The Gist
- The original voice of the customer. Zero-party data is customer-volunteered data that shines a light on their preferences, lifestyles and intent. No-code tools are making it easy for marketers to experiment quickly and apply insights to design better CX.
- AI plus zero-party data is powerful. Rich insights from zero-party “small data” can help train better AI models that can be leveraged at scale.
- Follow the rules. Like any other form of customer data collection, there are ground rules and best practices to make the most of the investment in zero-party data.
Once upon a time, third-party data was abundant, and everyone was happy except consumers, who felt exploited and “sold to” without consent.
Then came the almost-cookieless world and rising consumer awareness about compliance and consent. With “first-party data,” brands can “extract” information via various indirect and direct means from their website visitors, prospects and customers on their properties.
In 2017 analysts at Forrester popularized the term “zero-party data” to make a distinction between customer data “taken” by brands and data voluntarily “given” by customers to the brand, either in exchange for an immediate reward like a discount or value such as better personalization and product recommendations.
Unlike first-party data, which is often more transactional, historical and based on actions taken by customers, zero-party data tends to be more personal and includes details about preferences, lifestyles, hobbies, goals and even body measurements or health stats. Customers tend to share zero-party data when there is a high level of trust in the brand or the reward seems so attractive that they don’t mind.
Related Article: From First-Party to Zero-Party Data
Many Routes to the Zero-Party Data Party
Zero-party data can be collected in many ways throughout the lifetime of the customer.
Preference centers are becoming popular to manage signed-up customers, especially for brands where the inventory is so vast that customers value product recommendations and are happy to answer questions about their needs to aid that. Think Home Depot or Ikea, online educational platforms such as Udemy, and even platforms like Canva that want to know your role and how you plan to use Canva, so they can give you more relevant design recommendations.
Preference centers also let customers specify how they prefer to be contacted by the brand, how often and with what kind of information. This can lead to significant improvements in opt-out rates by nudging customers to “opt-down” instead.
The product-led approach to zero-party data is epitomized by brands like Stitch Fix where the product is 100% customized to shopper needs or insurance companies that ask you to fill out forms or calculators in granular detail, so they can give you the best quote. The zero-party data collection is often built into the product onboarding flow.
In categories such as personal grooming, beauty and food, high-engagement tools like surveys, quizzes, polls, custom coupons, review funnels and product finders are gaining traction. Because most of these tools are no-code and automated, marketers can easily experiment with them to collect zero-party data at scale across a range of touchpoints, from websites to chatbots and mobile apps. Of course, it helps that it's possible to draw a direct link to conversion, especially when the insights are used to design more effective cross and upselling opportunities.
However it is collected, zero-party data done right has the potential to change the way a brand — in almost any category — can deliver experiences and win preference and loyalty. In some ways, it even solves the personalization vs. privacy paradox.
Related Article: Marketers Should Prepare to Abandon Third-Party Data Now
Hyperpersonal Experiences With AI-Powered Zero-Party Data
The problem some brands have with zero-party data is that it does not qualify as "big data." Especially for business-to-consumer (B2C) and direct-to-consumer (D2C) marketers, used to working with huge volumes of data, it may seem like there’s just not enough of it to make a difference. But AI is set to change that.
AI can turn zero-party’s “small data” weakness into its power. While the volumes of the data may not be very high, the insights themselves can be rich enough material to create patterns and train AI models to keep getting smarter.
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Legacy consumer packaged goods (CPG) brands, especially, have struggled with the idea of personalization beyond mass customization. But today, they can use AI-powered zero-party data to personalize shopper experience not only at each touchpoint or channel but at any moment in the interaction.
Using generative AI (a type of AI that generates new data, such as images, text or audio, that is similar to or mimics existing data), brands can create dozens of experiences on the go, while saving time and money. For example, creating one quiz takes around 25 hours of copywriter, designer and developer time. Generative AI can create multiple quizzes at half or less of the effort while giving each shopper a different experience.
For example, Skeep is building an AI generator that can automatically turn any website or product page into a tailored experience that guides shoppers to purchase. It does that by scanning the ecommerce website, tagging all products, analyzing the product page and automatically generating interactive widgets.
Co-founder and CEO Omer Cohen calls it the “next step” in retail. Zero- and first-party data combined with generative AI can enable “micro, in-the-moment experiences,” giving each shopper a hypercustomized interaction not just in terms of content but also user interface.
Another way to look at these real-time micropersonalizations is like running a never-ending series of tests, where the system learns and gets smarter with each interaction, thus making the next microexperience better. It’s a virtuous cycle. One where the lines between the product experience and marketing experience are increasingly blurred.
Sai Koppala, CMO of SheerID, adds that zero-party customer data can be a powerful way to optimize ad campaigns and drive acquisitions, because “when campaigns work with opted-in customers of certain identities, they are likely to be effective with look-alike audiences too.”
AI’s Superpower in Customer Journey Optimization
AI is even more powerful when used with a combination of zero- and first-party data. “An essential rule of CX and UX is never to ask the user a question you already know the answer to or to which you can reasonably infer the answer. AI helps infer everything that is inferable, so you only have to ask customers a small subset of the right questions when collecting zero-party data,” said Michael Scharff, CEO of Evolv.ai, a company using AI to discover, personalize and serve progressively better journeys by continually adapting to live user behavior.
Insights from zero-party data about lifestyle, usage and genre preferences allow brands to turn first-party inferences into facts and deliver a more positive personalization experience, added Evolv.ai Chief Technology Officer Tyler Foster. “Aside from using AI to better understand users’ preferences and needs, it's also the only way to truly act on that understanding at scale. AI provides the path to adaptive journeys that would be too complex to manage through any other means currently available.”
Marketing With Zero-Party Data: Best Practices
Like with any other form of data collection, there are a few ground rules for making the most of zero-party data, too.
- Relevance and context are key. Dan Healy, founder and CEO of FanPower, helps sports organizations build direct relationships with their fans by getting to know customers better via zero-party data. He said that to gather zero-party data of any value, the questions need to be hyperrelevant to the content they're placed around. Sports organizations, for instance, collect AI-powered zero-party data through chatbots and polling. “The AI makes polling smarter because it can create questions based on the content the quiz is embedded in, with little to no human interaction. It also uses engagement data to understand what questions work best and collects incrementally more data over time."
- Design the zero-party data collection effort around the larger engagement strategy. Resist the temptation to over-collect data. Instead, use the data immediately to optimize the customer journey. “The experience following the customer volunteering all that information about themselves should be clearly connected to the answer they provided and contextually relevant enough to be worth their while. This will build trust with your users and ensure they know you're focused on using their answers for their benefit, not yours, and create a virtuous cycle of zero-party data for the future,” suggested Foster.
- Compliance still matters. Just because it's customer-volunteered data does not mean the brand can use it in any way they want. Compliance regulations dictate that any data collected should be used only for the stated purpose and not to needlessly retarget customers. Zero-party data is the key to co-created or collaborative personalization, but compliance issues and data breaches do shake customer confidence.
- Just because it's zero-party data doesn't mean it's always accurate. In general, the understanding is that zero-party data is more accurate, trustworthy and compliant than other forms of customer data. However, SheerID, which helps B2C brands instantly verify consumer-provided data, claims roughly 30% of the people they verify for a community discount misrepresent themselves. For example, people will claim to be a student in order to qualify for a student discount when, in fact, they aren’t students. Koppala suggested using the “trust and verify” approach when gathering zero-party data in exchange for community or identity-based rewards.
- Build a relevant portfolio of zero- and first-party collection sources. Citing the “say-do gap” when it comes to surveys, Koppala suggested collecting various forms of zero- and first-party data to combine the rich detail of surveys with observations of actual behavior across other properties and touchpoints.
- Maintain data discipline. When using multiple surveys and quizzes across multiple channels and touchpoints, ensuring the data sources are trackable and stored in the right place is key to being able to use it effectively.
- Data decay is real. Avoid one-off zero-party data collection efforts. Instead, create a plan and work the engagement moments seamlessly across the entire customer journey. Have a plan to regularly update preferences so that you are not working with outdated data.
Final Thoughts on Zero-Party Data and AI
Ultimately, it’s important to focus on the quality of human input, not the quantity of machine output, as H. James Wilson and Paul R. Daugherty from Accenture suggest in this paper. Zero-party data can drive engagement, sales and retention with improved personalization and recommendations. In the bargain, it can also collect rich data to better train the AI data models and generate more accurate predictions of customer behavior.
