---
title: "Unlocking the Power of Zero-Party Data"
date_published: "2023-03-26"
date_modified: "2023-08-04"
permalink: "https://www.samtomlinson.me/insights/zero-party-data/"
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seo:
  title: "Unlocking the Power of Zero-Party Data"
  description: "Lets talk a topic that’s frequently mentioned but rarely actioned: zero-party data. It’s no secret that data is everywhere  and being able to leverage the right data at the right time"
  canonical_url: "https://www.samtomlinson.me/insights/zero-party-data/"
---

Let's talk a topic that's frequently mentioned but rarely actioned: zero-party data.

It's no secret that data is everywhere ̵1; and being able to leverage the right data at the right time is increasingly becoming the point of leverage across the digital landscape. Put simply: those with the best data will win in the long-run. Those without it will lose.

Most of us are familiar with the "standard" types of data, all of which are passively collected by brands and deployed (to varying degrees of success) in many marketing initiatives:

First-Party (1P) ̵1; data we observe on our owned properties. Think web analytics data, pageview data, ecommerce purchase data, etc. This is the data brands passively collect on each and every website visitor or app user.

Second-Party (2P) ̵1; data we obtain from a partner or affiliate (such as a content publisher, or a conference organizer, or a webinar host).

Third-Party (3P) ̵1; data aggregated from multiple, unaffiliated-to-you sources and joined together by a third party. A great example of this is SparkToro audience insights or purchased credit report data.

The commonality across each of three methods of data collection is that the subject (the user) is unaware of exactly what is being collected, who is involved & how (or if) that data is being deployed. Further, all conclusions drawn from each of these three data types are inferred or assumed ̵1; we don't know how or why a user visited a specific page (or subscribed to a specific mailing list, or was categorized as having a specific interest).

Then, there's zero-party data (0P): information that an individual directly, knowingly, and intentionally shares with a brand. Used correctly, 0P data is an incredible point of leverage for brands - it avoids the challenges inherent in 1P, 2P & 3P data, while providing a persistent advantage (people's preferences + traits don't change *that* frequently).

And for those reasons, it isn't hyperbolic to say that the brands who can successfully implement a cohesive data strategy will thrive, while those that fail will falter and (eventually) fold.

While zero-party data is staggeringly important to brands, it's important to remember that it isn't a cure-all, and it certainly isn't an overriding source of truth. All data admits of errors and all data has shortcomings. To give a specific example: while 0P data avoids some of the issues with 1P (inference + lack of context) or 3P (source + quality) data, it lacks volume (how many people are really completing your quiz vs. how many are visiting your site vs. how many are visiting *any* site in your vertical?).

To succeed, brands need to be able to layer together each data type ̵1; and in so doing, build a fuller, more robust picture of their audience. That, in turn, unlocks a number of exciting (and lucrative) opportunities for brands, including:

Improve conversion rates + LTV ̵1; creating a more relevant, personalized experience is strongly correlated with higher conversion rates + higher LTV (which makes a lot of sense, since you can direct people to what they actually want, vs. what you hope they'll want).

Accelerate Product Improvement / Find Product-Market Fit ̵1; the easiest way to determine your optimal product development roadmap is to figure out what people are using your product for now, and where it's falling short ̵1; whether that's by survey, review, focus group or some combination.

Future-Proof Your Data Infrastructure ̵1; we've all heard that cookies are going away (or being eaten) in the next few years, while new privacy laws are continually being rolled out. Properly-collected 0P + 1P data tend to have the lowest risk profile of any data type (disclaimer: I'm not an attorney or a regulatory compliance expert; if you have actual questions for your jurisdiction, find one).

Demand Forecasting ̵1; understanding the types of users coming to your site (and their specific needs) is critical for both inventory + marketing performance forecasting - enabling you to allocate paid media more efficiently while avoiding sell-outs and overstocks.

Content Development ̵1; 0P data doesn't just help your paid media team; it also provides a boost to your content marketing + SEO teams, too.

While this is all well & good, the most common question I hear from brands is, "where do you start?" And I get it ̵1; it feels overwhelming to piece together a coherent, cohesive data strategy from square one. The good news: no one actually has it all figured out (and by the time they do, it all breaks again anyway). Your goal should be to get better every day, not to be perfect today.

And to get you started, here are four keys for building + leveraging your zero-party data strategy:

### Key #1: Identify the stuff you *absolutely* must learn about your audience, then make it remarkably easy for them to share it.

Every brand has certain pieces of information they absolutely need to know in order to direct a user to the correct product/offer/bundle/whatever. This might be as simple as a vacation destination (for travel) or a gender (for clothing) or skin type (for makeup/cosmetics) - or far more complex (for IT consulting or B2B or home buying). The point is that for every brand, there are a few pieces of information that can enable a remarkably better experience for the user AND provide outsized value to the brand.

Once you know what to collect, make it remarkably easy for the user to share. [This quiz from Winc](https://www.winc.com/palate-profile) remains one of my absolute favorites ̵1; it's absurdly simple (it's ~6 questions, each with visual aids) but collects a staggering amount of data on my palate profile + wine preferences. To Winc's credit, they're incredibly clear on how that data is used (to match me with wine) and the "results" page clearly shows me how some of my selections in the quiz influenced the wines picked for me.

If that's a bit daunting, consider [this pop-up experience from Vuori](https://vuoriclothing.com/) ̵1; the only thing they want to know (to start) is my gender ̵1; and they use it to send a personalized welcome email with some of their best-selling products for that gender. The actual workflow behind this is wonderfully simple ̵1; but the result is dramatically higher conversion rates + a delightful customer experience. [Jones Road Beauty](https://jonesroadbeauty.com/) does the same thing ̵1; only they ask about skin type (oily vs. dry) ̵1; which they immediately action via "personalized" recommendations.

The thing most brands miss is that integrating a cohesive 0P collection strategy ends up being a win-squared for the brand, plus a win for the customer:

Win #1: the brand collects insanely valuable data on their audience that they can't get anywhere else and which enables them to raise the expected value of each visitor

Win #2: the 0P data collection often *replaces* the typical discount offered for newsletter/email capture ̵1; increasing margin and customer lifetime value

Win #3: the data enables a better, more personalized experience for the customer

Finally ̵1; and if you *really* want to up your game, check out personality test sites. They have this down to a literal science. Answer a bunch of questions (in