Point is a new app that uses insights from your wearable devices to provide specific fitness recommendations that help you make the most of your metrics. Last year, Point tapped our team to create their iOS app and recommendation algorithm, bringing their vision to life.
Offering personalized, dynamic fitness advice
When our teams got together, Point expressed their desire to write and deploy countless actionable fitness recommendations for users. This content would be based on specific metrics like heart-rate variability (HRV), sleep, cardio activity, and more, collected from wearable devices like Apple Watch, Fitbit, Garmin, and Oura Ring, and apps like Apple Health. It looks something like this:
To get there, our data scientist, Arun, and developer, Lucas, needed to build a recommendation engine that would analyze an individual’s metrics and behaviors, then generate specific insights and recommendations that would then be delivered to the user.
Building the recommendation engine
The core component of the Point product is users’ health data. As soon as a user’s device, like their Apple Watch, registers a new data sample, it connects to the Point app, which uploads the data to its internal servers.
The servers analyze those inputs and crank out specialized insights, which move to the recommendation engine.
Then, the engine parses and assembles a user-friendly interface based on the insight, tying together 3 components that are written and stored in a CMS:
- All of the text the user sees on their screen, including their health metrics & insights
- The specific recommendation content (a type of exercise, rest, a meal, etc.)
- Call-to-action content (the button below the recommendation)
This architecture worked well, but Point wanted to ensure that its recommendations would vary to keep users engaged and motivated. So every time a user’s HRV decreases by 50%, they receive new tips to optimize their energy and performance.
A few templated recommendations were written by the Point team initially. The problem was that each time they had an idea for a new recommendation based on a metric already in the database (like the 50% decrease in HRV), they’d have to ask Arun and Lucas to add it instead of doing it themselves.
Our DevOps team realized that as Point grows, it’d be essential for them to update and add content independently using a CMS.
Enter Forest Admin.
Creating new content seamlessly
We chose Forest Admin to create Point’s admin panel, where the Point team can now create new user-facing content at any time. Forest Admin was the perfect choice for a few reasons:
- Seamless integration: Forest Admin runs into Point’s servers and databases to collect and store information using the infrastructure we already built, so there’s no need to set up a separate database, server, or API. The Point team can write new content in the Forest Admin panel and connect it to the data and insights already stored in their servers.
“We have a product offering that’s rooted in biometric health data, digital content, and data science, yet we’re an early-stage startup that also needs to experiment and iterate quickly. Forest Admin’s CMS allows us to do that because of how seamlessly it integrates with our core architecture.”
–Kingsley McGowan, CEO of Point
2. Quality performance: Since both the database and CMS are handled internally, the latency involved in connecting the two is dramatically reduced, and content updates and additions can be made quickly. The admin panel’s flexible, customizable features make it intuitive and straightforward to use.
3. Security: With both the CMS and database servers managed internally by our DevOps team, we can ensure that users’ personal health data remains secure. It doesn’t need to be sent around to third parties.
“The UI/UX within Forest Admin allows us to iterate on copy and content while ensuring that if we have any changes, everyone on the team is empowered to do so. If I had to do anything differently, it would be to use Forest Admin sooner.”
Forest Admin helped us build a customizable and flexible platform for the Point team to write and serve recommendations to end-users. The platform also complies with our development team’s initial constraints around architecting the recommendation engine.
But it’s not limited to that. Point can use this same structure to abstract several messaging and marketing strategies.
Right now, Point’s content exists within its app, but Forest Admin’s flexible admin API could eventually help Point leverage push notifications, SMS, emails, and other forms of messaging to bring customized content to users outside of the app.
Instead of traditional calls-to-action that rely on buttons and URLs, the team is also considering incorporating additional media components like video streams, podcasts, webinars, and more using Forest Admin.
We’re excited to see how Point grows and helps people make sense of their health data!
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