Zero-Party Data: Definition, Examples and Limits

Stores are told to collect zero-party data as the answer to disappearing identifiers, usually by a vendor selling a quiz builder. The idea underneath is sound and older than the label: ask customers what they want, and they will often tell you. This guide covers what zero-party data is, where the term came from, how it differs from first-party data, and why what customers say needs checking against what they do.

The short answer: zero-party data is what customers tell you, and Arktis is the check on it

Zero-party data is information a customer deliberately gives a brand: answers to a quiz, choices in a preference centre, a reply to a post-purchase survey. Forrester, the research firm credited with coining the term, defines it as data a customer "intentionally and proactively shares with a brand". First-party data, by contrast, is what you observe: the pages someone viewed, the ad they clicked, the order they placed.

The two are complements. Zero-party data tells you intent and context that behaviour cannot show, but it is self-reported and comes only from those who answer, so it should be checked against first-party behavioural data from the same store.

Arktis does not collect zero-party data. It has no surveys, quizzes or preference forms. For the first-party behavioural side that zero-party answers should be checked against, Arktis is the clear winner for an online store: it records the source of each visit, holds ad click identifiers and UTM tags against the visitor across sessions, and matches Shopify orders and Stripe customers back to those visits. Plans are $49, $149 and $349 a month, with a 7-day free trial on Growth.

Key takeaways

Zero-party data is volunteered, first-party data is observed, and most stores need both. The term is credited to Forrester, whose analysts were using it by 2017, and it has no legal meaning: under GDPR it is personal data like any other. The best collection points are short, offer something in return, and ask only what you will use. Answers reflect memory and self-image, and respondents are not a random sample, so check them against behaviour before you act.

What is zero-party data, and where did the term come from?

Forrester's definition is the one nearly every other source repeats. Zero-party data is data a customer intentionally and proactively shares with a brand, and Forrester lists preference centre data, purchase intentions, personal context and how the individual wants the brand to recognise them as examples.

The term is credited to Forrester. Salesforce, among others, describes it as a term coined by Forrester Research. The earliest Forrester material we could find is from 2017 and comes from analyst Fatemeh Khatibloo: a 2022 academic paper traces the definition to her report Consumer Data: Beyond First And Third Party, dated 3 July 2017, and her vendor landscape report dated 10 October 2017 carries zero-party data in its subtitle. A Forrester podcast episode dated 24 May 2018 describes the concept as data shared explicitly and intentionally by consumers, and her report Q&A: What Marketers Need To Know About Zero-Party Data followed on 10 October 2018.

The hyphenated spelling, zero-party data, is Forrester's. Zero party data without the hyphen is the same thing.

Zero-party vs first-party data

The line between zero-party vs first-party data is the difference between telling and showing. If a customer picks sensitive skin in a quiz, that is zero-party data. If the same customer views four fragrance-free products and buys one, that is first-party data. Both sit in your own systems, both come from your own customers, and for that reason zero-party data is often filed under first-party data, as our own first-party data guide does. Forrester gives it a separate name because the customer chose to hand it over.

The distinction matters in practice for two reasons. Zero-party data can answer questions behaviour cannot: who a gift is for, what budget someone has in mind, which channels they want to hear from you on. And it fails in a different way. Behavioural data is incomplete when tracking breaks. Zero-party data is incomplete when people skip the question, and inaccurate when they answer as the person they would like to be.

Second-party and third-party data sit further from the customer. Data company Lotame describes second-party data as another organisation's first-party data, and third-party data as data an aggregator collects from various sources and sells as a package. Our guide to first-party data strategy covers why stores are moving their weight towards the data they collect themselves.

Zero-party data examples

Product quizzes are the best-known example. Forrester's 2025 write-up of best practice points to MECCA Australia, whose skincare quiz asks where a customer is in their skin journey and how they would describe their skin. The customer gets a recommendation, and the store gets stated needs it could not have inferred from a first visit.

Preference centres are the second. Forrester's 2020 write-up cites Yelp's in-app preference centre, which asks about dining habits. For a store, the equivalent is letting subscribers choose topics, product categories and how often they hear from you.

Post-purchase surveys are the third. One question on the order confirmation page, such as how the customer first heard about you, produces self-reported attribution that click tracking cannot. Our guide to the how did you hear about us survey covers wording, placement and how to read the results.

Other zero-party data examples follow the same pattern: a fit finder, a gift finder, a birthday field, a back-in-stock request, a wishlist. In each case the customer states something directly and expects something for it.

Forrester's advice on collection is brief: the experiences that work are short, simple and offer a clear value exchange. A ten-question quiz with no result at the end is an interrogation.

How stores use it

The most direct use is recommendation. A quiz answer picks the product shown on the results page, and the same answer can shape which products appear in later emails.

The second is segmentation. A stated interest, such as buying for a child or shopping for oily skin, splits an email list in a way purchase history cannot for customers who have not bought yet.

The third is attribution. Survey answers about discovery fill in the channels a tracker cannot see, such as podcasts and word of mouth.

Consent and GDPR basics

This section is general information, not legal advice.

Zero-party is a marketing term. The GDPR does not use it. If a quiz answer can be linked to an identifiable person, through an email address, an account or an online identifier, it is personal data, and the usual rules apply even though the customer volunteered it.

Volunteering an answer is not the same as consenting to every later use. The GDPR's purpose limitation principle requires data to be collected for specified, explicit purposes and not processed further in ways incompatible with them, and its data minimisation principle limits collection to what is necessary for those purposes. In plain terms: say what the answers are for at the point of asking, and do not ask for more than you will use.

Where you rely on consent, the GDPR defines it as a freely given, specific, informed and unambiguous indication of the person's wishes, and says it must be as easy to withdraw as to give.

Take care with sensitive questions. Article 9 prohibits processing of special categories of data, which include data concerning health, unless one of its exceptions applies, such as the person's explicit consent. Whether a particular quiz question about skin, diet or fitness falls into that category depends on the facts, so check with a privacy professional before asking it.

Consent rules also cover the tracking on the page the quiz sits on. Our article on why cookie deprecation is off explains what still limits tracking, consent law included.

The limits of zero-party data

It is self-reported. Pew Research Center's guidance on survey questions notes that people's wish to be accepted can lead them to give inaccurate answers on sensitive subjects. A customer who says they shop sustainably may buy on price.

The options shape the answers. In a Pew example, 58 percent of respondents chose the economy when it was offered as an answer, while only 35 percent volunteered it in an open-ended version of the same question. A quiz with five skin concerns will find those five concerns.

The sample is small and self-selected. Only some visitors take a quiz and only some buyers answer a survey, and they are not a random draw from your customers. A segment built from quiz takers describes quiz takers.

It goes stale. A stated preference is true on the day it is given. Budgets, sizes and tastes change, and few customers return to update a profile.

It does not cover strangers. A first-time visitor has told you nothing, so the only signals you have are behavioural.

Checking answers against behaviour

Treat each zero-party field as a claim and look for the matching behaviour. If customers who chose a premium budget in a quiz buy from the entry range, the question is measuring aspiration. If the survey says 20 percent of new customers came from Instagram and first-touch click data credits Meta ads with far more, some customers are forgetting an ad they clicked.

Take an example store with 300 quiz completions in a month, of which 90 ordered. Compare what those 90 said they wanted with what they bought. Where the two agree, the question is useful and worth keeping. Where they disagree, either the question is leading or the recommendation is not landing, and both are worth knowing.

The same comparison works at channel level, with the survey's discovery shares next to first-touch sources for the same period. For the click side, see customer journey analytics.

Where Arktis fits, and where it does not

Arktis is ours, and it is not a zero-party data tool. It has no quiz builder, no survey tool, no preference centre and no email or SMS sending, so it will not ask the question or store the answers. For collection you need a quiz or survey app, or a form on your own site, and the answers will live there or in your email platform.

What Arktis gives you is the behavioural record to test those answers against: the source of each visit, ad click identifiers and UTM tags held across sessions, Shopify orders matched to a visitor on email where the store has identified the visitor, otherwise on the UTM source in the order's landing URL against a session from the previous 24 hours, which can be another visitor's session, Stripe customers matched through a four-pass waterfall, and a comparison of first-touch, last-touch, linear, time-decay and position-based credit per ad platform for visits that carried an ad click identifier. You put the survey or quiz export next to those numbers yourself. Arktis honours Global Privacy Control by default and is hosted in the EU: its database and functions run in EU regions.

To see the behavioural side on your own store, start the 7-day Growth trial, or compare the tiers on the pricing page. For related reading, see consent management for analytics and privacy-first analytics.

Sources

Forrester: Straight From The Source: Collecting Zero-Party Data From Customers, Stephanie Liu, 30 July 2020, the definition and the Yelp example, accessed 1 October 2026

Forrester: Ask, Don't Interrogate: Best Practices For Collecting Zero-Party Data, 13 March 2025, the definition, the MECCA quiz and the short, simple, clear value exchange advice, accessed 1 October 2026

Forrester: Q&A: What Marketers Need To Know About Zero-Party Data, Fatemeh Khatibloo, 10 October 2018, accessed 1 October 2026

Forrester podcast: The Algorithm Of Me, 24 May 2018, Fatemeh Khatibloo on the concept of zero-party data, accessed 1 October 2026

Forrester: Vendor Landscape: The Consumer Data Ecosystem's Service Providers, Fatemeh Khatibloo, 10 October 2017, zero-party data in the subtitle, accessed 1 October 2026

Forrester: Consumer Data: Beyond First And Third Party, Fatemeh Khatibloo, 3 July 2017, the earliest Forrester report we found, accessed 1 October 2026

Frontiers in Big Data, 2022, perspective article tracing the Forrester definition to the report Consumer Data: Beyond First And Third Party of 3 July 2017, accessed 1 October 2026

Salesforce: What is zero-party data?, attributes the term to Forrester Research, accessed 1 October 2026

Lotame: What is second-party data?, second-party and third-party definitions, accessed 1 October 2026

Regulation (EU) 2016/679 (GDPR), Articles 4(1), 4(11), 5(1)(b) and (c), 6, 7(3) and 9, accessed 1 October 2026

Pew Research Center: Writing survey questions, social desirability and the 58 and 35 percent example, accessed 1 October 2026