Using AI, this is how to stop someone cancelling their gym membership, before they even realise they want to.

Through integrated artificial intelligence and machine learning using years of data, Ian Mullane explains how every fitness operator can stop guessing about gym member activity and actively predict what's going to happen.

This episode was recorded before the pandemic. For more information on the Escape Your Limits podcast visit https://escapefitness.com/podcast

Video version – https://youtu.be/w5g2arKz57c

 

Ian Mullane has a background in financial engineering and financial software. Not the traditional fitness professional, he's ditched the field of the hedge fund field of corporate life to turn his expertise to another sector.

A passion for boxing was keeping him in shape. With some other likeminded enthusiasts, he wanted to open a 20,000 square-foot boxing club in a disused grandstand in the old Singapore Turf Club. His wife had different ideas, which turned out to be much more lucrative, and Ian was left with a 1000 square-foot to play with. Here, Vanda boxing club raised over $3m for charities through white collar boxing events, in one of the first boutiques in the city.

Today, Ian is overcoming traditional challenges of attrition and growth using data sets to explore predicability on whether or not members will stay or leave. Through this AI and machine learning expertise, he's able to help operators around the world drive revenue.

A revenue acceleration platform for the fitness industry, Keepme.ai is all about smarter member retention using artificial intelligence and machine learning. The platform identifies members who are close to cancelling and win them back before they even plan to leave.

Through SaaS expertise, Ian and his team exist to help health and fitness businesses retain more members. Regardless of whether customers are big box or boutique, pay as you go or contractual, Keepme.ai equips them with the ability to accurately target and engage members, implement behavioural science approaches, and allows operators to truly understand the people they serve.

For more information visit keepme.ai

 

Episode highlights -

• What the simple explanations are behind AI and machine learning.
• Why bringing a huge number of decision trees together with the right algorithm will bring high levels of accuracy in probability for any data set.
• What the difference is in accuracy between statistical modeling and machine learning predictions.
• What the importance is for revenue in segmenting data and providing the correct results for each member depending on what they need.
• How far machine learning and predictive algorithms have moved on in recent years, and what the future holds for people with accurate data sets.
• Why “dirty data” in the fitness industry will provide challenges for some operators, but what off-the-shelf tools can be used to overcome this.
• How looking forward and being able to predict what's likely to happen is going to leave you at a better competitive standpoint than people only looking at historical data.
• The importance of having an API on any software that you purchase, for future developments even if you don't think you need the function now.
• How you can integrate your predictions with other sources such as purchase data to better understand everything about a member and supplement information.
• How you can understand what members you will keep and lose, and what members you should be focussing your marketing on to improve retention rates.
• Why better business isn't always about the upsell, and how downselling members at the right time will keep them in your business for the long term.
• What partners such as Myzone can do to indicate when you need to intervene and interact with members to avoid their interest dropping off, leading to a member leaving.
• How Google, Facebook, Amazon and other giants are going to make greater steps into fitness using data and machine learning than many traditional fitness businesses in future.
• What you can do to predict your own health or apply preventative measures based on data from fitness trackers, accessories and apps.
• How the offer weighs up for communities between the connected home environment of fitness compared to bricks and mortar.

 

Join Matthew Januszek in conversation with Ian Mullane…