Current wearables and activity trackers suffer from a fatal flaw

Tracking is only one first step

All wearable are purchased for tracking data. They do it pretty well. But the user is not satisfied by just collecting data. He wants to draw conclusions out of it.

We know our past already

Sport portals offer athletes only historical views from uploaded workout data. Done this we have a clear view of the past, but in fact we know already from our own experience the past. We are more interested about the now and the future. If we search for features in those portals, we find nothing helpful.

"Celebrate each moment of the present before this present turns into the past."
Ashish Sophat

Customers want more

The killing feature would offer the user a prediction based on several main impacts on a daily basis: health, stress, recovery, nutrition, weather, gear, workout and activity data.


Current health, fitness and running applications are highly specialized on tracking one input.
But even if future applications manage to reflect all inputs, there are still factors that are not entirely caused by the past and there are factors that are not measured and analyzed.
Last but not least we can only influence a subset of these impacts.

To develop insights and apply them to future training we must establish predictive analysis of data.

Let us analyze the past, the present and the future

This is easy said. State of the art is to tracking and evaluating the data from the past.

How we can measure the present and the future?

Well, let's start with the weather. There are weather forecasts available and we can use the data to predict running conditions.
We also know the planned running course from map data and the planned workout from the training plan.

For the present, we can ask the user. An application can ask or conclude the current user feeling,  health level, goals etc.

Simply put all data together and evaluate all the data with an intelligent and holistic algorithm that helps athletes to unleash their best.

It is clear, if we are talking about predictions then a probability should also be calculated for all predictions. Only a good and big data base can lead to a higher confidence level.

Establish a win-win situation

Why should enterprises care about supporting their users with predictions?
Because they are customers. It is highly valuable for an enterprise to know, what will probably happen a long time before it happens to customers.

Some few scenarios:

• Tracking shoe kilometers can lead to targeted shoe offers when its time to renew them.
• The choose of wrong cloths for weather can be answered with tips for adequate gear.
• In case of injury companies can propose adequate measures, medicament, courses or medical gym equipment.
• Sponsors like to know, who will probably win next race.
• Supermarkets on the running track may offer runners passing deals for drinks and nutrition.

The runner himself is enabled to be better prepared to achieve the most under given conditions because knowing what might happen is an advantage.

Conclusion

Prediction on basis of past, present data and future forecasts of individual athletes are valuable for both all market players and the connected runner. Implement it to introduce the next generation of sport portals.

See also:
10kmlauf.blogspot.com - Ubiquitous tracking and coaching
10kmlauf.blogspot.com - Concierge like journey planning

Cure is past oriented (something went wrong). Motivation for a healthy lifestyle comes from prediction (the view into future).

— Ingo (@Runnibal) 3. Januar 2018