What is an identity graph?
An identity graph is a data infrastructure that connects and unifies information about individuals across multiple devices, channels, and identifiers—such as emails, cookies, phone numbers, and device IDs—to create a single, accurate customer profile.
How does an identity graph work?
Identity graphs ingest and match data from various sources—both online and offline—to create a single profile at the individual or household level. For example, Fluent’s identity graph uses 200M+ first-party profiles and enhances them with Experian’s identity data (spanning 2.75B IDs and 250M individuals), combining behavioral, transactional, and intent signals. AI and machine learning then power segmentation, targeting, and personalization in real-time.
Types of identity graphs:
Identity graphs vary in how they resolve and link customer data.
How to measure an identity graph:
The effectiveness of an identity graph is measured by how accurately and comprehensively it can identify, connect, and activate customer data.
Why is an identity graph important to marketers?
Identity graphs power personalization at scale—helping marketers understand who their customers are, what they want, and how to engage them. For commerce media, this means better targeting, increased ad relevance, and stronger revenue impact. Fluent’s graph enables smarter post-transaction offers and audience segmentation, improving both customer experience and partner ROI.
Who needs to know about identity graphs:
Anyone responsible for driving personalized experiences, optimizing media performance, or unlocking deeper audience insights should understand how identity graphs work and what they enable.
Use identity graph in a sentence:
By integrating Experian’s identity data into its proprietary system, Fluent’s identity graph enables brands to deliver highly personalized, high-performing offers that convert.