How Can Big Data Help your Gym Thrive?
What is Big Data, and how does it work?
Big data is a large, diverse set of information that grows exponentially. Big data can be structured or unstructured, meaning that it can be numeric and more quantifiable or less quantifiable. Structured data is quantifiable and is typically internal company data like customer information and purchase history. Unstructured data is less quantifiable and generally is 3rd party data, like social media and other external review and rating sites(Google, Yelp, etc.).
Big data analytics is a powerful tool because it helps businesses interpret big data into meaningful insights. These insights help businesses understand their customers better and help them make better decisions for various strategies within the business.
How can big data help your gym?
Big data analytics can be broken up into three categories: descriptive, predictive, and prescriptive. Let’s dive into each of these and see how they can help your gym thrive.
Descriptive analytics will answer the question: what happened? In other words, descriptive analytics looks at data from the past to help you understand what happened. In addition, descriptive analytics will help you identify patterns in your data and possible strengths and weaknesses. Descriptive analytics tells you what happened but doesn’t explain the why. Therefore, descriptive analytics is very surface level and can only give you a snapshot of what happened at a specified time. Descriptive analytics is typically used to summarize sales data, marketing campaigns, social media usage, etc.
Predictive analytics answers the question: what could happen in the future? In other words, it can help you identify a pattern based on a set of criteria. For example, it could help your gym predict when a member is at high risk of canceling based on patterns of missed classes, low attendance, or lack of bookings. If you can identify these issues early on, your gym can act and address them.
Prescriptive analytics helps a business decide the best next step to take, given a specific event
occurs. Continuing with the same example from earlier about identifying patterns in high-risk members, predictive analytics could take a particular action on a member missing a class. For instance, if a member misses a book class, you can implement an automated process texting them to check in to see if 1) they’re okay and 2) help them re-book the class. This is an excellent example of how prescriptive analytics and big data can help you improve your overall member retention. If you can identify the issues early on and take action, you have a better chance of keeping your members engaged.
Big data is a powerful tool that should not go unused by your gym.
Customer loyalty and member retention are something most gyms struggle with, but big data is promising in giving your gym the ability to overcome this obstacle. Use descriptive analytics to understand what happened, predictive analytics to avoid future behaviors (like membership cancellations), and prescriptive analytics to address those behaviors.
Miss last week’s post? Read about turning your data into better decisions.