Zero-Party Data
Data that customers intentionally and proactively share with a brand, including preferences and intentions.
Definition
Zero-party data is information that customers intentionally and proactively share with organizations, explicitly declaring their preferences, intentions, needs, and how they want to be recognized. Unlike first-party data that organizations observe and infer from customer behavior, zero-party data comes directly from customers who volunteer it—typically through surveys, preference centers, interactive quizzes, polls, account customization, and direct conversations.
The term was coined by Forrester Research to distinguish this explicitly shared data from passively collected first-party data. Zero-party data includes purchase intentions (what customers plan to buy), personal preferences (sizes, styles, dietary restrictions), communication preferences (how and when to contact them), lifestyle information (interests, life stages, goals), and self-declared attributes (professional role, industry, challenges).
The key characteristic of zero-party data is transparency and intentionality. Customers knowingly provide this information, usually in exchange for something valuable—better recommendations, personalized experiences, relevant content, or tailored offers. This creates an explicit value exchange rather than the implicit data collection that characterizes traditional tracking.
Why It Matters
Zero-party data addresses the fundamental tension between personalization and privacy that defines modern marketing. Customers increasingly demand personalized experiences while simultaneously resisting invasive data collection. Zero-party data resolves this paradox by putting customers in control of what they share.
When customers proactively share preferences, they expect and welcome personalized experiences based on that information. This consent and intentionality creates a trust foundation that improves both the effectiveness and the perception of marketing efforts. A customer who tells you their size, style preferences, and upcoming events welcomes relevant product recommendations—whereas the same personalization based on tracking can feel invasive.
Zero-party data also eliminates the guesswork and inference errors that plague behavioral data. When a customer states their intentions directly, marketers don't need to analyze patterns and guess at motivations. This precision improves marketing efficiency and customer experience simultaneously. The same information that would require extensive behavioral analysis to infer can be obtained accurately through a simple preference quiz.
The strategic value of zero-party data extends to competitive differentiation. Organizations that build genuine, transparent data relationships with customers create loyalty and engagement that competitors cannot easily replicate. This relationship-based data strategy becomes a sustainable advantage as privacy changes make inference-based approaches increasingly difficult.
Examples in Practice
A premium beauty retailer develops a comprehensive skin analysis quiz that captures skin type, concerns, sensitivities, product preferences, routine complexity, and budget range. Customers invest five minutes answering questions because they receive genuinely personalized product recommendations and routine guides. This zero-party data powers email marketing, homepage personalization, and in-store consultations—all welcomed by customers who explicitly requested this tailored experience.
A travel company creates interactive preference tools that capture bucket list destinations, travel styles (adventure vs. relaxation, group vs. solo), budget ranges, and important trip criteria (food, culture, nature). When deals match these stated preferences, customers receive notifications they actually want. The company's conversion rates on preference-matched offers dramatically exceed generic promotions.
A financial services firm implements a goals-based preference center where customers specify their financial priorities—retirement timeline, risk tolerance, major purchase plans, education funding needs. Advisors and automated systems use this explicitly stated information to provide relevant guidance, product recommendations, and content. Customers appreciate advice aligned with their stated goals rather than inferred assumptions.
A fashion subscription service bases their entire model on zero-party data. Members complete detailed style profiles covering fit preferences, style aesthetic, price comfort, lifestyle needs, and off-limits items. Each delivery is personalized using this explicit guidance. The direct relationship between shared preferences and received products creates high satisfaction and retention because customers see their input directly reflected in outcomes.