Wouldn’t it be great if you had a crystal ball and could identify those members most at risk of resigning? You could begin identifying reasons they might leave and reach out to them before they do!
You’re worried because the past two years have seen a decline in membership. And this year, your club’s Marketing Professionals, leadership and committees will start reacting even more to this dilemma and spend a considerable amount of time trying to recruit new members versus proactively retaining your current members.
Data has become a critical component to the growth and retention of private clubs. It can guide smart decision-making, improve staff efficiency and increase member retention. The most successful clubs are those who are constantly monitoring engagement, membership feedback and most importantly, membership activity levels. Not only is it critical for a club to monitor trends and activity levels, but also be prepared to act if trends at the club reveal the need for action.
When looking at each of your member’s engagement and activity levels, you can also begin predicting how they will interact with your club and how to best reach out. Predictions based on gut reactions are typically not effective. However, when they are based on data supported by actual member behavior, it becomes much easier for your staff to understand how interactions with members will be received.
Clubs are able to drill down further to reveal even more specifically how much engagement each member has with your club. When you thoroughly understand your members, you can speak directly to each of them, highlight their interests and address any concerns. This type of predictive analysis can build loyalty and help solidify their commitment to the club.
Think about how, over the next year, if you knew which factors could be correlated to those members most likely to resign and which factors are correlated with those member most engaged; you could begin to tailor your marketing, events, programming, and communications to attract more of your best members and increase engagement from those who might otherwise leave.
Now you have not only a list of members in each group, but an understanding of their specific engagement. You can change the future and you can better forecast what will happen next year.
P.S., One offshoot of predictive analysis of engagement and activity levels is member satisfaction. When club’s really get to know their members, they can create the most effective member satisfaction programs for directly boosting retention.
If you would like additional information regarding factors involved with the predictive analysis of your membership, or if you would like help analyzing your own data, please Click here or call (800) 526-8794.
Comments