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How Big Data in personal fitness industry is gaining potential?

Riddhi Shah
, 9 Jan 2017
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9-Jan-2017

With consumers progressively adopting healthy living practices, several companies operating in the fitness centric business now see their customers base grow at rates never seen before. Hence, more and more data scientists and business executives are working in tandem to drive a vision.

Correct usage of data science can increase the overall information processing power of health & fitness data while providing insights about our health habits, consumption, treatments and medication. Thus, the room for growth of data science in health & fitness for the next few years is big.

Most of the value fitness technology users are looking for is very personal. There are a few areas more interesting for the use of big data in the fitness area than helping us track our own activity to become better at whatever we are doing, whether it is sleeping, running, or staying agile by signaling us to get up and move around more often.

The fitness tracking apps, nutrition apps, yoga and exercise apps, blood pressure and sugar level monitoring apps, weight control and fat burning apps are a few great instances of health and personal fitness industry using big data technology. Data from these apps is put to better decisions. Some of them include:

Re-discovering customer trends – A visual representation of the dataset, to quickly spot behavioural aspects and customer preferences helps in re-discovering the customer trends. Example could be a fitness center monitoring demographics, sign-ups, churns and attendance details, gender, footfall density and time, etc. to serve their members more efficiently. By targeting the time and gender footfall, the centers have started to include diverse activities which can be availed categorically. Hence, overall fitness has gone to the next level from just traditional ways.

Food lifestyle improvisation – Terabytes of consumer data is collected 24*7 across various channels like fitness centers apps, Fitness Wearables, etc. The channels are then integrated with external apps and real-time data to make data-driven decisions for the benefit of customers. Example could be a fitness tracker integrating with apps like foursquare and swarm to track the check-in patterns and suggest healthy eating options in the vicinity. This way, more and more people become conscious of their food consumption patterns and look out for healthier options, either at home or outside.

Fitness Infrastructure – Some of the apps data like nutrition and weight watcher collectively and intuitively understand user patterns to come together and develop fitness infrastructure within the city localities. For example if a variety of users are complaining about unavailability of good healthy eating options in a locality, it could be a great opportunity to start a fitness centres like yoga and cross-fits to serve the localities or open a health food restaurant.

These are a few ways data is applied to better use and there are many more. However, global variety and complexity of different data that can be put to use in health & fitness is quite notable. It is known that health and fitness touches every aspect of human activity, and different companies in health & fitness have been gathering different types of semi-structured and structured data related to health & fitness. Not just for health and fitness, data can tell you almost everything if you keep nudging it often, so its application is unimaginable in today’s time.

Riddhi Shah – Digital Marketing Manager, Ashnik


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