its identity engine. AI not only helps normalize massive data sets but also plays a central role in identifying patterns and continuously optimizing campaigns.
“Maybe you’re selling chocolate and you find out that on rainy days people buy more chocolate,” Carter said. Then on a rainy day, AI tells the marketer to reach out to chocolate buyers. “We’re seeing a lot of areas where AI can help in the decisioning process” by linking seemingly unrelated data points.
The company also uses AI internally to clean and enrich its datasets – ensuring accuracy and freshness across both its business contacts database and consumer file. The latter now covers 95% of U.S. adults, according to Carter, though he emphasized the company’s conservative stance on consumer data: no social media tracking, no credit card data, and only opt-in personally identifiable information (PII) when used.
Early traction has been strong in sectors like financial services and telecommunications.
Looking ahead, Carter sees data quality as Dun & Bradstreet’s key differentiator and AI as the critical tool for enhancing it. “Our future for the next decade plus is (to provide) more easily consumed data in AI-driven applications for customers,” he said.
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