An identity graph (also called an ID graph) is a database that connects all the different digital identifiers that belong to the same real person — email addresses, phone numbers, device IDs, cookies, IP addresses — into a single unified profile. It's the technology that makes cross-device personalization, visitor identification, and accurate attribution possible.
An identity graph (or ID graph) is a database that links multiple identifiers belonging to the same individual — including email addresses, phone numbers, device IDs, IP addresses, browser cookies, mobile advertising IDs, and physical addresses — into a single unified profile. The process of creating these links is called identity resolution. An identity graph enables companies to recognize the same person across different devices, channels, and touchpoints, even when that person has not explicitly identified themselves.
The core challenge an identity graph solves is fragmentation. A single person interacts with the digital world through dozens of different identifiers — their work email, personal email, home IP address, office IP address, iPhone, laptop, tablet, and browser on each device. From any individual data source's perspective, these appear to be many different people. An identity graph recognizes them as one.
Identity resolution works through two mechanisms: deterministic matching and probabilistic matching. Deterministic matching uses hard-linked identifiers — for example, if a person logs in with the same email address on two different devices, those devices are definitively linked to one person. Probabilistic matching uses statistical inference — if two devices share the same household IP address, have similar behavioral patterns, and access the same services, they're likely the same person with high confidence, even without a definitive link.
Large-scale identity graphs — like those maintained by major data companies, ad platforms, and visitor intelligence providers — are built by aggregating billions of deterministic and probabilistic links over time. Kopimore's identity graph, for example, contains links between IP addresses, device fingerprints, email addresses, and physical profiles for over 200 million U.S. consumers and businesses, enabling anonymous website visitors to be matched to real people in real time.
Without an identity graph, digital marketing is fundamentally anonymous. You can track that a user visited your pricing page on a Tuesday, but you don't know who they are, which company they work for, or whether they're the same person who attended your webinar last month. Every new touchpoint looks like a stranger.
An identity graph changes this in four ways. Personalization becomes possible at scale — you can show a returning visitor a different experience than a first-time visitor because you know who they are. Attribution becomes more accurate — you can see the full journey a prospect took across devices and channels before converting. Visitor identification becomes possible — an anonymous IP address can be matched to a real person with name, email, and phone. Audience building gets richer — you can target known high-value prospects on ad platforms using first-party identity data rather than probabilistic lookalike models.
Kopimore's visitor identification technology is built on a proprietary identity graph that links anonymous website visits to real people and companies. When a visitor lands on a Kopimore-instrumented website, the platform captures a set of signals — IP address, device fingerprint, browser characteristics — and runs them against an identity graph containing over 200 million U.S. consumer and business profiles.
For B2B visitors, the graph resolves IP addresses to company networks and then identifies the most likely individual contact based on job function, seniority, and behavioral signals. For B2C visitors, the graph matches device and IP signals against residential profiles to identify homeowners, consumers, and individual buyers. The result is a name, email address, phone number, and profile delivered to the Kopimore customer — transforming an anonymous pageview into an actionable sales lead without any form fill required.
Kopimore identifies your anonymous website visitors using its proprietary identity graph. Get Started and see your first identified visitors within 24 hours of setup.
Get Started → See How It WorksIf you're researching What Is an Identity Graph?, these neighboring concepts in our glossary often come up in the same conversations — particularly when teams are scoping a visitor intelligence implementation or comparing identity resolution approaches. Browse the related entries below to fill in any gaps in your mental model: Intent Signal, IP Address, Lead Identification, ICP (Ideal Customer Profile).
Looking for something else? The full Kopimore glossary covers every term in visitor intelligence, intent data, identity resolution, and CRM activation. If a term you expect is missingcontact our team — we publish new definitions weekly based on what customers ask about.