It is a common and hardly controversial belief that if a member is not getting value for money from their membership they will leave. In a 2004 Fitness Industry Association report on membership retention, members stated that value for money was the most important factor in determining decisions to stay or leave. So if members say value for money is important we need to know how to measure this so we can do something about it.

How can we measure Value for Money?

It is not safe to rely on what people say about whether or not they are receiving value for money, as this may be subject to bias. Equally it is clearly not a manageable measure when running a business,  i.e.  how would we ensure that every member answers this question on every visit?. Therefore, to overcome this problem TRP conducted extensive research to create a robust measure of value -  the Value for Money (VFM) Index^©, to enable us to assess Value independently of subjective measures  TRP considered a variety of factors which have been proven to impact length of membership, and how these factors could be linked to value. The results produced a VFM index combining the following three factors to assess how much value a member is gaining from their membership

• How often the member is visiting.
• The level of service a member is receiving*
• How much the member is paying.

*level of service can be measured by recording service interactions.

What is the purpose or value of a VFM score

There could be several very powerful uses for our new VFM index:

• Determining how VFM relates to income and profits which would then enable strategies to be developed to move VFM scores and therefore to improve revenues and profits
• Predicting cancellations and taking proactive steps to prevent the cancellation
• As a key factor in determining the index is membership price, we believe it can help in providing a metric for deciding membership pricing levels and contract terms

We are sure there will be many more uses for this metric as we continue to work with operators on implementing strategies within the industry.

1. VFM^© Scores, Retention and Revenues

In order to analyse how this new VFM index impacts income from members, we must first look at how it impacts membership life. We segmented the data into member groups, based on their individual performances on the VFM factors and computed three levels of the Value for Money (VFM) Index^© for members: Low, Medium and High. An example here would be that a member who attended 3 times per week, received a service interaction once per month and paid a low fee would be perceived as having a high VFM. A member attending once per month, who had never been interacted with and was paying a high monthly fee would on the other hand have a low VFM. We then examined membership retention based on the three level index of VFM. On average, high VFM members retain their memberships for 13 months longer than medium VFM members and 18 months longer than low VFM customers. Therefore clearly moving members from a low VFM score to a high score will dramatically improve retention and overall revenue.

Retention

Figure 1: Average Length of Membership by Value for Money Group

VFM^© Revenue and Profits

How much more revenue would be generated for a typical club of 1000 members if all members were currently receiving low value for money and actions were taken to mean they received high value for money?

1000 members x average fee of £35 x 18 months = £630,000

Another way to look at this is that moving a member from low VFM to Medium VFM is worth £455 per member (£35 x 13 months), whilst moving a member from  low to high represents £630 per member (£35 x 18 months).

2. VFM^© Scores and Risk of Cancelling

Figure 2 shows the percentage risk of members cancelling each month after joining based on the three levels of VFM. The Figure shows that in the medium and high VFM groups, there are no cancellations in months 1 and 2 but in the low VFM group there is a 13% risk of cancelling between months 1-2. In the low VFM group it is clear that the risk of cancelling is significantly higher (up to 7 times higher – 21% vs 3%) for all periods after joining compared to medium and high VFM groups.

There are two occasions when the risk of cancelling peaks in the low VFM group, at months 4-5 and 13-14. Between months 4-5 the risk of cancelling in the next month for the low VFM group is just less than 20%. At month 14 the risk of cancelling in the next month for low VFM members is 17%. The two peaks in risk are not seen in the medium and high VFM groups. The high VFM group have an approximately 2 percentage point lower risk of cancelling from around months 10-14 compared to the medium group.

This indicates clearly that members who have a higher VFM are less likely to cancel their membership at any stage during their member lifespan. Members with a low VFM on the other hand have a higher risk of cancelling throughout their membership.

Figure 2. Month by Month Risk of Cancelling by Value for Money Score

3. VFM and determining pricing levels

As seen in the retention and profits analysis, VFM can be used to predict income from different member segments. This combined with other analysis such as member gender, age or contract length can be used to determine price levels for different membership packages. For further reading on how VFM impacts different categories of members see the research summary here.

Conclusion:

TRP believe our latest research into members’ value for money which has lead to the creation of the VFM index, is a great step forward for the industry and provides some science to assist operators with difficult decisions around, pricing, retention and even resourcing of their businesses.

We are keen to see how operators will use VFM in their businesses. Please contact TRP if you are interested in working with us to implement this new metric and the strategies around improving the score. 

Further research

VFM^© Scores against different categories of members.

VFM^© Scores and Gender

Overall 35% of members had a low VFM score, 40% had a medium score and 25% a high score. There are more males with medium scores but more females with high scores, as can be seen in Figure 3 below. This indicates that more females perceive that they are gaining higher value for money from their gym membership than males, however at the low VFM level there is very little difference.

Figure 3. Value for Money Score by Gender

VFM^© Scores and Age of Members

The proportion of members with high VFM scores increases with age and fewer members in the oldest age group have low VFM scores compared to members in the lowest age group (Figure 4). This means that older members believe their gym memberships represent higher value for money than younger members, who perceive their gym memberships to be lower value for money.

Figure 4. Value for Money Score by Age Group

VFM^© Scores and Contracts

Fewer members on 12 months contracts have low VFM scores compared to members without minimum term contracts. Members without contracts are slightly less likely to have high VFM scores (Figure 5).

Figure 5. Value for Money Score by Contract

In previous research, The Retention People (TRP) have demonstrated that the frequency with which fitness staff speak to members while working out both increases their subsequent visit frequency and membership retention rates. A question that often arises is whether it matters what fitness staff say when they talk to members. Is a simple “hello, it’s good to see you” enough or should we be encouraging something more sophisticated?

Research from changing other health behaviours, such as stopping smoking, suggests that the communication style adopted by practitioners (in this case fitness professionals) can have a dramatic effect on the level of behaviour change achieved by clients. The research also suggests that the words the client uses in response to the practitioner may also have an impact on behaviour change. In this article we explore what this research could mean for fitness team interactions.

The potential pathways between fitness staff interactions and increased visit frequency/retention are shown in Figure 1.

Figure 1: Mechanisms of fitness staff interactions

The most direct path A – connecting box 1 and box 4 -  represents the established evidence that any increase in fitness staff activity is directly related to both an increase in visit frequency and improved retention rates. This assumes that all types of communication have the same effect on visits and retention. However, as noted above, theories and research into communication styles suggest that this may not be the case and that we may be able to make an even greater difference to member retention by changing what we say and how we say it. 

An alternative path from box 1 to 4 takes this into account by following paths B and E and hypothesises that the particular words fitness staff use have a direct effect on visit frequency (a change in behaviour) and improved retention.  The research suggests that the more empathic (seeing things from the clients point of view) fitness staff are, the more they listen to and empower clients (promoting a ‘can do’ attitude) then the more clients will change their behaviour. In practice this means asking open-ended questions, listening with a view to understanding the client’s perspective and providing reinforcement about the client’s ability to change. This can be quite a change for many instructors – even this job title implicitly undermines an approach that actually requires much more than ‘instructing’.

A further alternative to move from box 1 to box 4 (following path B, C and D)  suggests that what fitness staff say, effects what clients say and what clients say in turn predicts behaviour change and retention. A behaviour change method called Motivational Interviewing^[1] proposes that when clients talk positively about changing their behaviour or their ability to change their behaviour, then they are more likely to change their behaviour compared to talking about the difficulties they are having or why they cannot change. In other words, they can talk themselves into and out of change. In turn the method proposes that what practitioners say influences what clients say. The theory is that if practitioners can elicit ‘change talk’ from their clients then clients are more likely to do what they have spoken about. When clients (not practitioners) talk about their desire, ability, reasons, and need for change this predicts commitment which itself predicts behaviour change.  We want clients to say things such as “I want to”, “I could”, “there are good reasons for me to”, “I need to”, “I am planning to”, “I am intending to”, “I am going to”.

So we want practitioners to ask open questions that elicit these kinds of statements. This also means fitness staff avoiding giving advice, judging people, talking about themselves, or telling clients what they need to do.  These things are all too common in our experience of observing fitness staff work and all tend to reduce empathy and client autonomy.  Also, many members tell us that the only time they are spoken to is if they are doing something wrong which diminishes confidence. Imagine how much better they would feel if they were frequently told things such as “I see you working really hard there”, “you are doing that perfectly” and “great technique”.

The general style of communication that the research suggests is associated with behaviour change is a ‘guiding’ or ‘coaching’ one rather than an advising or instructing one. While advice and instruction are necessary when teaching specific exercises or exercise equipment, when talking about behaviour change clients respond better to guidance. Good guides need to know where we are now and enquire where we are trying to get to rather than tell us where we should go. Good guides also offer different routes for getting where we want to go and work with us to choose the best route for us. On a long journey we may need to occasionally check the ‘map or route’ with the guide, changing the route sometimes if we meet a lot of obstacles.

The model in Figure 1 suggests that fitness staff may have the power with their words to assist members in their efforts to change their level of physical activity. Change would appear to be more likely if fitness staff discuss exercise in a way that is collaborative, supports members’ autonomy, and allows the member to be the driver of change. Conversely, the more fitness staff try to persuade, cajole or coerce members to exercise more the less likely they will. 

In our experience, most instructors do not currently possess the skills and attitude required to be a guide.  Changing from an ‘instructor’ to become a ‘guide’ or ‘coach’ is a tough challenge that should not be underestimated.  Staff need to be trained, have support and show real commitment to make it happen.  However, the hard work is clearly worth it when the rewards are really making a difference to more of our clients’ lives, increasing our own satisfaction and improving the health of our businesses.   TRP are currently working with many clients to develop guiding and coaching skills and evaluating the effectiveness of different types of fitness staff interactions on both visit frequency and membership retention.  Look out for further research being released soon and contact us for further information on how to transform your instructors into guides.

^[1] Rollnick S, Butler CC, Kinnersley P, Gregory J, Mash B. Motivational interviewing. BMJ. 2010 Apr 27;340:c1900.

FACT : You can predict which members will remain a paying member longer, before they even do their first workout – simply by knowing some basic information.

By analysing the retention rates for various groups within a club or centre we can see that some groups are predisposed to stay longer than others. This is true for a range of factors from age through to membership type and even home postcode. This can clearly be seen in our example club when we look at the variations in retention between members of different age groups.

Survival or retention analysis starts by plotting 100% of members as ‘live’ at the point they join (0 months from joining). As time progresses, the retention curve plots the percentage of members that remain paying. The steeper the line falls, and the lower it is, the worse the retention problem. The average membership duration is identified by drawing a line out from the 50% point on the vertical access and observing where it crosses the survival curve. Reading down to the horizontal axis from this point gives you the number of months the average member remains paying.

Figure 1 shows the 14-month retention rate for each of the age categories in the club. It is clear that higher age is associated with higher rates of retention. The average member in the older age group stays at least 4 months – or £140 – longer than the average member in the youngest age group. And this only shows the impact of membership fees, if you look at secondary spend as well the difference in value between the two types of member can be more than double!

Figure 1: Membership retention by age group.

FACT : Most clubs focus on ‘easy’ sales – not ‘quality’ sales.

Knowing which members are likely to naturally stay longer is clearly hugely powerful information. Any good sales and marketing manager should be able to create a campaign and sales strategy that appeals to such people.

However, more often than not, the length of time a member will stay at the club is not even considered in these discussions. Quite simply ‘a sale is a sale’ regardless of how long the member is likely to stay. In considering this, imagine how ridiculous it would be for a car dealership to treat the sale of low end car worth £8,000 in the same way as a high end model worth £80,000 – well this is what most health club operators are doing by ignoring the fact that each membership sale represents significantly different levels of income for the business.

As a result, operators’ strategies focus on volume of sales regardless of quality and, whether consciously or subconsciously, usually generate more lower quality sales. This results in many clubs having higher numbers of members in the lower retention groups. This can be clearly seen in Table 1 where 73% of our club’s members are from the groups with the lowest retention rate.

Table 1. Age profile of members

FACT : a small shift in the proportion of ‘high yield’ members can make a difference to your bottom line.

We can highlight this point by just looking at one basic factor – age – and reviewing the impact that this factor has on retention. Using the information from Figure 1 and Table 1, we can estimate the income over 14 months for each age group. We can take the proportion ‘surviving’ each month and multiply this figure by the monthly fee of £35.00.

Table 2 shows the total income from dues for the 3,233 members at our club using the age based retention rates shown in Figure 1. The baseline figure represents the total income based on the current age profile.

Each row then estimates the income based on reducing the number of 16-24 year olds in 10% increments and adding the same number of members to the age group 45+. So in essence we are swapping a small proportion of young members for older members. It can be seen that for each 10% reduction in the youngest age group and increasing by the same number the oldest age group we get approximately £8,000 more in income over 14 months.

Table 2. Change in income with change in age profile:

FACT : You can make this change and gain this additional £8000 easily.

There are numerous steps you could take to shift the structure of your membership. You could think about:

• Making the images, offering and pricing in your campaigns more attractive to older members.
• Identifying areas within your catchment where older members live.
• Adapting an approach in your sales consultations that connects with older members.
• Reviewing your product – making the club or centre, and the service within it, an attractive proposition for older members.  This may mean reviewing areas as diverse as your service standards and the music you play.

NOTE : We are not saying reduce your number of sales – maintain your current levels, just target the most valuable members first.

FACT : There are many more simple changes that you can make which will have a dramatic impact on your income per member.

Don’t forget, age is just one factor that we have used as an illustration in this article.  You could take the same approach with a host of other variables and by switching your membership base towards groups with naturally better retention, see gains worth tens or even hundreds of thousands of pounds. 

If you want more help with data analysis and ‘Smart Sales and Marketing’ please let us know.

Introduction

The financial success of a health club is dependent on a combination of the number of memberships sold each month, multiplied by the yield per member. The yield per member can be split into 3 lines:

1. Retention – length of time that they remain with the business
2. Secondary spend – which is directly related to their length of stay and the frequency with which they use the service
3. Referrals – which are directly related to their satisfaction with the service provided

In order to maximize sales most clubs employ sales teams who are often paid a commission for each membership sold. The presumption is that the sale of a membership is income generating. However, in most cases* the minimum guaranteed income from each sale is just 1 month. A range of other factors in the club, not involving sales people, will then determine how many more months a member will pay before terminating their membership. One of the factors, arguably the most important, is the activity of the fitness staff.

Knowing this, TRP decided to conduct a study in order to analyse the difference in value that sales team are able to add to the business in comparison to an organisation’s fitness team.

TRP has been assessing the impact of fitness staff activity for a number of years and has consistently found that the frequency with which fitness staff speak to club members affects the risk of members cancelling and the average yield from memberships. This study combined previous TRP analysis and found that in members who visit their club at least once during their membership, the average number of interactions with fitness staff is 3 interactions per quarter. TRP research has shown that every 2 interactions fitness staff deliver to a member in a month adds 1 extra visit in the next month compared to members who do not receive an interaction. Every extra visit a member makes in a month reduces the risk of cancelling in the subsequent month by 33% and increases the potential of secondary spend purchases and referrals. In other words, fitness staff interactions increase members’ visits to the club and extra visits equate to greater membership yield.

Fitness staff as ‘sales’ staff

One way to interpret these findings is to think of fitness staff as sales staff. What is it that they are selling you might ask? The answer is repeat visits, and every repeat visit is directly related to increased yield from this member. Every visit a member makes to a club is an opportunity to sell them another visit. The fitness staff are extremely well placed to make this sale given the opportunity that they have to interact with members. Indeed, independently of the number of visits a member makes to a club, if fitness staff talk to members they save memberships. TRP research has shown that for every 100 members a club has, on average 16 will leave each month if they do not receive an interaction from the fitness staff. By comparison, if fitness staff speak to them once then just 7 members out of every 100 cancel each month. That is more than half the number of members each month that the sales team do not need to replace to maintain the membership base. Even better, if fitness staff talk to members 4 times or more during their membership, then for every 100 members just 2 cancel each month. That is 88% fewer cancellations each month and 88% fewer members that sales staff need to replenish.

TRP have also found that the effect of fitness interactions on membership retention is universal. Fitness staff interactions reduce the monthly risk of cancellations in members of any age, both sexes, any contractual arrangement and for any given visit frequency. In other words, not talking to members while they are in the club, whoever they are, increases the chance they will cancel next month.

Do sales or fitness staff generate the most income?

It is argued that the reason sales staff are paid a commission is to motivate them to make sales. Given the low rate of interactions reported at the beginning of this article, it might be argued that fitness staff need some form of incentive or reward to motivate them to interact with members and sell repeat club visits. To illustrate why this might be financially beneficial we present a case study using real membership data from real clubs which we have anonymised and combined to model a ‘typical’ club with over 3,000 members who joined over a 3-year period. For illustrative purposes we will restrict the analysis to members who pay monthly, did not pay a joining fee and are not signed up to a minimum term contract. The members who joined the club have an average length of membership of 11 months (a range of 1-36 months) including both live and cancelled members. Furthermore to keep the example simple we will only look at the financial benefit of increased membership life, ignoring secondary spend and referrals. Therefore the total realisable financial value is in fact higher than then figures demonstrated in the example.

So let us look first at the financial benefit of sales staff. This can be estimated as the average length of membership in members who received no fitness staff interactions. For members in our case study this equates to 4 months of membership which at £35 per month equals £140. If during their membership members receive 1 interaction from fitness staff then the average length of stay increases to 9.9 months, an increase of 5.9 months over and above sales alone. That is a net additional income of £206.50 that can be attributed to fitness staff. If the fitness staff interact with members 4 or more times during their membership then the average length of stay increases even further to 27.3 months, an extra 23.3 months above sales alone. That is a net additional income of £815.50 due to fitness staff actions. This equates to 600% more income per member from fitness staff actions, compared to those of the sales staff. When including the impact of secondary spend and referrals this figure grows exponentially.

Although no official figures are available, it is reasonable to assume that fitness staff interactions are considerably shorter than the sales process and therefore cheaper and far less resource intensive to conduct. Furthermore, it only takes 8 interactions to save 1 membership. Assuming each interaction lasts approximately 5 minutes (it is almost certainly less) then fitness staff can potentially conduct around 12 interactions an hour and therefore save an average of 1.5 memberships per hour.

In conclusion, this analysis has made is very clear that investment in fitness staff, training them to make better interactions and rewarding for the quantity and quality of these interactions would be expected to save memberships and yield more income per member compared with investments in sales staff who arguably spend most of their time responding to fitness staff failures in replenishing lost members.

* assuming no fixed term contract. Even with a fixed term contract the sales staff have little influence over visit frequency, satisfaction and retention when outside of contract term.

Get it right and it helps retention – Get it wrong and you could make the situation a lot worse.

The results show that although some types of emails have a positive effect, many types of emails had no effect or even showed a negative impact on retention. This included communication to longer standing customers who have not had any previous digital contact (i.e. email/SMS) and blanket emailing of customers who recently attended the club. Operators are urged to take care when emailing and never believe that there is no cost to emailing.

The study showed there was significant promise in taking a more sophisticated and targeted approach to emailing. Emailing customers early in their customer journey so that they become accustomed to digital communications appears to be vital. Additionally, TRP were able to identify target customers based on a number of factors, including their ‘risk of dropout’ and attendance pattern. The study confirmed that motivational emails to customers in certain key groups produced some very positive results, with the most successful email type reducing the risk of quitting by 52% against the control group.

The early signs are very clear – operators should not be wasting time and resource sending emails that are not having a positive effect, and that in some cases are having a negative effect. More controlled studies are needed to extend our understanding of what makes the most effective emails.

In the meantime, TRP encourage all operators to only send emails that they can show make a difference when compared with control groups not receiving emails. (There are off the shelf products to assist you with this. Click here for more information). TRP will continue to experiment to find out more about the most effective emails.

FYI – TRP have just opened a future study into the effects SMS communication has on retention please sign up here if you would like to take part.

The Summary of the Study

First the Thank Yous
Our research would not have been possible without the co-operation of all the organisations and clubs who helped TRP in this quest and we would like to thank all those who took part and helped us start to really understand this area. We also want to extend our thanks to XN Leisure and Spa and Leisure Jobs who invited their customers to take part in the study.

Research not Marketing Hype – read this, it’s important!

Effective research is always a long process of testing various hypotheses, building on previous findings and progressively expanding our knowledge base. This article represents a summary of the first stage of this process as it explores some preliminary findings. TRP are not claiming to have all the answers at this early stage, but instead look forward to being able to expand this knowledge with further research in the coming months.

The Study Methodology

TRP integrate live with leisure operators’ existing databases and apply a unique and sophisticated algorithm to identify customers that are more likely to stop attending and/or cancel their membership. TRP are then able to automatically email these ‘high risk’ customers at key points in their customer journey, or following key events, e.g. periods of non attendance. By recording this process, TRP can then examine if this has any effect on their chance of cancelling and the likelihood of attending the club in the following time period.

In order to accurately determine the retention impact of an intervention, it must always be compared with a control group who do not receive the intervention. TRP first split the database at each participating site into a test group and control group. The control group is randomly selected from existing and new customers and as a result matches the test group on all key attributes (i.e. age, gender, membership type, duration of membership and other demographics) so the only difference between the groups is whether or not they receive email. For example, for every customer who was sent a 7 day email after not attending for 7 days, there was a matched customer who also did not attend for 7 days who was not sent the email.

Using TRP Interact DIGITAL (TRP’s intelligent emailing and SMS tool), TRP sent a range of emails based on various triggers; some basic triggers e.g. if customers had not attended for certain periods (7, 14 and 21 day emails), other emails were more sophisticated e.g. taking into account the ‘risk’ of cancelling of customers. The emails encouraged the customer to attend again and offered some motivational tips. There were no financial or benefit in kind incentives offered.

Overall, for this initial part of the research, TRP formed a group containing 110,894 customers with relevant criteria and during the initial trial, 14,632 received at least one email.

What did TRP find?

The emails’ effectiveness was measured by:

• Reduction in risk of cancelling in the month following receipt of the message versus the control group. Rate of return – the increase in the number of customers that return to the club within 7 days of the message being sent versus the control group.
• This preliminary study of the effectiveness of sending emails has produced mixed results. This is an interesting finding in itself as research into other interventions such as conversing with customers always delivers strong, robust, positive findings.

The Best Type of Email

As noted above, many configurations of ‘intelligent’ email logic were used during the study. In this summary article, TRP will share the logic used in the email which was the most successful. Using TRP algorithms for ‘risk of dropout’, the following logic was configured in the software (TRP Interact DIGITAL):

• Customers who are new – joined less than 3 months ago
• Customers who are at a high risk of quitting
• Customers who have had no attendance for 7 consecutive days, but less that 14 days.

The software (TRP Interact DIGITAL) then automatically sent motivational emails to customers who matched the criteria above.

Figure 1 below shows the survival rates of customers who received these emails compared to the control group. The difference between the groups equates to customers receiving this type of email being 52% less likely to cancel in the month after receiving the email compared to the control group.

Figure 1. Retention of customers who received the 7 day email compared with the control group who did not receive the email.

Please note that all other emails had smaller, no or negative effects.

TRP also compared the rate of return to the club, (i.e. how did the email impact visit frequency) in the seven days after an email was sent and compared this to the return rate of the control group. This allowed TRP to assess if the emails had beneficial effects in the short term by increasing the likelihood of a customer returning.

Figure 2 below shows the increase in the return rate of customers who received an email compared to their control groups. The effect ranges from just -15% to 7% improvement depending on the email that was sent and when the customer joined. Here again we see mixed results with some emails making very little difference at all, and some having a large negative impact.

Figure 2. Improvement on return rate for customers receiving the range A-J type of emails being tested when compared with the control group.

Initial conclusions

The initial findings from our research highlight some key points:

• There is definitely potential to improve customers’ retention and visit patterns with the right email being sent to the right customer at the right time.
• The logic which identifies what message to send to which customers needs to be sophisticated, time since last visit alone is an over simplified method for identifying who to send emails to and, if in doubt, controlled experiments must be conducted to ensure that the message is not having a negative impact.
• Comparable research – When comparing the results of this email study to previous TRP studies on ‘face-to-face’ interaction, it is clear that emails are much less effective. In all TRP research into ‘face-to-face’ interaction the results have always been robust have and always shown a substantial effect. This email study produced much smaller and more varied findings, concluding that the use of email to tackle the industry’s retention problem has a long way to go to catch up with the impact of face-to-face service on retention.

Future Research

This is a preliminary study and more studies are required, with a longer follow-up period, to either confirm or refute the findings. TRP will also be conducting studies using different, more personalised content to the messages. Finally, we will also examine what impact SMS have, when used standalone or in combination with email. It is possible that SMS text messages are more effective than email, or that a combination of SMS text/email and interactions have the greatest impact on retention. Our future studies aim to answer these questions and other important industry questions related to membership retention.

TRP have just opened a future study into the effects SMS communication on retention. Please sign up here if you would like to take part.

It is commonly accepted that membership retention is the largest problem facing most businesses in our industry. However, this problem is not new, so why are clubs still struggling to make an impact on their retention performance? The secret lies in a change of strategy. Operators who continue to focus their energy and investment on sales and marketing as the primary method to grow their businesses are missing an opportunity. It is proven that successful retention of members not only increases profitability, but will reduce the necessity to perpetually sell to a shrinking market.

So if it is that easy, why aren’t all clubs, and the industry as a whole, taking hold of the problem and delivering better retention results? The underlying reason is that most clubs use the wrong measures and can therefore never clearly assess whether their retention efforts have any kind of impact. In this article we look at how to measure retention in a way that allows operators to make clear, actionable decisions which will improve retention and increase income.

The attrition percentage – why it has no value in measuring retention

A method which has been used for years by the vast majority of clubs is to measure attrition by expressing the number of membership cancellations in any given month as a percentage of the starting membership that month, as illustrated in Figure 1 below:

Fig. 1

A similar measure is used to calculate ‘annual attrition’ as illustrated in Figure 2 below. In this case the annual percentage is calculated by totalling the number of membership cancellations throughout the year and dividing the figure by the average monthly starting membership.

Fig. 2

Drawing conclusions about retention performance using these methods has two fundamental flaws:
• 1. The attrition percentage is heavily influenced by the number of membership sales. In Fig. 1, between June and July the attrition % fell (from 5.0% to 4.9%), yet the number of cancellations increased (from 126 to 129)! It is clear in this example that the reduction in attrition was caused by a large amount of new joiners in June and not by any improvement in the retention of existing members.
• 2. The attrition percentage does not take into account HOW LONG A MEMBER HAS BEEN RETAINED. Using our example from the table in Figure 1, if we analyse the cancellations further on any given date, it is possible to see huge variances in the membership duration of each member that cancels. This is illustrated below in Figure 3, which looks at the cancellations from 1st April 2009.

Fig. 3

As you can see the membership life varies considerably. If every member left after 1.18 months the club would be in a very different financial situation compared to a scenario where every member stayed 56.57 months! It is therefore essential that clubs get beyond the cancellation figure to understand more about their members and how to encourage them to stay longer. What is the reason the member was retained for 50 months? What kind of demographic profile did that member have, how old were they and what kind of service did they receive?

Measuring Retention Correctly

In order to understand how to improve retention operators need to measure:
1. THE RETENTION RATE defined as:
The proportion of members who stay for a predefined period of time e.g. 3, 6, 12 months etc.
2. LIFETIME VALUE defined as:
The average length of time members stay and therefore how much they pay in membership fees.

RETENTION RATE

The horizontal axis on the graph in Figure 4 below shows the time lapsed since joining, taking ’0′ as the start of a membership. The vertical axis shows the proportion of members who retain their membership. Figure 4 shows that the 12 month retention rate is 50.4%. That is 50.4% of members retain their membership for at least 12 months. The corresponding figures for 24, 36 and 48 month retention rates are 27.7%, 17.1% and 10.7%. The area under the curve represents the total income from membership dues and therefore the shape of the curve is very important. Any flattening of the curve represents greater income.

Fig. 4

LIFETIME VALUE

The lifetime value of a member is the average duration of membership represented by the ‘median’ duration – that is the duration of membership that separates the total membership in half. Half the members stay longer than this time and half stay less (for mathematical reasons it is wrong to use the mean value as the average). This can also be read from the retention curve (Figure 5). A horizontal line is taken from the 50% point on the vertical axis and read across to the corresponding point on the retention curve. Taking a vertical line down to the horizontal axis will give the median length of stay and therefore the average lifetime value. In this example the Lifetime Value is 7.8 months. That is, 50% of members pay 7.8 months of membership dues or more, and 50% of members pay less than 7.8 months.

Fig. 5

Operators can plot all sorts of variables using these measures e.g. age, gender, membership type, service received etc. and by doing so, can start to understand why some members stay longer than others. This helps them take actionable decisions that will improve retention.

Using ‘Age’ as an example, we can plot the graph below:

Fig. 6

Assuming £40 per month.

By looking at the Lifetime Value measure in Figure 6 we can clearly see that recruiting 45+ year old members yields on average £344 more income per member than recruiting 18-24 year olds. What decisions can we make from this analysis that can be used to increase retention?

• Invest in marketing to older age groups through campaigns, imagery etc.
• Offer a discount to older members e.g. you can spend £300+ more attracting an older member and still be better off than selling to a 18-24 year old.
• Adjust membership sales targets and commissions accordingly, i.e. offer a higher commission to a sales person if they sell to an older and reduce commissions for younger members

These are examples, but they all stem from having the correct membership retention measures in place.

CONCLUSION

Hopefully we have helped to illustrate that the first and most important task in developing a membership retention strategy is to fully understand the size of the problem, and whether the problem is more prevalent in some members than in others. This will lead to possible solutions in sales and marketing, and more importantly, help to develop your customer experience using systems, policies and procedures that will achieve the desired retention outcomes.

Some of the practical steps you can take to do this are reviewed in later TRP articles.

Join us on LinkedIn to discuss this and other findings and developments in the retention field.

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Join us on LinkedIn to discuss this and other findings and developments in the retention field.