Are you targeting an Ideal Customer?

05. 29. 2019


(Case Study: Boxing Gym)

We had a client that was a chain of boxing gym franchises that was looking to expand in a large city in the middle America. The gym wanted to do what every franchise does: grow the number of it’s branches and make the most money at each of its locations.
They were spending quite a bit on advertising, targeting specific demographics that they thought would be their ideal clients. But no matter what the marketing team did, they could not get a conversion rate of more than 10 percent.

Who is the boxing gym’s target customer?

Who do you think a boxing gym’s target customer is? Are their certain demographic groups? Maybe males? Say ages 25-35? Possibly a couple of ethnic groups but less so certain others?

This boxing gym had some assumptions about who it’s clients were based on some data and market research that they’d conducted. Then the marking team was making its advertising decisions based on that.
Still, no matter what they did, they were stuck at a ceiling of a 10% conversion rate. That’s where Fract came in.

The Fract AI cuts through the fat and gets right to the meat

When the boxing gym signed up to Fract to help them figure out how they could up their conversions and put their advertising budget to better use, it was a radical departure from their previous strategy.
Instead of having some people in a room talking about charts and graphics, trying to interpret that based on on some preconceived notions of who their clients are and should be, the Fract system’s AI analyzes more data than humans ever possibly could and derives often-surprising data-driven insights based on that.

The boxing gym uploaded all the data from their POS system in Fract, and the AI interpreted that in combination with publicly available geospatial data.
The Fract AI found revelations that ran in direct contrast to the assumptions about the gym’s clientele. It turns out that there was little correlation between demographic factors like gender and race and who the gym’s ideal customer was. Interest in going to the boxing gym cut across demographic lines. That was surprising.

The strongest correlations associated with gym membership were people who:

  • Spend money on sports equipment (87.8% of gym members)
  • Attend sports events (86.9% of gym members)
  • Watch boxing on TV (86.5% of gym members)
  • Buy activewear (86% of gym members)

Another surprising insight based on geospatial data was that people wouldn’t drive more than 17 minutes to the gym! 16 minutes is fine, but if someone lives 18 minutes away they aren’t going to that gym.

Actionable Insights

With Fract’s AI driven insights in hand, the gym’s execs were able to cut through all the signal to learn more about who their customers really were than they ever would have been able to on their own.
Using this information, the gym’s marketing team was able to better target customers with Google Ads.

This is just one example of how businesses can use Fract’s AI to gain actionable insights that increase revenues and empower intelligent expansion. Book 30-min call and get insights about your business:

Mike Mack

Mike Mack

Mike is the Co-Founder and CEO at Fract. With over 20 years of retail and business location analytics experience behind his belt, Mike counsels business owners and helps them get the most out of their business and sales data. He is also a passionate art lover and enjoys a glass (or two) of good wine with friends and family on the weekends.

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