Personas @ Disney’s Movies Anywhere

As the UX Researcher on the Movies Anywhere team at Disney, I led foundational research from Nov 2021 - April 2022 to develop 2 personas. I collaborated closely with a designer who aided in research and created the persona visuals.

Note: Insights and deliverables are confidential, but please reach out if you have any questions.

What makes a movie fan?

Movies Anywhere is a platform that enables movie fans to purchase, store, and watch movies from various retailers and sync their movie collections across devices. At the time of this study, the product team was working on an initiative to reframe Movies Anywhere to better cater to our unique users and increase user engagement. This required a deep understanding of our users’ motivations, feelings, behaviors, and needs, but unfortunately, the Movies Anywhere personas were outdated. I led research to update these irrelevant personas, understand how our users consume movies, and build cross-functional alignment about user needs. See Figure 1 for a quick summary of this study and keep reading to learn about my process!

Figure 1. Project summary created in Figma

I designed a survey to understand what users do and interviews to uncover why they do it.

Before beginning this study, I met with stakeholders from product and design to come up with the following research questions:

  1. What are the most common uses for Movies Anywhere?

  2. Why do users watch and/or buy movies?

  3. What impact do movies have on users’ lives?

  4. For those who collect movies, why do they do so?

I leveraged a survey to answer research questions 1 and 2, and interviews to answer research questions 2, 3, and 4. Expand each section below to read more about each phase of the research.

Methods

  • In November of 2021, I began designing the survey. I chose to start with a survey to understand our users’ movie consumption behaviors and the prevalence of those behaviors before diving deep with interviews. I gathered quantitative and qualitative data about users' goals regarding movie consumption, their movie-watching and purchasing habits, their behaviors in Movies Anywhere, and demographics.

    I used a stratified proportionate sampling method with groups divided based on app usage because we had a small group of very engaged users and a larger proportion of less engaged users, but we wanted to hear from a representative group of all users. I estimated response rates based on engagement and worked with our CRM team to send the survey to a random sample of our current users via email. We gathered 296 responses over 2 weeks.

  • In February of 2022, when I began planning interviews, I ran a workshop with team members from design, product management, engineering, data science, marketing, and leadership to identify assumptions and questions we had about our users. This informed the interview protocol and aided in buy-in for the personas.

  • In March of 2022 I conducted in-depth interviews with 7 Movies Anywhere users who fell into our hypothesized persona groups. I chose interviews to dig deeper into why users watch and buy movies, why they use Movies Anywhere, and evaluate feelings related to movie consumption. Interview participants were recruited from the survey and UserTesting. Product designers and product managers were invited to observe interview sessions and also helped with note-taking. After the interview sessions, the observers and I debriefed to discuss interesting takeaways and begin identifying trends.

I used exploratory survey analysis and inductive interview analysis to uncover patterns and build personas, collaborating with cross-functional team members to reduce bias and engage stakeholders in the persona creation process.

I approached survey analysis from an exploratory lens and focused on descriptive statistics to identify patterns of behavior and possible personas. For example, I filtered data by different measures (e.g. reasons to purchase movies) to see if there were distinct groups that emerged. For our use, descriptive statistics about reasons users watch and/or purchase movies, frequently used Movies Anywhere features, movie consumption habits, demographics, etc. were enough to start developing personas. More advanced statistics, like factor analysis, were out of scope but would be interesting to explore if I were to do this project again.

I took an inductive approach to interview analysis. I began by reviewing transcripts and pulling common themes in participants' answers, then coded all data based on the themes that emerged. At this point, I collaborated with the product designer to do affinity mapping with the codes and survey findings to look for patterns in all the insights and start building our personas.

As an additional exercise to reduce bias in our conclusions and build buy-in with stakeholders, I conducted a second workshop with team members from design, product management, engineering, data science, marketing, and leadership to do additional affinity mapping of interview and survey data. The themes that arose corresponded with the themes the product designer and I had identified. This workshop also helped our cross-functional partners get excited about research and have a hand in building the personas that they’d be using.

Analysis

Updated personas were instrumental in shaping the future of Movies Anywhere by aligning teams and tailoring the product to better meet user needs.

We created two updated personas that represented current Movies Anywhere users and focused on behavior relevant to the Movies Anywhere value proposition (i.e. purchasing, redeeming, storing, and watching movies all in one place). Research findings were shared throughout the study during informal updates at design team stand-ups and presentations to leadership. The final personas were presented to the entire Movies Anywhere team along with journey maps based on the data collected during this study to contextualize the personas for our team members.

Going forward, these personas were used as a basis for user-centered design and helped build alignment across teams. These personas were crucial in getting to know who our current users are on a deeper level to better tailor the Movies Anywhere app to our unique users and serve their specific needs.

Findings & Impact

Next time, I'd start with interviews to identify themes before using a survey for validation, but effective communication was essential in achieving success for this project.

If I were to redo this study, I’d consider doing interviews first to identify the themes that lay the foundation for personas, then follow up with a survey to validate that those themes apply to the larger population.

Some challenges arose during this project. First, we faced delays while running the survey. Securing legal approval and distributing the survey proved to be more complicated than initially anticipated, however, I kept the project moving by maintaining transparent communication with all stakeholders. I regularly updated the team on the project status, action items, and upcoming milestones to keep everyone aligned and informed. Another challenge came up during interview recruitment. While the goal was to recruit interview participants from the survey, only a few were available for interviews. To reach thematic saturation, I recruited additional interview participants from UserTesting, screening them to ensure they were active Movies Anywhere users.

My collaboration with a product designer was key to overcoming these challenges and creating effective personas. Through our weekly meetings, regular working sessions, and asynchronous communication, we were able to keep the project moving even in the face of blocks and ended up with personas that helped the team gain a deeper understanding of our users.

Reflection

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My Lists @ Disney's Movies Anywhere