Why this topic?
I like to do sports, but running has always been something I couldn’t quite find the motivation to do on a regurlar basis. Then, about one and a half years ago, I started to use tracking apps. And all of a sudden my workout experience changed. Comparing my own results and being able to track progress worked as a motivational boost. Sharing some workouts to Facebook even motivated me more, since fellow runners commented and liked my activities. I found that app providers didn’t put enough focus into this part of their respective apps and that’s when I decided that the social phenomenon deserved special attention and I made it the topic of my final project.
I was in the lucky position to collaborate with the sports app provider Runtastic to do the investigational part of the project and therefore I could count with real user data throughout the whole process.
How did I go on about the project?
First of all I started with a background analysis of the Quantified Self movement, the facilitators of self-tracking (which basically is the broad access to smartphones) and the fitness app market itself. Since there is an inmense number of different apps to track workouts I decided to carry out a benchmarking of major fitness apps in order to better understand the products and social anchors within the apps. The 7 apps included in the benchmarking have been chosen according to download volumes in Google Play Store, data from the app research platform appdata.com and competitive insights from Runtastic. Thanks to that part of the project I got in good shape since I did serveral runs with all apps in their different versions 😉
The conclusion I draw from the benchmarking confirmed my assumption that there was room for improvement for social sharing within all of the apps. The core features of any running app are very similar, but I also found that social interaction was very basic among almost all tested providers.
In parallel I analysed the importance of the social channel within the marketing mix of fitness app providers and not only found that social tends to achieve best conversion rates and user quality, but also represents a major traffic source – in the case of Runtastic social networks generate around 33% of all traffic to their website (!) This clearly shows that such an important channel should be nourished and taken advantage of – the more, the better.
Gathering data from real users
Here is where the really interesting part of the project started: gathering real data from users and investigating their running and sharing bahavior in depth. As a methodology I opted for a quantitative analysis and carried out an online survey in collaboration with Runtastic. In total I got 792 respondents to participate in the survey, out of which I could use 700 as valid data.
To briefly resume the findings of the survey the following facts should be highlighted:
- People making use of fitness apps tend to track almost all of their runs, especially if they work out alone => high retention rate
- Fitness tracking is more interesting to the male population than to females, and men also share their workout summaries significantly more often to social networks.
- People preparing for special events (like running a marathon) are most likely to share their workouts, followed by people trying to lose weight.
- Sharing workouts creates a motivational loop: Feedback from other users foments retention and increases loyalty. Workout summaries trigger possible new users to try the product.
- The majority of people who doesn’t share fitness related topics in social networks doesn’t share anything else in social networks either.
- The detection of personal records, the possibility to share workout summaries and the active incentivation of sharing could drive people who currently don’t share workouts to start sharing in social networks.
Based on the results from the survey I could create a prototype of a typical fitness app user (male, between 28 and 42 years old, lives in urban area etc.), which can help app providers to better understand their audience and target users in a more efficient way.
Besides the mere analysis of the results I suggested the implementation of 2 different business cases, which now could (should) be tested by app providers in order to increase social sharing within their apps. According to the survey the biggest potential lies within the automatic detection and information of personal records (e.g. record time over 10 kilometres) and a personalised invitation to share this achievement. Almost 65% of all respondents of the survey said they would wish for such a feature. This is only one example out of many actions that could be iniciated based on the results of the survey and help app providers to improve their business model and drive app downloads and user retention.
Limitations I encountered during the analysis of the data are of a qualitative level. Since the survey has been carried out as a questionnaire, I could not follow up and analyze in depth all motivations and constraints of users when it comes to sharing in social networks. I think it would be very interesting to carry out a qualitative analysis (e.g. performing personal interviews with self-trackers) in order to complement the results of this project.
So, what are the conclusions?
Today thousands of different devices, sensors and apps are available in the market to track our workout behavior and store the recorded information. But it is the connection to social networks that allows users to share achievements, compare results and expose workouts to the appraisal of others. The linkage of fitness with our virtual self creates interaction and entails great motivational power. Sharing workouts makes people push to new goals and gives them a reason to work out harder, run faster or go a little further. Besides the positive motivational effect on users, sharing at the same time plays an important role for app providers, being a key driver of user acquisition and retention.
The whole research process has clearly shown the importance of the social channel within the business strategy of fitness app providers. The findings confirm that sharing plays an important role in keeping up the motivational level of existing users, hence making them use the same app over and over again. Besides this effect of self-retention, sharing also creates triggers for third parties – and therefore foments user acquisition.
The outcome of the survey also proves that there are demographic factors and workout patterns that influence sharing behavior. This knowledge opens new ways of targeting users to further increase sharing and can help app providers to better understand the actions users take in social networks. In order to gain market share and overtake or outdistance competitors, the findings of the survey could help to make a more deliberate use of the social element in order to create a competitive edge and tie users to a specific app or workout program.
I think this paper opens the door for many different aspects of further investigation. Based on the results and data of the survey, a multitude of different approaches and targeting methods of users could be tested. Having seen that social sharing can be actively promoted through multiple variables (e.g. copy of messages, personalization of information, targeting according to behavior and/or demographics) the possibilities for app providers to foment activities in social networks are almost infinite.