Identity Resolution
Identity resolution links a user's many identifiers into a unified profile. This module covers deterministic vs probabilistic, the major identifiers, and the quality measurement that prevents bad personalization.
What you will learn
- Why identity resolution is the heart of a CDP
- Deterministic vs probabilistic matching
- Identity graphs and their construction
- Common identifiers and their reliability
- Cross-device matching
- Cross-domain matching
- Online-to-offline matching
- Privacy considerations
- Vendor identity solutions (LiveRamp, Tapad, etc.)
- Measuring identity-resolution quality
- Common identity-resolution mistakes
1. Why identity resolution
A user appears in dozens of systems with different identifiers: web cookies, mobile IDs, email, phone, customer-ID. Identity resolution links these into a unified persistent profile. Without it, every marketing system has a partial view of the customer.
2. Deterministic vs probabilistic
| Type | How it works | Accuracy |
|---|---|---|
| Deterministic | Exact match on known identifier (email, phone, customer-ID) | Very high when match exists |
| Probabilistic | Statistical match on signals (IP, device, behavior) | Moderate; declining due to privacy |
3. Identity graphs
An identity graph stores relationships between identifiers. Each node is an identifier; each edge is a confidence-scored relationship. The graph grows as new signals connect previously-disjoint identifiers.
4. Common identifiers
- Email (highly reliable, persistent).
- Phone (highly reliable, persistent).
- Customer-ID (most reliable for known customers).
- Device IDs (mobile MAID; reliability declining).
- First-party cookies (browser-specific, expire).
- Third-party cookies (deprecated).
- Login session.
- IP address (low-quality identifier, especially with mobile).
5. Cross-device
Linking a user's desktop, mobile web, and mobile app. Methods: login (most reliable), email collection, deterministic match via shared identifier, probabilistic via behavior/location.
6. Cross-domain
Linking the same user across multiple owned domains. Methods: first-party cookie + login, server-side identity stitching, third-party graph (LiveRamp).
7. Online-to-offline
Linking online identifiers to offline customer records. Methods: email/phone capture, in-store login, transaction matching, third-party graph providers.
8. Privacy
- Identity work concentrates PII; treat with appropriate security.
- Consent requirements vary by jurisdiction.
- Right-to-deletion must propagate across the identity graph.
- Hashing PII for vendor sharing.
9. Vendor solutions
- LiveRamp: The leading commercial identity graph.
- Tapad (Experian): Probabilistic device graph.
- Adobe Real-Time CDP: Adobe-native graph.
- Salesforce Data Cloud: Salesforce-native graph.
- Acxiom (IPG Mediabrands): Marketing identity graph.
- The Trade Desk Unified ID 2.0: Email-based open identity.
10. Measuring quality
- Match rate: percentage of records that resolve to a known profile.
- Match accuracy: confirmed correct matches vs total.
- Profile completeness: data points per profile.
- Recency: how current the linked identifiers are.
11. Common mistakes
Sources & further reading
- LiveRamp blog
- Experian Identity Resolution
- Unified ID 2.0
- Acxiom insights
- CDP Institute identity
- Segment identity
- mParticle identity
- Books: Martin Kihn & Chris O'Hara, Customer Data Platforms; Jed Williams, Identity Crisis
- IAB Identity Resolution
- Tealium AudienceStream
- Salesforce Identity Resolution
- TTD UID2.0
Part of the Customer Data Platforms series · RGM Training