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Sample Study Design: Generating Robust, Relevant Persona Data

All too often we see teams build personas based on passively-collected data (like usage stats, or NPS feedback) or incomplete data (like standalone surveys, or long-held assumptions).

If you want to build accurate, reliable, complete personas—you’ll need authentic, user-generated insights. Real moments, collected from your users' day-to-day lives, will stick with stakeholders, and make your personas more dynamic and representative.

Moments-based methodologies allow you to gather “sticky,” imperative info from your users (like their life goals, and value systems). They help you reach participants during banal (but imperative!) moments that, over time, paint a complete picture. This can include garnering a better understanding of their:

  • Behavior
  • Attitudes
  • Perceptions
  • Motivations
  • Outcomes
  • Context

Personas work conducted remotely should focus both on behaviors of interest (e.g., moments when you’re using product/experience X) and peripheral moments (e.g., moments when you’re thinking/feeling/doing X). With this approach, you’ll be able to combine classical demographic data with rich, contextual, qualitative data.

Pair usage data with evaluative feedback and you’ll make personas even more accurate and rich.

A sample study design:

Most the persona studies we see done using dscout home in on a behavior or product category of interest (e.g., booking travel) and attempt to build context, texture, and understanding the factors surrounding it.

This is typically born out in a classic three-part mission design.

A note: we definitely think of remote-mobile research through a “dscout” lens—but you may be able to simulate this study design with other tools.

Some dscout specific vocab to be familiar with, in case you’re not a user: we call our research participants “scouts” and our studies “missions.” Missions can be separated into different “parts”—and scouts can complete each part once, or multiple times. This allows for easy experience sampling.

Part 1. Introduction: Getting to know the scouts more deeply

This opening part focuses on understanding your participant’s history, experience, or interest in and around the focus topic. Use dscout Live (or another interview tool of choice) to collect essential background information.

Example interview questions:

1. When you choose to travel for enjoyment, what is the primary reason for it?

2. List a few of your primary sources for searching and researching travel destinations.
3. Who do you typically travel with, and why?

Part 2. Behavior: Moments of interest or focus

In building your personas, you'll want to build segments based on realized behavior and motivations. Here, you can leverage multiple entries (or moments) focused around a behavioral trigger.

Example prompt/trigger: “Complete an entry every time you consider booking a trip—near or far. This could be a train ride away to visit family for the weekend, or an international trip you’re planning and saving for.”
Example questions:
What are you researching in this travel moment?
What resources are you using?
In a video, show us what you're trying to accomplish and why you chose that resource.
How often do you typically engage in this research behavior?

Part 3. Reflection, ideation, or co-creation

With moments of interest captured, you can leverage the "top-of-mindedness" of travel booking (or whatever your experience focus is) to solicit feedback on a concept, focus them on your product, or ask how it could be made better.

Example questions:
In one word, describe [Brand/Product X].
In a video, tell us why you chose that word.
What one feature does your ideal [Category/Product] have?

Many persona studies will explore secondary and tertiary behaviors that may influence behavior with/on an experience, factors such as:

  • Location
  • Family/friend influence
  • Motivations to use competitors and/or alternatives
  • Perceptions of the specific industry
  • Rationale for continuing or shifting category behavior

In this way, personas are both broad and deep, while still anchored in the lived experiences of your users. When you layer this with back-end or passively collected data on usage from your development and engineering teams, you’ll create a lived, and soundly grounded, persona set.

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