Unlocking the Power of 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 – 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) – 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) – data we obtain from a partner or affiliate (such as a content publisher, or a conference organizer, or a webinar host).
- Third-Party (3P) – 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 – 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 – 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 – 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 – 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 – whether that’s by survey, review, focus group or some combination.
- Future-Proof Your Data Infrastructure – 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 – 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 – 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 – 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 remains one of my absolute favorites – 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 – the only thing they want to know (to start) is my gender – 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 – but the result is dramatically higher conversion rates + a delightful customer experience. Jones Road Beauty does the same thing – only they ask about skin type (oily vs. dry) – 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 – increasing margin and customer lifetime value
- Win #3: the data enables a better, more personalized experience for the customer
Finally – 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 <5 minutes) and sit back while they generate a personality assessment preview, upsell that 0P data into a $19.90 downloadable guide (which is automatically generated from existing content) AND use your personality profile to sell you on future stuff, using a communication style and language they are pretty confident will resonate with you (since they now have a pretty good idea of what makes you tick).
The bottom line: in each of these cases, a successful 0P strategy starts with understanding exactly what you need to know in order to dramatically improve your odds of converting that user into a customer (or a lead/prospect/whatever), then making it remarkably simple for the user to share that information with your brand.
Key #2: Integrate that 0P data into your customer journey in a tasteful, relevant way.
One of my favorite examples of this is one that was truly delightful for me: Mockingbird. After signing up for their emails, they’ll ask for your due date – then use that to tailor the welcome email + SMS series. This is a delightfully simple way to collect + action data that would be otherwise impossible to obtain (what 3P data set contains due dates?) but is incredibly important to the overall purchase journey. This is a wonderful example of how a brand recognized a relevant gap in their existing data structure (most couples aren’t thinking about buying a stroller when they are just thinking about their first kid or in the first trimester – but are VERY interested in a stroller in the 2nd/3rd trimester), then devised a simple way to collect + integrate that data into the customer journey. The added bonus is that this data is valuable beyond the actual due date (since many child-related purchases are triggered by the approximate age of the child).
Another fantastic example? Jolies’ water report. In this case, a single piece of 0P data (zip code) is actioned into an automated water report (generated via the EPA’s EnviroFacts API), which is emailed to the user and used to make the need for the Jolies’ filtered showerhead acute. This is another wonderfully simple example of using a relatively small piece of data (zip code), transforming it into something incredibly useful + persuasive (a water quality report) to drive incremental sales.
This need not be only at the outset of the journey, either – both Amazon + Audible do a fantastic job of leveraging 0P data to improve retention rates. In both cases, the cancellation screen prompts the subscriber to provide a reason for cancellation. In Aaudible’s case, it’s whether they’re just not using the product, have too many credits, it’s too expensive or they were unsatisfied with a previous experience. The selection here triggers a set of corresponding “retention” offers, aimed at alleviating the cancellation trigger.
The same logic can be applied to product onboarding and training (something that we did with a Multiple Listing Services (MLS) client several years ago) – prompting new subscribers to input + update their preferences, then tailoring their experience to highlight how a platform can help them do that better.
Key #3: Enrich 0P data with 1P, 2P & 3P data to unlock additional insights + opportunities.
Some of the most powerful insights you’ll glean will come from combining your 0P, 1P & 2/3P data together. This is particularly powerful when you consider the different errors inherent in each data type:
- 0P data tends to be polarized (people who love you + people who are upset tend to give reviews at the highest rates, for instance), over indexes on people who are more likely to intuitively understand your value prop and is volume-constrained.
- 1P data errors tend to be context-focused (i.e. drawing conclusions from a clickstream is maddeningly difficult) and technologically-dependent (i.e. interrupted sessions, making sense of cross-device interactions, etc.)
- 2P & 3P data tend to avoid the audience + volume issues that plague 0P & 1P, but they come with integrity issues (where is this data collected from? Are the people classified as “X” really “X” today?).
For me, this tends to take a few common paths (though detours are equally prevalent):
The “What’s Going On Here” Path:
We’ve all stumbled across the occasional, interesting nugget in GA – maybe users are abandoning a specific page at an astonishingly high rate, or perhaps one particular lander is converting well above expectation, or there’s a particular page path that seems odd (very typical in carts). Whatever it is, it piques your curiosity to a level where further investigation is merited.
My go-to in this case is the on-page survey / user experience survey, combined with a heatmap (I love HotJar, which supports heatmap collection, session recordings + site surveys on a single platform). Combining specific pieces of user feedback with session data makes previously obscure pain points obvious – whether that’s “this copy just doesn’t make sense” or “what am I looking at” or “this really isn’t what I thought it would be” or “I honestly don’t care at all about X – what do you do about Y?” – allowing for quick design pivots that better align your experience with your audience expectations.
The “How Do I Solve This” Path:
On the flip side, there are plenty of engagements where we have a set of features, but no idea which ones appeal to our target audience (basically – trying to find PMF). This is one of those cases where 2P/3P data can be remarkably helpful in understanding several questions, like:
- Where is my audience online? (I use SparkToro for this on a daily basis, along with LinkedIn insights (B2B) and Meta Audience Insights (B2C, sometimes B2B)
- Who should I partner with to collect additional data about that audience?
And once I have that information, it’s possible to do two exciting things:
- Craft angles/offers/value props in ways that are likely to resonate, given the overall profile of that audience
- Validate that via 0P data collection. This can be done by inputting those audience attributes into a survey or data collection platform (Pollfish or Momentive or Centiment), along with the offer/angle/value props to test. I’m a huge fan of forced choice questions, alongside free response fields to capture the “unknown-unknowns” that I’d otherwise miss or simply not know to ask)
The outcome of this is that I now have a data-informed audience profile AND validated messaging to use in my go-to-market strategy.
One example of this that has been wonderfully effective comes from the fintech space, where we (Warschawski) werewas commissioned to conduct a target audience survey (0P data), then match pain points in the surveyed audience to benefits offered by the client via both targeted ads (leveraging 2P/3P + 1P segments) and personalized, 1-to-1 outreach.
Key #4: Continually evolve your 0P strategy.
There’s no data strategy that’s perfect – and even if (by some miracle) you achieve perfection at a moment in time, people evolve & data decays. We’re constantly working with clients to refine our 0P strategy – whether that’s testing new methods for 0P collection, better models to layer data together, or more robust actions + deployments.
The key is to be both your own worst critic and biggest optimist – relentlessly scrutinize what data you’re collecting to ensure it’s what you need to add value to your audience. If it doesn’t fit your needs, stop collecting it and pivot to something that does. That’s often a difficult pill to swallow for brands (who think that “more” data is always better), when the reality is often true – having less total data, but *exactly* what you need in order to deliver a remarkable experience – is actually more (and it’s better).
Zero-Party data is here to stay – and the sooner you can incorporate it into all aspects of your marketing + data infrastructure (that’s data layering!), the better positioned you’ll be to succeed.
The reality (which is both happy for you and sad for the marketing industry) is that acting on Key #1 above will propel your brand into the upper echelon among your competitive set. If you’re able to add on Keys #2 and #3, you’ll catapult yourself into a class of your own. And if you can integrate Key #4 while doing the first 3, you’ll be well-positioned to remain there for the long-haul.