Apple is launching Fitness +. What the hell, man?

I think there’s a couple of things that we know about Apple Fitness + already. Having basically never seen the service, read a review, or knowing anything besides that it ties into the Apple Watch. We know, that on day two, it will very likely to be a third of as good as the 2.0 version will be while also being better than it deserves to be. By version 2.0 they will steal a photogenic and charismatic instructor or two from Peloton and generally have a competent service. After its soft relaunch, their new processors will lead to visual analysis better than the competition and they will have a solid, if relatively meaningless couple billion dollar business. So I say this with an understanding of the possibilities. “What the hell, man?”

For a moment, forget about the Good people that run the companies that make the products we love and think for a moment about what would be true if merely Ambitious people ran those businesses instead. Apple is a company that charges its ecosystem 15-30% of their revenue if Apple believes Apple did meaningful work to contribute to the generation of that revenue. Lightning connectors, the App Store, the dongle life, it’s all based on making their 15-30%. Collecting payment on every new workout machine built to at least nominally interact with Apple products - there’s certainly opportunity there. That’s especially true as Apple’s hardware gets more sophisticated and measures more things. More sophistication means more API calls, which means, for Apple, more money from anyone who might want access to read it, to write to it - at a high margin. So there’s a potential business model. So why have your own service? Data.

Netflix, once, was considered a data run organization. They were supposed to know about how long subscribers paused to view a trailer, how long they perused before viewing. Every beat, every second was supposed to make the Netflix content machine run better. But TV watching is communal. Preferences are often stated, not revealed. And devolution to the lowest common denominator is frequent (although I have thoroughly enjoyed watching Boss Baby at dinner). Combined with humanity’s fickle pop culture interest even with all that data, Netflix’s second season renewal on its TV shows is merely average for the industry. It’s Emmies per content dollar spent was almost always below pre-ATT Warner Media/HBO. All that data and it’s only exceptionally ok at what it does. Fitness though seems different.

As I pedaled through minute 35 of my last workout, it occurred to me just how much Peloton knows not just about me, but their riders in various aggregates; as a whole, as a city, as a region, as a stratified economic group, as a multicultural entity. And the quality of what they know is supreme. It’s not based on stated preferences, but preferences revealed by behavior. That behavior isn’t measured in a communal setting where pretense or situation may impact the choice, but extremely privately, with high intention and low stakes. Further, the user has the ability to iterate, to reveal unhappiness in the moment (drop out of a class and start a new one) and through a change in behavior over time (never take that instructor again). And all of that action is recorded.

During Covid times, my wife knows where I am 100% of the time, but she doesn’t know how hard I’m working out on our stationary bike and why. Peloton might know that better than I know myself. In a quick brainstorm, (minute 38 of said workout - Matt Wilpers needs better music) I reasoned that Peloton knows:

  1. By crossing workout data with weather data they know precisely when people give up on their outdoor workouts for indoor ones. Maybe it’s rain, maybe there’s a temperature threshold. Maybe there’s an anticipation of better whether modifier. 

  2. Whether morning workouts are generally as strenuous as evening workouts and who is doing which (observed output)

  3. What music gets the best output from which people and whether variance improves that. (music monitoring)

  4. How the news impacts views on race. (Correlating instructor selection with news events)

  5. How exercise frequency and intensity leads to injury (stretch/yoga vs workout)

  6. Depression trends (low intensity vs normal, class selection)

  7. Sickness trends (who shows up, low intensity vs normal)

  8. Who our friends are (Facebook tie-in and follower/follow count)

  9. How we identify and who we care about? (Hashtags)

  10. How much we will support perfect strangers. (High five giving and response)

And they can vary it across geography, across age groups, across ethnicities, across economic wellbeing. Whether they currently analyze all of this or not they have the data, and as users of the service, its not data we can restrict them from knowing if we want to get into better shape. It’s heaven for a data scientist. It’s not great if you value your privacy.

With Fitness+, Apple is about to start on the journey to having all of that data as well. While I like Tim Apple (that joke only has about a month more to live), and think he’s probably a great person….that’s a lot of data now in the hands of a company that knows a lot about you and as they expand into other services is going to know a lot more. A lot of data that’s valuable to militaries, to politicians, to insurance companies, to advertisers, to a lot of different people. Whomever at Apple came up with the service to begin to collect that data is pretty smart, even if current leadership is unlikely to use it. He or she probably deserves a promotion…

Thanks for reading

Basil

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