Decent data is vital if you want to improve member retention. That's why we work with the DataHub

Lord Kelvin said, “If you can’t measure it, you can’t improve it”, and hit on one of the key issues in the fitness industry. Ask a club manager what their retention rate is, and many will shrug, while others will quote an attrition figure from months ago. Follow-up by asking what they’re doing to improve their retention, and you’ll typically get more blank looks, or possibly something about inductions or 6-week programme reviews.

The Datahub aggregates data from thousands of facilities. Datahub clients get accurate, real-time reports on their retention performance, as well as Geo Impact, Social Value and Marketing Intelligence tools. Any other organisations can benefit from anonymised benchmark data to compare against their own performance.

Here are 7 data points that GGFit clients use as retention Key Performance Indicators (KPIs), with benchmark data powered by the DataHub.

12-Month Retention

How many members stay for 12 months? The UK average is 52.4%⁽¹⁾. Regardless of when members join, how many stay for at least 12 months. This is a difficult KPI to affect in the short term, but a good (if alarming) metric for overall retention.

Attrition

UK average is 6.2%⁽²⁾. The number of members who leave in a certain period (month) as a percentage of total members. Attrition is a more dynamic KPI, providing an ongoing monitor that can show retention performance, but it can be affected by sales (e.g. a high sales month can reduce attrition).

Length of Membership (and Stay) 

Knowing your average Length of Membership (LoM) is essential if you want to calculate the average lifetime value of a member. The average LoM is 14.4 months⁽³⁾. Understanding Length of Stay (LoS) is less financially interesting, but critical for retention. The difference between LoM and LoS shows your absent member recovery window before they leave. 10.8 months is the average LoS, so members are typically dormant for 3.6 months (107 days) before cancelling their membership.

Average Visit Frequency

This is a great KPI to start to deliver improvements in the ‘big’ numbers above. Knowing how often your members visit on average gives you a gauge that you can try to affect through interactions, reviews, classes and challenges. The average visit frequency is 6.75 times per month⁽⁴⁾, or 1.5 times per week.

First Month Visits

This leads nicely onto First Month Visits (FMVs), a vital measure of how your new member journey is performing. Knowing average FMVs (6.60⁽⁵⁾) is useful, but a more practical KPI to consider is how many new members make the cut, of say, 4 visits. Typically, 75% of new members make 4 or more visits in their first month, which is good, but needs improvement, as 25 in 100 aren’t forming the exercise habit. Some clubs have up to 10% of new members making no FMVs, which is a serious issue.

First Month Induction and Class turnout.

Two more significant KPIs that focus on the new member journey. Both these KPIs will improve your bottom line retention. If you know what percentage of your new members have an induction (there is not enough standardised data for a benchmark here), or those that join in a class in their first month (18.5%⁽⁶⁾), you can work on ‘selling’ more to new members to ensure that they have more chance of forming the habit. Combining these KPIs with FMVs always shows the benefit of the induction appointment, or the loss when it is missed, and demonstrates the benefit of classes in engaging new members.


The DataHub suite of tools are a great help to GGFit in delivering retention solutions. Analysis can be performed much more efficiently due to standardised groupings or aggregation of membership types, group exercise class types, appointments and visits. Marketing Intelligence enables us to take action and measure the effectiveness of those actions. And the benchmark data helps customers to compare their performance with other clubs in the same sector, or across the industry.


Notes on data sources / criteria for KPIs, intended as help in using the benchmarks to compare against your data. All KPIs are calculated based on members with DD memberships, for both public and private sector clubs.

1. 12 month retention rate is calculated using all datahub memberships started between July 2015 and June 2016. Data set is 300+ sites, 75,000+ memberships.
2. Attrition is calculated as the average monthly attrition for 600+ datahub clubs from July 2016 to June 2017. 800,000+ terminations
3. Length of Membership/Stay for all members (active and expired) can be very high. Here, it is calculated for all members who cancelled their membership from July 2016 to June 2017. Length of Membership based on 275+ clubs, 600,000+ cancelled memberships.
4. Average visit frequency is calculated by dividing the total member visits by the number of unique members. The timescale is July 2016 – June 2017, 4,000,000 members making circa 27,000,000 visits/bookings.
5. First Month Visits is defined as the average number of visits all members make in their first 30 days after joining, for all joiners from July 2016 – June 2017. Based on 200+ sites, 35,000 joiners.
6. Class turnout is measured by calculating the percentage of new members who attended at least one class in their first 30 days after joining. Based on 200+ sites, 35,000 members.