Zero-Party Data
Zero-party data is information a customer intentionally and proactively shares with a brand. It covers stated preferences, purchase intentions, personal context, and how someone wants to be recognized. Forrester analyst Fatemeh Khatibloo introduced the term in a report published on 10 October 2018, and the defining feature is that the customer declares the data rather than the brand observing it.
Zero-Party Data vs First-Party Data
The difference is how the data is obtained, not who holds it. Zero-party data is declared. First-party data is observed.
| Zero-party data | First-party data | |
|---|---|---|
| How it is obtained | The customer states it | The brand observes behavior |
| Example | “I am shopping for a gift” | Viewed three gift-guide pages |
| Reveals intent | Directly | Only by inference |
| Typical volume | Low | High |
| Main risk | People answer aspirationally | You misread the behavior |
Most practitioners treat zero-party data as a subset of first-party data, since the brand collects it directly in its own channels. Forrester positions it as its own category. The classification argument matters less than the operational point: declared data answers questions that behavior cannot. Browsing history shows a person looked at running shoes. It cannot tell you they are buying for their father, which changes every recommendation that follows. The broader comparison of all four data types sits in first-party data vs third-party data.
Zero-Party Data Examples
Anything the customer types, selects, or rates on purpose qualifies. Common sources:
- Preference center selections. Email frequency, topic interests, preferred channel.
- Quiz and product finder answers. Skin type, room size, experience level, budget band.
- Profile and account fields. Birthday, sizing, dietary restrictions, job title.
- Survey and poll responses. Post-purchase reason codes, NPS free text, feature requests.
- Wishlists and saved items. A declared signal of future intent rather than past behavior.
- Stated purchase context. Gift versus personal use, replacement versus first purchase.
What does not qualify: anything inferred. A predicted size, a modeled affinity score, or a lookalike segment is derived data, even when it is highly accurate.
How to Collect Zero-Party Data
Collection works when the value exchange is explicit and immediate. The customer gives up information and gets something back in the same session.
- Name the payoff before the question. “Answer 4 questions, get a routine built for your skin” outperforms “Tell us about yourself”.
- Choose an interactive format. Quizzes, configurators, and recommendation engines report completion rates around 30% to 50%, against roughly 2% to 5% for a standard form.
- Keep the first ask short. Three to five questions. Depth comes later through progressive profiling, not from one long form.
- Write the answer straight into the profile. Declared attributes are worthless sitting in a survey tool. They belong in the CDP or ESP that runs your campaigns.
- Use it visibly within one cycle. If the next email ignores what the customer just told you, the next request gets ignored too.
Tag the links that drive traffic to these assets so you can tell which channel produces the most complete answers, not just the most starts:
https://example.com/skin-quiz?utm_source=newsletter&utm_medium=email&utm_campaign=quiz-launch
Reading completion by source is the fastest way to find out where your declared data actually comes from. Link analytics records the click at redirect time, so the channel attaches to the session before the first question loads.
Building a Zero-Party Data Strategy
A strategy is the collection plan plus the maintenance plan. Most programs build the first and skip the second.
Four numbers make the program measurable:
- Profile completion rate. The share of active customers with at least one declared attribute. Mature programs target above 40% within 18 months of launch.
- Activation rate. The share of collected attributes actually used in a campaign. Anything below 70% means you are asking questions you do not act on.
- Completion versus start rate. A high drop-off mid-quiz usually means the value exchange was oversold at the entry point.
- Refresh cadence. Re-prompt every 6 to 12 months and stamp each attribute with a last-validated date.
Decay is the failure most teams miss. A customer who declared an interest in baby products in 2022 has different needs by 2026, and stale declared data is worse than none: it drives confident personalization in the wrong direction.
Where Zero-Party Data Falls Short
Volume is the constraint. Only a fraction of any customer base will ever complete a preference form, so zero-party data enriches profiles rather than populating them.
Three other limits are worth planning around:
- People answer aspirationally. Stated budget and stated frequency both skew optimistic.
- It cannot be bought. Unlike third-party data, there is no shortcut to scale. Every record is earned.
- Consent is not implied by the answer. Someone completing a quiz has not agreed to be retargeted with it.
Frequently Asked Questions
What is zero-party data?
Zero-party data is information a customer deliberately and proactively gives a brand, such as preference center selections, quiz answers, or a stated purchase intention. Forrester’s Fatemeh Khatibloo introduced the term in October 2018. The distinguishing feature is intent: the customer chose to share it, rather than the brand deducing it from behavior.
What is the difference between zero-party and first-party data?
Zero-party data is declared by the customer. First-party data is observed by the brand from behavior in its own channels, such as page views, purchases, and email opens. Both are collected directly, which is why many practitioners treat zero-party data as a subset of first-party data. The practical difference is that declared data carries intent and context, while observed data carries volume.
What are examples of zero-party data?
Preference center settings, quiz and product finder answers, profile fields such as sizing or dietary restrictions, survey responses, wishlists, and stated context such as “this is a gift”. Inferred attributes do not count, even accurate ones. A predicted shoe size is derived data, while a shoe size the customer typed in is zero-party data.
How do you collect zero-party data?
Offer something specific in return and ask at the moment the answer is useful. Interactive formats such as quizzes and product finders report 30% to 50% completion, well above the 2% to 5% typical of standard forms. Keep the first request to three to five questions, write the answers into the system that runs your campaigns, and visibly act on them in the next message.
Is zero-party data exempt from GDPR?
No. Zero-party data is still personal data, so GDPR obligations on lawful basis, purpose limitation, and data subject rights all apply. Voluntary submission is not blanket consent either: answering a product quiz does not authorize using those answers for advertising. State the purpose at the point of collection and keep the record of what was agreed.
To see which campaigns bring in the people who actually complete your preference forms, tag those links with the free UTM builder at linkutm.