Personalization Benefits of Zero-party Data
Optimized onboarding, better engagement, and identity resolution.
In the previous post, I covered the common use cases of zero-party data for B2B and B2C. Today, I’m covering why zero-party is key to building hyper-personalized audience experiences.
This is an excerpt from a guide originally published on the astorik learning hub →
Leveraging zero-party data for personalization workflows is a no-brainer. But what does it mean to build personalized experiences? Surely it’s more than just using liquid tags in event-based emails or delivering offers disguised as birthday greetings.
Users, especially the savvy kind, are able to tell when personalization is done well. And they also understand that true personalization requires them to explicitly let brands know who they are and what they need.
The benefits of zero-party data in terms of personalization are plenty but I’d like to focus on the ones that brands just cannot ignore anymore.
An onboarding survey asking new users their primary use case for the product and the expected outcome, as well as professional (B2B) and personal (B2C) info, is the most reliable way to personalize the in-app experience and deliver relevant communication. This is not something that can be deciphered accurately based on usage data (event data that’s collected implicitly).
And not asking what one intends to use the product for or what their goals are is such a missed opportunity. Moreover, onboarding is not a one-time, set-it-and-forget-it activity.
Collecting preference data early in the audience journey and giving users the ability to keep their responses updated helps brands understand the changing needs and priorities of their diverse audiences. And doing so is key to delivering experiences that remain personalized through every stage of the journey.
Engagement via relevant content and communication
Leveraging zero-party data in conjunction with first-party data for personalization efforts is a lot of work, but it’s also a proven method for hyper-personalization.
Here are a couple of everyday scenarios:
In B2B, a power user is quickly assumed to be a prospect for an upsell. However, that power user could also be using the product on behalf of her clients, making her an ideal candidate for a channel partner.
Proactively finding out her use case and labeling her as a prospective partner in the CRM (or even onboarding her as one) helps deliver content and communication designed for partners, leading to a truly personalized experience.
That’s not all though — excluding her from engagement campaigns meant for power users who are actual prospects for an upsell positively impacts the outcome of those campaigns.
In B2C, it’s almost always assumed that if someone buys a certain product, they’d be interested in buying more of that product. It’s taken for granted that everything you buy, you buy for yourself — how many brands even ask whether the product you’re buying is for your own consumption or for someone else?
After all, it’s not uncommon for people to buy things for others (as a gift or otherwise) that they would never buy for themselves.
Therefore, asking the buyer deliberately who they bought a certain product for, and whether or not they’d like to buy a similar product again not only helps deliver relevant content and communication, but also minimizes wasted effort on campaigns that only take past purchases into consideration.
These are just two of the many examples where collecting data explicitly from the zero party or the end user can lead to much better personalization.
You might ask what zero-party data has got to do with identity resolution, to which I’d say “resolving identities using data collected explicitly from end users is more accurate than relying on algorithms powered by first-party data that’s collected implicitly as a result of user activity.”
Here’s an example that’s rather common in the B2B world:
I use a popular productivity tool where I used my personal email address to create the account. Due to the popularity of the tool, it’s also adopted by the organization I work for and I receive an invite on my work email to join my organization’s account. Upon joining, I’m put through the onboarding meant for new users even though I’m actually well-versed with the product since I’ve been using it for my personal projects.
Sounds familiar? Notion and Make come to mind first but there are many such products.
If only at the time of onboarding I was asked if I’d already used the product before, my experience could have been tailored to the needs of someone who has been using the product in single-player mode and is familiar with the core features, but is now going to start using the product as part of a team and will have access to collaboration features that they might not be familiar with.
Assuming the above was actually implemented in the onboarding flow, the brand now knows that I’m an existing user and all they need to do to resolve my identity is to ask me for the email address I use for my personal account. In fact, they also have the opportunity to go a step further and proactively ask me if I’d be interested in contributing to their community or joining their partner program.
Incorporating zero-party data in your workflows is sure to bolster personalization efforts while also giving more control to the end user — giving them a seat on the decision table and letting them decide how much personalization they’d want.
As you can tell, I’m going all-in on propagating the adoption of zero-party data — not just the term but also the practice of collecting and activating it.
My thesis on audience data is far from over and in fact, I have several pieces in the works on topics like:
The freshness of zero-party data
Zero-party data is complementary to first-party data
The consequences of ignoring zero-party data
The role of zero-party data in building a thriving community