Case Study:  

A mixed methods approach to
building personas





Project Type: Research, Persona Study
Product: Consumer app & website
My role: UX Researcher 
Team: 3 Researchers, 1 Principal UX Researcher, 1 Data Scientist
Duration: 1 month

For confidentiality reasons, I have omitted or obfuscated restricted information. All information in this case study is my own and does not necessarily reflect the views of ClassPass. While I can't share certain details of the research and deliverables, I can speak to my process and the general project scope.

Project Background


ClassPass consumer iOS app

About ClassPass

ClassPass is fitness and wellness subscription service that allows you to book classes at boutique studios and gyms at a discounted rate. Since launching in 2013, the company iterated through different business models in pursuit of healthier margins and long-term sustainability, ultimately landing on a credits-based system with dynamic pricing (think airline pricing). 

ClassPass constantly rolls out new features and offerings.

It’s a competitive market

The fitness app market (and really anything fitness-related) is booming. To retain and increase membership, ClassPass needs to continually improve and evolve. Efficiently solving user needs with well designed digital products is key to their success. 

The Goal: Understand your customer

Knowing who your users are and what problems and challenges they face is integral to creating useful and desirables products.  When you start hearing a lot of “We think our users do this” or “I’d like this” around the office, you know it’s time to talk to actual users.

The Research

A mixed methods approach: a little more science and a little less art

With over 55 million reservations booked to date, ClassPass has a lot of information on where, when and how customers are using the app (or website), but they don’t know all of the whys behind the numbers.  To mine actionable insights, my research team employed a mixed methods approach grounded in quantitative behavioral data.

Study overview

  • Participants from 4 quantitatively derived clusters 
  • Data from pre and post interview surveys
  • 29 user interviews
  • Synthesis of qualitative data through affinity mapping
  • Iteration of cluster approach through attribute comparisons
  • Development of 4 core personas
  • Presentation of findings and recommendations to cross-functional teams

Recruiting the "right" users

Working alongside a data scientist, our research team refined user criteria based on four clusters groups previously identified through cluster analysis to ensure that our interviewees were indeed representative of actual users.  To further screen participants and collect additional pre-interview information, we deployed a questionnaire.


Our research team recruited and interviewed a total of 29 people. Each interview was one hour long. The majority of interviews happened over video, although several NYC based users came in for in-person interviews.


When n=29

The initial plan was to affinity map within the four cluster groups-- one affinity map per cluster group with a focus on behavioral differences as opposed to demographic differences. 

Post-its for just 7 out of 29 user interviews 

Sorting ideas and information into groups

Sifting through the data proved to be a daunting endeavor. The first attempt to make sense out of this overwhelming mass of sticky notes failed for two reasons: 1. There wasn’t enough pattern overlap in the initial clusters, and 2. There were 2,500 post-it notes.  We regrouped by literally regrouping the clusters.  

Iterating on the approach

We created an "attribute tally" spreadsheet to track salient data points across the 29 interviewees. The resulting document tracked over 20 user attributes, from age to workout schedule. By coding these data points, we could more readily determine key variables that differentiate segments and extract nuanced patterns.

Quantifying qualitative data by coding behaviors and comments


Data-driven personas

Convincing, representative personas speak to known and unknown user pain points and opportunities. The four user personas that emerged from our research findings captured the motives, behaviors, goals, priorities of ClassPass users.  Each persona artifact included a short narrative from the persona’s perspective, providing both depth and personality.

Specific personas details are not available for view due to NDA.

Data-driven personas as an efficient, research-led method for better understanding our users.

Each persona represents a significant portion of ClassPass users in the real world, enabling product designers to focus on a manageable and memorable cast of characters.

Communicating Research

Presentation matters: Transferring insights and knowledge

I find presenting work to be both immensely satisfying and completely daunting.  Satisfying because you're finally able to share something tangible and actionable for your efforts; daunting because startups move at a fast clip (and humans generally have limited attention spans), which means you need to capture your audience's attention early and keep it.  Knowing this reality all too well, we relied on storytelling and visuals to convey findings and insights and saved the nitty gritty details for the research report. Quotes from user interviews were particularly impactful and led to many follow up questions and animated discussions.


Pull quotes gave life and validity to our findings.

The presentation was well received. The deliverables, particularly the personas, are being used to brainstorm and prioritize features.  They are also helping to define product strategy. To ensure that our research lived on, we created a file repository where product and marketing team members could go to quickly access high level insights, individual observations as well as raw research data.

Learnings & Takeaways

Making research visible

Affinity mapping is a great tool when…

  • You are confronted with many facts or ideas in apparent chaos
  • Issues seem too large and complex to grasp
  • Group consensus is necessary

Question: But what happens when you meet the affinity mapping criteria and your total post-it note count is in the thousands and you research area looks like this?  

Answer: It depends.

If you are looking to uncover patterns and new insights or to build consensus within your team, consider either working with a smaller subset of the research or switching over to a digital tool that won’t be constrained by available surface area.  The act of physically organizing and labeling generates useful discussions. By having a physical place for your data and observations, you can literally step back and see the big picture. By going digital, data points and findings are more easily managed.  The trade off is that many of the benefits that come from being a physical, tactile process will likely be diminished. 

However, if you want to pique curiosity, spark conversations, and expose more people to the benefits of UX research, post-it notes are the way to go.  When a centrally located, glass-walled conference room is suddenly covered in post-it notes, people take notice and start to ask questions. Engineers, customer experience specialists and even the company founder stopped by to find out more about what we were doing.  By making our research visible, we introduced more people to the research and made them more interested in our findings and insights.


Special thanks to my fantastic research team: Pat Glass, Jane Richardson, and Sam Place.