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ID mapping connects different identifiers to the same user, enabling cross-device targeting, measurement, and analytics. When a data provider links a hashed email to a mobile advertising ID, or a cookie to a device identifier, they create an ID mapping that bridges previously siloed data.

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Why ID mapping matters

Modern consumers interact with brands across multiple touchpoints:
  • Mobile apps (identified by MAID)
  • Websites on desktop (identified by cookies)
  • Email communications (identified by email address)
  • Connected TV (identified by device graphs)
Without ID mapping, each touchpoint exists in isolation. A retailer might show the same ad to a customer on mobile, desktop, and CTV without recognizing it’s the same person—wasting budget and creating a poor experience. ID mapping solves this by creating links between identifiers, enabling:
  • Unified targeting: Reach the same person across devices
  • Frequency capping: Limit ad exposure across channels
  • Attribution: Connect conversions to the right touchpoints
  • Audience expansion: Find customers in new channels

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Common ID linkages

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Hashed Email to MAID

The most valuable and deterministic mapping connects hashed emails to mobile advertising IDs. How it works: When a user logs into a mobile app with their email address, the app developer can link the MAID (from the device) to the hashed email (from the login). This creates a deterministic, high-confidence link. Use cases:
  • Target email subscribers in mobile apps
  • Extend CRM audiences to mobile advertising
  • Measure mobile conversions against email campaigns
Connects web browsing behavior to mobile device identity. How it works:
  • Cookie syncing through pixel fires on mobile web
  • SDK-based matching when users interact on both web and app
  • Probabilistic matching based on shared signals (IP, location, behavior)
Use cases:
  • Retarget website visitors in mobile apps
  • Build unified user profiles across web and app
  • Measure cross-platform campaign performance
Links browser-based identity to email-based identity. How it works: When users log in on websites, the site can link their cookie to their hashed email. This creates a durable identifier that persists even when cookies are cleared. Use cases:
  • Build persistent identity across browser sessions
  • Connect anonymous browsing to known customers
  • Enable email-based audience activation

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ID mapping quality

Not all ID mappings are equal. Consider these quality factors:

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Deterministic vs. probabilistic

TypeDescriptionConfidence
DeterministicDirect observation of link (e.g., same user logged in)High
ProbabilisticInferred from signals (e.g., shared IP, similar behavior)Variable
Deterministic mappings are more accurate but harder to scale. Probabilistic mappings offer broader reach but may include false matches.

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Recency

ID mappings can become stale:
  • Users reset their MAIDs
  • Cookies expire or are cleared
  • Email addresses change
More recent mappings are generally more reliable.

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Source quality

The method of collection matters:
  • First-party login data: Highest quality
  • SDK integrations: High quality
  • Cookie syncing: Medium quality
  • Probabilistic inference: Variable quality

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ID mapping in Narrative

Narrative enables ID mapping through several mechanisms:

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Standardized identifiers

When ingesting data, Narrative normalizes identifier formats to enable matching across sources:
  • Consistent casing for MAIDs
  • Standardized hashing for emails and phones
  • Narrative Cookie IDs for cross-supplier cookie matching

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Cross-supplier matching

Different data suppliers use different cookie namespaces. Narrative creates a standardized cookie ID that links to each supplier’s cookies, enabling matching across suppliers.

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Query-time joining

Use NQL to join datasets on shared identifiers: 
SELECT
  a.hashed_email,
  b.maid
FROM company_a."email_data" a
JOIN company_b."maid_data" b
  ON a.narrative_id = b.narrative_id

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Privacy considerations

ID mapping must respect privacy regulations and user expectations:
  • Consent: Ensure mappings are created with appropriate user consent
  • Pseudonymization: Always hash PII before creating mappings
  • Data minimization: Only create mappings needed for specific use cases
  • User controls: Honor opt-outs across all linked identifiers

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Related content

Identifier Types

Categories of identifiers used in mapping

Data Onboarding

Connect offline data to online identifiers

UID2

Privacy-preserving universal identifier

Narrative ID

Secure cross-partner matching