What is Zero-Party Data?

Most of us have heard of third-party or first-party data. But what exactly is zero-party data? This invaluable resource is information that is explicitly shared by end users. It complements traditional structured data and helps companies around the world to create more hyper-personalized experiences. Marketing, customer service, and product development teams in particular can use this diverse data set to their advantage and provide greater value to the end user.

In this post, we’ll look at what exactly zero-party data is and the role it plays in creating a comprehensive Customer 360 view. We’ll then look at some scenarios in which you can collect zero-party data and give you tips on how to get started with your new data strategy. The latter is important to help you stay ahead in the evolving landscape of AI and customer engagement. Let’s dive in.

What is Zero-Party Data?

Zero-party data is information a customer intentionally and proactively shares with a brand, such as their preferences, purchase intentions, and how they want to be recognized. Forrester Research coined the term. It can be structured, like a quiz answer, or unstructured, like a request typed into a chatbot. Unlike first-party data, which you observe from behavior, zero-party data is what customers tell you directly.

Companies that use this type of data therefore benefit from direct insights into the intentions, preferences, and needs of their customers. In combination with other first-party and third-party data sources, zero-party data enables the creation of a clearer customer view or Customer 360 in your data platform of choice.

Why is Zero-Party Data Important?

This unstructured data type is essential for businesses today to understand their customers, especially with the rise of AI. Traditionally, tools such as preference centers and surveys have collected this data, but they often fail to capture the true intent of users. GenAI has opened up new possibilities in sectors such as media, retail, healthcare, and finance by making it easier to detect explicit user intent. AI customer agents are transforming online search, browsing, and purchases. This change offers brands the opportunity to better understand their customers’ intentions and improve their personalization strategies.

In addition, the emergence of more affordable storage options for unstructured data in data lakes and lakehouses simplifies the management of these previously unwieldy data points. GenAI capabilities within lakehouses and warehouses now allow organizations to structure and operationalize this information in a similar way to how first and third-party data has been done over the past decade. As storage and modeling technologies become more accessible in the race to improve personalization, the real advantage will be in enriching customer data with zero party data. This approach is already being taken by some companies. Some examples in how companies are advancing their competitive advantage include:

• Offering hyper-personalized experiences
• Predicting customer intentions with greater accuracy
• Improving the efficiency of customer support
• Making informed product development decisions

As John Bourous, Head of Technical Growth Marketing at Snowplow, explains: “Zero-party data is incredibly valuable because we can now learn the intention of a user directly.” This direct insight allows companies to ask questions like “What are you doing here?” and respond accordingly. Now companies are learning to do this at scale to improve customer satisfaction, increase efficiency, and ultimately drive higher profits in an increasingly competitive market.

5 Real Examples of Zero-Party Data Sources

There are a number of sources that companies can take advantage of. Each one counts as zero-party data when customers volunteer the information directly to you. Below we have listed the five most common sources:

Search & Discovery

Search queries on your website or mobile app provide information about users’ purchasing intentions. They are a form of zero-party data that provide a view into what your customers are looking for, so you can customize your offering and improve the user experience. You can use search queries to find out which products and services are trending. You can use them to identify common pain points in the user journey. They can also reveal potential gaps in your product range and serve as a basis for merchandising decisions.

Can AI chatbots collect zero-party data?

Yes, when customers type a budget, a destination, or a problem into a chatbot, they're volunteering zero-party data in their own words. To use it, track each message as an event tied to the same user as their browsing behavior. Snowplow Customer Data Infrastructure offers ready-made schemas for AI agent interactions, and you can attach custom entities for details such as the intent your chatbot extracts.

Advanced companies are using this information to improve their chatbot responses, increase conversion rates, identify common customer issues, and even support product development.

Preference Centers and Quizzes

Preference centers, product quizzes, and onboarding surveys are the most direct sources of zero-party data. Customers tell you which topics and products interest them, how often they want to hear from you, and what they're planning to buy. Because they choose to share it, this data comes with clear consent. Use it to tailor content, recommendations, and communication frequency from the first visit.

Customer Support Interactions

Your customer support channels contain valuable unstructured data about customer issues and experiences that directly impact customer loyalty and retention. From emails and chat logs through to call logs, B2B and B2C brands can benefit from this rich source of data. This data is one of the best places for you to understand customer issues, problems with products or services, and the effectiveness of your support processes. Product and support teams in particular can use this information to improve their products, streamline support processes, and increase overall customer satisfaction.

User-Generated Content

User-generated content such as forum posts, reviews, and blog comments provides authentic, unsolicited customer feedback. This type of data provides detailed information about customer experiences, preferences, and suggestions for improvement. It’s a great way to accurately measure trends in customer sentiment, gather ideas for product improvements, and even discover new use cases for your products or services.

And the list doesn’t end there. The wealth of zero-party data can seem overwhelming. But if you use it effectively and combine it with other data sources, you can completely revolutionize your customer experience.

When you combine zero-party data with structured data, you can create unparalleled personalized interactions and make more accurate predictions and recommendations. But it’s important that you don’t tackle everything at once. Start small. Focus on the areas with the biggest impact. And gradually expand the use of zero party data within your data and personalization strategy.

The future belongs to the companies that can apply this multimodal approach to building an advanced Customer 360 strategy. And we at Snowplow look forward to supporting you on this journey.

Start Your Zero-Party Data Journey

Snowplow Customer Data Infrastructure has always excelled at capturing zero-party data events. From Zendesk support tickets to full application chat logs, our data collection capabilities incorporate multiple data sources, while focusing on data quality and richness.

But now, with the proliferation and accessibility of LLMs in your data platform, we can make sense of these historically cluttered data signals and unlock the true value of this information. With these tools, we can turn unstructured data into structured, analyzable insights and improve business operations.

Think of a customer conversation with an AI chatbot. Now it’s possible to turn these insights into actionable data: tracking the effectiveness of recommendations, measuring positive response rates, and linking conversations directly to sales. With Snowplow’s AI Agent Event Collection and Analytics, you can do just that.

You no longer have to just gather small bits of zero-party data. You can understand it, learn from it, and use it at scale to drive your business forward. Reach out to request a demo from one of our technical consultants.

Zero-Party Data FAQs

How does zero-party data differ from first-party data?

Zero-party data is information a customer intentionally shares with you, while first-party data is information you observe about them through your own channels. A preference center choice, quiz answer, or survey response is zero-party data. Page views, clicks, and purchases are first-party data. Both signal intent: zero-party data captures what customers say they want, and first-party behavioral data reveals it through what they actually do, continuously and at scale.

What is the difference between zero-, first-, second-, and third-party data?

The four types differ by source: customers volunteer zero-party data, you observe first-party data, a partner shares second-party data, and outside providers sell third-party data. Zero-party examples include stated preferences and quiz answers. First-party data covers clicks, sessions, and purchases in your own channels. Second-party data is a partner's first-party data. Third-party data is aggregated by companies with no direct relationship to the people it describes.

How can businesses ethically collect zero-party data?

Businesses collect zero-party data ethically by asking customers directly, explaining why they're asking, and giving something useful in return. Common methods include preference centers, onboarding questions, product quizzes, polls, and post-purchase surveys. Ask only for what you'll use, record consent alongside the answers, make preferences easy to update or withdraw, and act on what people tell you so they see the value of sharing.

How do you combine zero-party data with first-party behavioral data?

Combine them by capturing stated preferences as events that carry the same user identifiers as your behavioral data, then analyzing both in your warehouse. With Snowplow Customer Data Infrastructure, you can track survey answers or preference choices as custom events validated against your own schemas, or capture them with form tracking. Snowplow Identities can then link identifiers, such as a hashed email from a form submission, so stated preferences and browsing behavior resolve to the same user.