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Zero-party attribution is attribution based on what customers explicitly tell you—most commonly via a post-purchase survey like “How did you hear about us?” (HDYHAU).
The term “zero-party data” was coined by Forrester Research: “data that a customer intentionally and proactively shares with a brand, including preference center data, purchase intentions, and personal context.”
This distinction is important:
  • First-party data is data you collect about a user’s behavior (observed intent - e.g., “User viewed Blue Shirt”).
  • Zero-party data is data the user tells you about themselves (explicit intent - e.g., “I am looking for a Blue Shirt”).
This complements tracking-based attribution by capturing discovery channels that are often hard to measure with cookies and pixels. As privacy restrictions reduce tracking reliability, zero-party data becomes increasingly valuable.

When zero-party attribution is most useful

Zero-party data is especially valuable for:
  • Word of mouth / referrals
  • Podcasts, radio, print, and other offline media
  • Influencers where click tracking is inconsistent
  • PR and partnerships

How it fits with UTMs and MTA

A simple way to think about the three layers:
  1. Zero-party: “How did you first hear about us?” (discovery/awareness)
  2. UTM last-click: the last tracked touch before purchase (conversion)
  3. MTA: credit across multiple touchpoints in the journey (multi-touch)
If surveys show meaningful revenue from a channel that tracking doesn’t capture, treat that as a measurement gap to investigate—not just a reporting difference.

Survey setup basics (high impact)

  • Prefer single-select answers for clean reporting, with an optional free-text “Other”.
  • Keep options mutually exclusive (avoid overlapping choices like “Instagram” and “Social”).
  • Use stable naming for options so historical reporting stays consistent.