A shopper lands on a CBD store looking for help with sleep. They see a wall of tinctures, gummies, and capsules. No guidance on dosage. No way to figure out which format might work for their situation. They leave.
Now picture the same shopper taking a 60-second wellness quiz. It asks about their sleep patterns, whether they've tried supplements before, and whether they prefer something they can chew or drop under their tongue. At the end, they see three products matched to their answers, with dosage suggestions included. They add one to their cart.
The difference between those two experiences comes down to one thing: zero-party data.
This article covers what zero-party data actually means, how it compares to other types of data ecommerce brands work with, and what it takes to collect and use it well.
Forrester Research coined the term “zero-party data” in 2018. Their analyst, Fatemeh Khatibloo, defined it as data that a customer intentionally and proactively shares with a brand. That includes preference center data, purchase intentions, personal context, and how the customer wants the brand to recognize them.
In practice, here's what zero-party data looks like across different ecommerce verticals:
"When a customer trusts a brand enough to provide this really meaningful data, it means that the brand doesn't have to go off and infer what the customer wants or what their intentions are." — Fatemeh Khatibloo, VP Principal Analyst, Forrester
The common thread across all of these: the customer volunteers the information because they expect something useful in return. A better recommendation. Less irrelevant noise in their inbox.
Zero-party data makes more sense when you see how it fits alongside the other data types brands rely on.
Zero-party data is what a customer tells you directly. "I want a CBD gummy for sleep, nothing with THC, under $40." It's the most accurate type because the customer gave it to you on purpose, with full awareness of what they were sharing.
First-party data is what you observe from their behavior on your own channels. Pages they viewed, products they bought, how long they spent on a particular collection page. It's useful, but it requires interpretation. Someone browsing baby products might be shopping for a friend. Someone who viewed five different protein powders could be comparison shopping for their gym buddy.
Second-party data is another company's first-party data, shared or sold to you through a partnership. It's not as common but not unheard of.
Third-party data gets aggregated from external sources by data brokers. Broad demographic and behavioral categories are often collected without direct user consent. Accuracy varies widely, and privacy regulation has made this type of data increasingly risky to use.
“The difference between first-party and zero-party data is the difference between watching what someone does and hearing what they actually want.”
Three things are converging, making this topic especially relevant for ecommerce brands in 2026.
GDPR went into effect in 2018. CCPA followed in 2020. Since then, a growing list of state-level and national privacy laws have added new restrictions on how brands collect and use consumer data. Third-party data, which often depends on tracking users without their explicit consent, sits in an increasingly uncomfortable legal position.
For brands selling in regulated or controlled categories like CBD, supplements, or adult wellness, the scrutiny is even higher. Advertising platforms already limit targeting options for these verticals. The brands that can personalize without relying on third-party tracking have a real operational advantage.
The story here is more complicated than the headlines suggest. Google reversed its plan to fully remove third-party cookies from Chrome, and as of April 2025, cookies will remain enabled by default and there's no separate consent prompt.
But Chrome isn't the whole picture. Safari and Firefox already block third-party cookies. Ad blockers strip them. Consent banners on European sites reduce their reach. And the trajectory is one-directional: Apple's App Tracking Transparency rollout in 2021 showed what happens when users get a clear opt-out: the majority take it.
The practical result is that marketers who still depend on third-party cookies are working with a data set that shrinks and degrades a little more each year, regardless of what web browsers do.
According to a 2025 study by Qualtrics XM Institute covering more than 23,000 consumers globally, 64% of shoppers prefer to buy from companies that tailor the experience to their needs. McKinsey's research tells a similar story: 71% of consumers expect personalized interactions, and 76% get frustrated when it doesn't happen.
But there's a tension. Customers want personalization and they're also wary of how brands get the data to deliver it. Zero-party data resolves that tension because the customer controls what they share, when they share it, and why.
“Customers want you to know what they need. They just want to be the ones who tell you.”
When you infer preferences as first-party data from browsing behavior, you're still just guessing. Sometimes the guess is good, but often it isn't.
Someone who viewed three different melatonin supplements might have trouble sleeping. Or they might be researching options for an elderly parent. Someone who spent four minutes on a product page might be deeply interested in that item, or they might have set their phone down to answer the door.
The problem compounds when you try to build segments from this kind of data. A supplement brand might create a "sleep health" segment based on browsing patterns, only to find that a third of those visitors were browsing casually or for someone else. Now their email campaigns are going to people who don't actually care about sleep products, open rates drop, and the data looks like it's working worse than it is.
Zero-party data removes that ambiguity. When a customer tells you through a quiz that they're new to CBD, want help with anxiety, and prefer something they can take at work without feeling drowsy, there's no interpretation gap. You know what they want because they said so.
That directness makes everything downstream more accurate. Product recommendations land closer to what the customer actually needs. Email segments reflect real preferences instead of guesses. Ad targeting gets sharper, and even inventory planning benefits when you know what customers are asking for rather than trying to reverse-engineer it from click patterns.
There's a compounding effect here, too. Every time you use zero-party data to make an accurate recommendation, the customer's trust in sharing more data goes up. A pet food customer who gets a spot-on food recommendation based on their dog's breed and age is more likely to fill out a follow-up survey about treats or supplements. The data relationship deepens because the value exchange keeps delivering.
There are several proven methods here. Most brands start with one and layer in others over time.
The best zero-party data collection doesn't feel like a form. It feels like a conversation where the customer gets something useful at the end.
Collecting data is only half of it. What matters is how quickly and effectively you put it to use.
Quiz responses map directly to product suggestions. A supplement brand can recommend a specific daily stack based on a customer's stated health goals, age, and dietary restrictions. A CBD retailer can steer a first-time buyer toward a low-dose gummy instead of jumping straight to a full-spectrum tincture that might overwhelm them.
Instead of segmenting only by purchase history, brands can segment by stated preferences. A pet food customer who told you they have a senior dog with allergies gets a different email flow than someone with a healthy puppy. A coffee subscriber who prefers single-origin light roast doesn't get campaigns pushing flavored blends.
This shows up in the numbers. McKinsey's Next in Personalization report found that personalization typically drives a 10 to 15% revenue lift, and companies that grow faster drive 40% more of their revenue from personalization than their slower-growing counterparts.
Zero-party data feeds better lookalike audiences. When you know what your best quiz completers care about, what problems they're trying to solve, and what product attributes matter to them, you can build acquisition campaigns around those attributes instead of generic demographics.
A supplement brand running Facebook ads could build a lookalike audience based on quiz completers who indicated they're interested in gut health and prefer capsule formats. That's a much tighter seed audience than "people who visited our probiotics page," which might include casual browsers, bots, or people who hit the page by accident. The resulting lookalike will be closer to actual buyers because the seed data is richer and more intentional.
Especially relevant for supplements, apparel, and any category where the wrong product leads to churn rather than returns. When a customer tells you their goals, experience level, or sensitivities up front, the recommendation is more likely to stick. Fewer returns. Higher lifetime value.
Most zero-party data content ignores this angle entirely. For brands in CBD, adult wellness, supplements, and other controlled categories, zero-party data offers a compliance advantage. You're collecting information the customer volunteered, with clear consent, through a transparent interaction. That's a much stronger position than relying on inferred behavioral data when regulators or ad platforms ask how you're targeting customers.
When Facebook or Google restricts your ability to run interest-based targeting for restricted products, having a rich set of customer-declared preferences becomes an operational lifeline.
Consider a CBD brand that can't run retargeting ads based on browsing behavior because the ad platform flags the category. If that brand has quiz data showing which customers want sleep products versus pain relief versus general wellness, they can still build targeted email campaigns, personalized landing pages, and segmented SMS flows. The ad platform restriction hurts their paid acquisition, but their owned channels stay sharp because the data came directly from the customer.
Adult wellness brands face a similar dynamic. Many advertising channels restrict or ban these categories outright. Zero-party data collected through onboarding quizzes or preference profiles gives these brands a first-party dataset they fully own, built on explicit customer consent, that no platform policy can take away.
“For brands in restricted categories, zero-party data is the most defensible way to personalize when the rules are strictest”
Why would anyone volunteer their personal information?
Customers share data when they believe the trade is worth it. Forrester's research calls this the "value exchange." The customer gives you something meaningful about themselves, and in return, they get a better, more relevant experience.
This works when:
When the exchange breaks down, customers either abandon the experience or give inaccurate answers. Forrester has noted that asking for too much information at once can push customers to provide false data just to get through the process.
Picture a quiz that asks seven questions about sleep habits and then demands a phone number and email before showing results. That's a broken value exchange. The customer came for help. They got a lead capture form. A better version shows the product recommendations immediately after the final question and then asks for an email to save the results or unlock a discount. The data quality is higher because the customer already received value before you asked for anything.
If you've read this far and want to know what to do next, here's a reasonable starting sequence:
Tools like Sensez make this process native to Shopify, handling quiz logic, product mapping, and platform integrations without requiring custom development. It's a good place to start if you want to move quickly.
Privacy regulation is expanding. Third-party data gets less reliable every year. And customers already expect brands to know what they need without feeling watched.
The brands that build a direct data relationship with their customers will have a structural advantage. Zero-party data is the foundation for that kind of relationship, and the ones collecting and activating it now are building a head start that compounds over time.
![CBD Brand Quiz Strategy: Match Products to Goals [2026]](https://cdn.prod.website-files.com/69cdce356fb7cba8c3800587/69e0ab9e4d7285403c49c567_tg_image_1576438528.png)
![The Complete Guide to Shopify Product Quizzes [2026]](https://cdn.prod.website-files.com/69cdce356fb7cba8c3800587/69e0a74eb763be0a82ac4187_tg_image_1002197460.png)
