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Healthy Habits

A self-guided, flexible behavioral change model that provides a personalized dynamic experience to enrich the user’s knowledge and capability to change their daily habits (habit-forming feature).


 

Phase 1

Low-fidelity: Concept Creation

As the lead mobile designer, I created low-fidelity designs and prototypes to test the discovery of the program. Currently the mobile application gives users access to 8-10 additional features to keep the users engaged throughout the year. We wanted to ensure that the enrollment steps were clear for the user to understand the guidelines of the program.

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We sketched screens and created user flow-patterns that would help users discover and navigate easily to their personalized self guided program.

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To gather feedback, we held usability sessions to better assess the discoverability of a program and to minimize the number of enrollment program steps. The test scenarios were based on returning and new users that visited the member platform. The process had to be simple enough to keep the user engaged until they reached their tailored dashboard. Using data from our Health Assessment, we were able to show users a recommended program based on their results.

 

 

Phase 2

Usability Testing: Discovery

The goal of usability testing is to identify any usability problems, collect quantitative data on participants' performance (e.g., time on task, error rates), as well as determine user satisfaction within the application or product.

What We Wanted to Learn:

  • Does the user understand how completion of the health assessment (or a module) drives the recommendation of a digital self-guided program?

  • Can the user identify what program is recommended to him or her?

  • Can the user navigate to a digital self-guided program and enroll?

 

 

Phase 3

Refined Concepts (tested with users)

Based on the data from Phase 1, we reduced obstacles or user frustrations. It was important to keep the elements and interactions that users preferred as well as to understand technical constraints. These iterations were tested with new users to validate assumptions and get direct feedback.

 

Key Findings/Takeaways

Did users start their recommended program?

  • 10 out of 10 users preferred the Jennifer view

  • 9 out of 10 preferred bottom tabs

    • This was more from a UI preference. Users found the design “simplistic” and “personalized.”

  • 4 out of 10 understood the HA drove recommendations

  • 8 out of 10 users could NOT identify “Achieving Your Healthy Weight” as the recommended program

    • “It looks more like a headline. I’d put a colon after program.”

    • “It says interested in another program. I haven’t seen a program yet. How do I see my program?” 

      • Facilitator: “Do you know what’s recommended for you?”

      • User: “Do you mean what’s recommended goal wise? Achieving your healthy weight. Maybe, that’s what I chose as my #1 goal.”

  • 2 out of 10 users did NOT select Get Started on the recommended program

  • Of the 8 that selected “Get Started”:

    • 0 out of 8 did NOT select after clicking “Viewing Recommendations” and seeing Achieving Your Healthy Weight on the page

    • 1 user had to reopen the prototype

    • 4 out of 8 selected the “Achieving Your Healthy” program

 

 

Phase 4

Hi-fidelity + Iterations

The team gathered the user feedback and data to refine the concepts for stakeholder review. After their input, we finalized the designs and presented the high-fidelity version to the developers and product managers. In this process, the team was able to develop a stronger phased approach for the product team based on user needs.