> ## Documentation Index
> Fetch the complete documentation index at: https://docs.sourcemedium.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# What is zero-party attribution?

> Learn how customer-reported survey answers complement tracking-based attribution and how to use zero-party data in SourceMedium

**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)**.

<Note>
  The term "zero-party data" was coined by [Forrester Research](https://www.forrester.com/blogs/straight-from-the-source-collecting-zero-party-data-from-customers/): *"data that a customer intentionally and proactively shares with a brand, including preference center data, purchase intentions, and personal context."*
</Note>

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)

<Tip>
  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.
</Tip>

## 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

<CardGroup cols={2}>
  <Card title="Survey Best Practices (HDYHAU)" icon="square-poll-vertical" href="/help-center/faq/account-management-faqs/best-practices-in-setting-up-a-post-purchase-hdyhau-survey">
    How to design and deploy an effective post-purchase survey.
  </Card>

  <Card title="Post-Purchase Survey Module" icon="chart-pie" href="/data-activation/managed-bi-v1/modules/post-purchase-survey-module">
    How zero-party attribution appears in SourceMedium reporting.
  </Card>

  <Card title="Fairing Integration" icon="plug" href="/data-inputs/platform-integration-instructions/fairing-integration">
    Set up Fairing for automated survey collection and order tagging.
  </Card>

  <Card title="KnoCommerce Integration" icon="plug" href="/data-inputs/platform-integration-instructions/knocommerce-integration">
    Set up KnoCommerce for zero-party data collection and attribution.
  </Card>

  <Card title="First-Party Attribution" icon="shield" href="/help-center/core-concepts/attribution/first-party-attribution">
    How tracking-based signals complement self-reported discovery.
  </Card>
</CardGroup>