In order to improve a person’s life and wellbeing, we can focus on a couple of things: health and fitness data, nutrition and drugs / supplements. Companies that work in this sector, independently of what vector they are targeting, usually don’t give any recommendations, insights or actionable tasks. Even when they do, these are not tailored for specific individuals. If we pick a company that works with Nutrition, for the most part you will get generic recommendations. For example with magnesium ingestion, the recommended daily dosage for male adults is 400-420 mg. That’s likely what you will get once you input your age and sex. This is better than nothing, and for a large chunk of the population this will suffice.
There are two important elements when looking at these vectors: cost and convenience. Buying a $80 Fitbit tracker is both cheap and easy to use. Doing a blood test to measure multiple biomarkers can be costly and can take a couple of hours to go through the whole ordeal. Convenience is also about how easy, or difficult it is to measure something. Going for a run with a Garmin watch on your wrist is easy. You tap a couple of buttons and you are done. Tracking food macros is the opposite. I still have my kitchen scale to weigh my chicken breasts, but I have stopped doing so after a couple of weeks. Glucose monitors, something that diabetics rely on, are not cheap, but they are becoming more convenient. A Freestyle Libre sensor can last for 14 days and you just need to tap your phone on the sensor to read the value. Scales have as well gone a long way. You only have to get on top of them, wait a few seconds and the measurement is available in some app. Highly convenient, even if the price is a bit steep. Taking supplements is for the most part convenient, if you don’t forget to do so. The price can be steep, depending on what you are ingesting. The cheapest Omega 3 supplement at Amazon.co.uk costs £5. Carlson’s Wild Norwegian Omega 3 supplement costs £40. Not all supplements are made the same and there’s an important educational component that companies often ignore.
There are a couple of reasons why fitness trackers are so popular these days. They are cheap, convenient and provide ok-to-good fitness and health data. There’s also an element of status signalling - for this post that component is irrelevant. As I wrote yesterday, most companies or apps don’t know what to do with this data. I wish I could further expand on this, but it’s difficult. They manipulate data to show nicer graphs, but for the majority of the population this doesn’t add much. Apple is one of the culprits with the Apple Health app. There’s no real insight derived from the vast amount of data they have. My hypothesis is that incentivising more activity is already a good thing - and I agree with this. Does it really matter for a sedentary person that they should compensate their cardio with some strength training? Maybe, but surely the first step is to make them move. Having some small goals (e.g. rings in the Apple Watch) can be a great way to make people work for them. However, these goals aren’t smart - they are manually set by the user. This is a missed opportunity and something that Oura does well. It not only adjusts this value based on your profile, but also how well you slept and what are your goals. If you had a bad night’s sleep, Oura will encourage you to take it easy the next day. The Oura app will also change its UI depending on what your goals are. Companies that operate in the B2C Health and Fitness sector will struggle, if they don’t provide this level of individual customisation.
At the first level you find companies that only display data - the app store is flooded with these. Yours truly has one there as well - Dash. I use it every day and I love it. Although it does display data in a far better way than what Strava does, it doesn’t do much more than that. I guess this goes back to Apple’s approach. Perhaps if one can nail data visualisation, that in itself is already a win. I suspect that we might be at the cusp of moving on to Type 2 applications and services, I am just not sure about the trigger. Perhaps better ways to generate ML models, without the need of massive amounts of data?
Using a tracker is both convenient and cheap. A Fitbit tracker can cost as low as $80, while a used Apple Watch series 6 can cost $200.
The next step is providing insights and recommendations. Based on the time you wake up, the HRV, hypnogram and age, companies can tell what’s the ideal time for you to go to sleep. Companies that are capable of doing this have a clear advantage over the ones that don’t. Knowing what’s the impact of doing something is what a lot of these companies miss. What’s the added benefit if I walk 5k more steps on top of the 10k I already do? What do I gain from sleeping well every day? There’s also an educational component that is missing. Companies can go a step further and allow the user to add extra metadata to both activity and sleep. For example, Oura allows you to assign things like “drank alcohol” to a day. It then tries to correlate that every time you drink alcohol you have a bad night’s sleep. There’s still high convenience at this level - since you only rely on a tracker. But it can get expensive quickly. An Oura ring costs $300 plus a monthly subscription. Not a lot of people are willing to pay this.
A Type 2 company provides concrete actions for the user to do. If you do X, you will see an improvement in Y. On the other hand, there’s a regulatory angle. My hunch is that companies might be avoiding providing actionable items to a user so they don’t have to go through the process of becoming a certified medical device. What if a recommendation leads a person to ingest too much of a particular supplement? These and similar scenarios might make companies nervous about what exactly they should provide to the end-user. This might be the barrier that keeps a lot of companies at Type 1. However, I am more inclined to think that most companies don’t know what to do with the vast amount of data they have.
Here we find companies, or services, that mix multiple vectors and provide a holistic view of your health. For example, they can look at your health and fitness data and combine it with your nutrition. I don’t know a single company that does this well enough and is a) affordable and b) automated. My hypothesis is that this is where the holy grail for a lot of companies is. But nutrition is just one among a few vectors. A company can take a user’s existing health data and extend it with blood tests. This further enhances their view of how this individual is doing. The only people that can do this well are personal coaches or niche companies. They can look at all this data: fitness and health, nutrition and blood results and come up with a plan aligned with the individual’s goals. The current obstacle is that this is mostly manual work. But also expensive and time consuming. Very few people can afford to do this - elite athletes are good examples of people that pay for this kind of service. At the level of people like Cristiano Ronaldo and others, these are measured: nutrition, health and fitness data, genetics, blood tests, mental health, environment (e.g. air quality, humidity, elevation) and potentially others I am not even aware of. For every small change in one of these, his protocol is tweaked.
Bryan Johnson is perhaps the most famous person on Type 3 with blueprint. But notice that he spends 2 million dollars per year. There’s room to reach Type 3 without spending this amount of money. But I am unsure how many people would a) benefit from this b) are willing to still pay a non-trivial amount of money c) have the discipline and time to go through with it.
Finally, blood tests these days are also becoming a commodity. You can pay $100 to get a package at home, draw some blood, send it back in the post and wait for the results. Companies like Thriva do this for years. They will then recommend supplements and additional tests based on the results you get.
The fourth level is the automation of Type 3. Driving costs down and convenience up.
As far as I am aware, there’s no one here.