line graph, bar graph, two women looking at data on a computer, large group of people walking and wearing masks in a city, and two males a manager and frontline employee checking on products in a warehouse
June 6, 2022
Data Intelligence

Zero-Party Data Makes Online Shopping Less Scary and More Personal

There is a new party in town…

You’re likely familiar with first-party, second-party, and third-party data. Enter zero-party data.

This data party isn’t necessarily new, but the term was recently coined by Forrester Research and “zero-party” is now a buzzword that is quickly making its way through the retail e-commerce space.

Zero-party might just be the consumer’s favorite party. Here’s why: 

Imagine you are online, shopping for the perfect white t-shirt. Your friend recommended a new brand and when you get to the website, you are instantly prompted to take a True Fit quiz about your measurements and fit preferences. Because your friend has had a great experience with the brand, you willingly share your sizing information for the personalization quiz and answer questions about your brand preferences like “J.Crew” or “Kate Spade?”. These questions about favorite brands (and more about fit) build trust that the shirt will be exactly what you need, especially after reading the True Fit reviews. 

You’ve just experienced zero-party data as a consumer. 

As a retailer, zero-data happens when the customer trusts you and willingly exchanges information for a value proposition. Customers share their information when they can receive valuable content, discounts, access, or gated information, just to name a few. 

We are heading into zero-party growth as more and more consumers become leery about companies tracking their moves online. In fact, dotdigital reported that, 

51% of respondents said they had become more aware of how brands used their data. 68% of consumers were concerned their data would be passed on to third parties for marketing purposes, while 69% worried their personal information would be passed to other companies without their consent.”

Bottom line: Zero-party data just feels more human.

What are the different types of party data?

To put zero-party data into perspective, let’s briefly review the current party-data options from Treasuredata.com:

  • Zero-Party Data: Individual data “intentionally and proactively” shared by customers with a brand that is highly reliable and accurate (Example: customer preferences)
  • First-Party Data: Individual data collected directly by a brand, with consent, through interactions with customers that is highly reliable and accurate (Example: purchase history)
  • Second-Party Data: Individual, indirect customer data given or purchased from a partner that is very reliable and accurate (Example: retailer purchase data shared with a supplier partner)
  • Third-Party Data: Anonymized, aggregate customer data from a variety of sources typically purchased from a marketplace or data aggregator that is less reliable and accurate (Example: customer behavior data purchased from Nielsen or IRI)

There are two pieces of advice that may be helpful when considering zero-party data:

First, keep a pulse on what the consumer really wants.

The way that we collect data is becoming more important to the consumer than ever before. Understanding the data types helps to determine the overall accuracy and reliability of data, as well as privacy rights. Do we want to build trust and loyalty with our customers, or do we want to simply collect as much data and information as possible? As consumer behavior and habits change, so should our data collection strategy. Zero-party data helps solve the personalization versus privacy concern.

Because companies are changing the way they share and collect data – switching from using third-party tools to second-party tools – when consumers happily share their information, it becomes a win-win for both the consumer and the company.

Second, remember that there is no perfect way to collect data.

Keep in mind:

  • Zero-party data may require a shift in the way companies approach their marketing strategy.
  • Zero-party data is precise, but is not 100% accurate.
  • Zero-party data still requires a human element.

Zero-party data gone wrong: Stitch Fix

female with a striped shirt holding a phone and opening a box with clothes

In the case of Stitch Fix, an online personal styling service that uses AI and zero-party data to curate clothing items for its customers, the zero-party data and stylist partnership began swinging and missing in recent years. The data collected from the style quizzes was not always reviewed closely (or at all) by Stitch Fix stylists, leading to customer dissatisfaction with the box of assumed-to-be personalized items they received in the mail. In years prior, the company instructed the stylists to mention the algorithm as the source of the problem, but is now asking stylists to take responsibility for any mis-matched, repeated, or incorrect item selections that resulted from the data science.

“Companies like Stitch Fix that present themselves as tech-forward often face elevated expectations from investors and consumers alike... Yet when it comes to making choices in areas like clothing, tech is less nimble than humans, who are aware of the subtle shifts in trends and understand the emotional response to style, he said. One way to manage customer expectations is to pair recommendations with the reasons why they surfaced.” - RetailDive

It’s important to leverage zero-party data while also keeping a loose grip on the expectation that it can scale all on its own. Zero-party data is a tool, not a siloed data strategy.

Zero-party data gone right: True Fit

two female clothes models with long hair standing or leaning on stairs with fashionable jumpsuits

True Fit is a machine-learning system that serves the apparel and shoe industries to ensure that customers shopping for apparel online will be given the most accurate information about size and fit while also providing social proof to consider. 

First, the customer creates a True Fit “Passport” through any True Fit retailer's profile. The information they share describes what they already wear, their favorite brands, and preferred fit. Second, when they see the True Fit “T” logo on any retailers site, they will be able to shop with confidence that True Fit has gone before them to provide the most precise fit information for their shopping experience.

It doesn’t take long to see how impactful the True Fit partnership with many mainstream brands has been when looking at the lengthy case study page on their website.

“Since the launch of True Fit, ASICS has seen a 150% increase in conversion from product page to cart. He said that translates to a 7.4% conversion rate for True Fit customers versus 2.4% for non-True Fit customers.”

Jason Le Boeuf, Ecommerce Director, Asics

"We are already seeing significantly higher conversion rates with customers using True Fit." (2X  Conversion Increase and 95% Increase Adoption With Email Promotion)

Craig Leavitt, CEO, Kate Spade


In closing, Rhonda Textor, VP of Data Science at True Fit explains why zero-party data has helped the company seamlessly connect the consumer to the products they love: 

“Fashion is too personal to rely on basic data and averaging to predict a shopper's best fit. Fit guidance is served to shoppers in many forms today, from a standard size chart to crowd sizing. Our data and algorithms reveal so much detail about the unique dimensions and proportions of shoppers without that shopper taking out a measuring tape. Understanding their preferences based on what they wear and love gives us the opportunity to turn hesitation into confidence and ultimately trust."

Not sure where zero-party data makes sense within your organization? Meet with a RevUnit data expert for a free consultation.

Understand how to best use party-data within your organization

Asian man talking on the phone holding a tablet with speech bubble icons overlaid

When party-data seems like a puzzle too complicated to solve, our data experts are on hand to help

Speak to a RevUnit expert →
RevUnit icon
WRITTEN BY
Courtney Ulrich Smith
Courtney is RevUnit’s research and design strategy expert. She’s particularly adept at helping large retail organizations and their teams make better use of their data, specifically in the fast-moving world of data visualization. She has a depth of experience, having been a key driver of data-related initiatives inside of a number of Fortune 500 organizations, including Walmart, H-E-B, and others.

Related Posts