Eva and Josh learning card:
- We believed that: AI would not be harmful to our customers and help create workouts through insights
- We observed: 1) Customers like AI giving them a “rough idea” to track activity; customers would definitely use data if it improves the customer’s performance and efficiency. 2) Customers would trust an AI over time if the results are accurate and the risk is big enough. 3) If AI tells them to stop when there is a risk of an injury, customers listen because they know the severity of the injury
- From that we learned that:
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- For actionables, users want the AI to move beyond generic tracking to provide specific targets and reasons
- For all users (runners, lifters, casual players), the value of AI was protecting their ability to perform long-term by preventing catastrophic injury
- AI was viewed as the or “shield against harm”
- Users were willing to compromise or ignore general advice, but showed immediate adherence to high-severity alerts
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- Therefore, we will:
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- Emphasize in marketing that the AI is a single source for precise numbers needed to achieve high goals
- Invest effort into guaranteeing the accuracy and reliability of the high-severity warnings
- If this fails, users will not trust the AI, which may lead to an accidental serious injury, which would also lead to them to blaming our product for the injry
- Ensure the AI clearly distinguishes between negotiable advice vs. non-negotiable safety alerts
Anthony and Eduardo learning card:
- We believed that: Users would love seeing their workout data and clearly see the value of the AI coach
- We observed: 1) Multiple users asked “Does it give me workouts, or just my data?” and “I’d want to see it in action,” signaling confusion about the AI piece. 2) All 3 users were unsure of what the AI insights were actually telling them as compared to the data. 3) When shown the coach area on the right, users said it should be “way more” prominent and suggested a weekly summary with clear next actions.
- From that we learned that:
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- The core value (AI guidance) wasn’t discoverable; data displays alone aren’t perceived as unique.
- Users need explicit, immediate “what should I do next?” recommendations tied to their goals.
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- Therefore, we will: Make the AI coach the hero
- Emphasize goal-driven, personalized guidance as the core promise.
- Present raw data as a drill-down that explains and justifies the coach’s recommendations.
- Highlight that the “smart” part is turning data into decisions, not just tracking.
Jason and Estella learning card:
- We believed that: Users would enjoy a social and community aspect to their workout tracking
- We observed: Both of our interviewees compared the activity tracking feature to Strava
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- There is interest for smaller family/ friends groups in addition to the broader community
- An interviewee noted that today there is data overload and many different apps and devices for tracking fitness and it would be nice to have one centralized space with everything you need (like our AI powered insights and social feature in the same app)
- “Club” identity associated with wearing our hardware makes sense and is appealing
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- From that we learned that:
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- Differentiation must be clear; otherwise we may be branded as “just like Strava”
- Users may be more motivated by intimate accountability rather than just the broader community
- To stand out make sure we turn “data overload” into clear, actionable steps for our users and that our users are not overwhelmed with metrics
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- Therefore, we will:
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- Lead with and emphasize what makes us different – an intelligent, all in one platform that transforms data into direction – and also make sure that our social feature has differentiating features than Strava, such as the “milestone” tab
- Ensure that users can create their own intimate group circles to post and share their workouts with, in addition to the broader community
- Emphasize the “next steps” aspect of our AI coach, giving users exactly what they need to know to make progress instead of flooding them with information they don’t know what to do with
TEAM SYNTHESIS
- It’s critical that we lead with the AI coach as data alone didn’t feel differentiated or valuable to users. We need to clearly showcase the coach’s personalized insights and next actions, with data supporting (not overshadowing) those recommendations. When the “smart” guidance is front and center, users better understand the product’s unique value.
- Social features need to be a clear and core component, not appear like a later feature that was tacked-on. We should design with social interaction as front and center and leveraging users’ desire friendly competition to drive engagement. Concretely, this means making social groups more intimate (friend circles as opposed to broader public, for a “club” feeling), and social encouragement more incentivized (make each user’s “milestones” more visible to their friends, and enable kudos/likes)
LINK TO TRANSCRIPTS
https://docs.google.com/document/d/1uonnBk15ax5f-Z40IsvXiZOMzdTnarehVceKAlHEa64/edit?usp=sharing
