This is the continuation of “UX of Onboarding: PLG Series” where I do teardowns and discuss user onboarding onboaring UX.
As a fitness enthusiast, I tried Asana Rebel onboarding and loved the initial visuals and personalization!
It felt engaging and tailored to my needs.
However, I found the body fat percentage question using a slider and illustrations (15–40%) a bit off and risky more to say.
It relied on subjective perception, which might lead to inaccurate answers and even discourage some users.
Why I felt so ?
My gym friends and I were curious about each other’s body fat percentage. We tried guessing, even poking a bit (don’t worry, gently!), but our estimates were way off.
Even when I shared my actual percentage from a checkup — 15%! — no one believed it.
This made me realize: judging body fat based on looks is super inaccurate. People see things differently.
Here’s the Case:
The onboarding process asked me to estimate my body fat percentage using a slider and illustrations ranging from 15% to 40%.
Please see the interactions below:
While I have some suggestions for visual improvements, this approach poses a more significant UX challenge.
As a designer myself, I appreciate the difficulty in gathering accurate user data. However, relying solely on subjective perception, especially when users might already have a calculated BMI, raises concerns.
Asking for a guesstimate based on illustrations could feel awkward and lead to inaccurate data, ultimately impacting the efficacy of their personalized workout plans.
Wouldn’t it be better to:
🤔Ask if they already know their body fat percentage (from BMI or body scans).
🤝Offer alternative ways to gauge fitness level, like activity level or goals.
👌🏻Provide educational resources on estimating body fat accurately.
This approach would be more user-friendly and provide more reliable data for personalized workout plans.
Overall, great job on the onboarding flow and personalisation!
But, I believe refining the body fat input could significantly improve the user experience.
Question for Asana Rebel product team: How do you address the accuracy concerns around the current body fat percentage estimation method?
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