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.”
- 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”).
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:- Zero-party: “How did you first hear about us?” (discovery/awareness)
- UTM last-click: the last tracked touch before purchase (conversion)
- MTA: credit across multiple touchpoints in the journey (multi-touch)
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.
Related resources
Survey Best Practices (HDYHAU)
How to design and deploy an effective post-purchase survey.
Post-Purchase Survey Module
How zero-party attribution appears in SourceMedium reporting.
Fairing Integration
Set up Fairing for automated survey collection and order tagging.
KnoCommerce Integration
Set up KnoCommerce for zero-party data collection and attribution.
First-Party Attribution
How tracking-based signals complement self-reported discovery.

