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Membership, how to engage, grow and retain

Businesses that rely on a Membership model have different analytical needs compared to those using say a Distributor or Retailer Model. This post is about how analytics supports this type of business

Some background is probably useful at this point. A membership model is a type of business plan where members pay a recurring fee to access the service(s) available. Some examples of membership based businesses that come to mind include:

Within membership models there are sub types (e.g. Fixed Term, Service Model, Upfront, etc.), I have deliberately not explored the differences, as they apply to analytics, and instead will focus on the attributes and objectives they share


The recurring nature of subscription means that they share the following simplistic objectives:

  • Keep as many of their existing members as possible.
  • Attract new members to grow, and offset membership loss (i.e. Churn).
  • Transition members to a higher value package, whether it is a family pass for Netflix or moving from an Affiliate Physician to an Associate Physician.


The advantages of a Membership Model include:

  • Recurring, predictable revenue based on a periodic subscription. Clearly this is impacted by the frequency of payments (e.g. monthly, annual or some other variation) however, it is at the least predictable.
  • Direct, ongoing relationship with customers at an individual level, after all they will all have a membership ID and there aren’t any intermediate(s) (i.e. distributors, agents, resellers, etc.). This means the feedback is of higher quality, and can be immediate, so that services and messaging can be refine as necessary.
  • The eggs are not all in one basket. if an individual members drops their subscription then the impact on the business is small. Contrast this with the impact of say, a law firm losing their biggest client.
  • The cost to scale is lower than comparable models. For example, the cost to deliver a service (e.g. streaming online content to one 1 or 1,000,000 subscribers) often does not increase proportionally.
  • There is a reduced marketing cost to constantly attract new members, assuming that there is a manageable churn rate, and the organisation is mature.


The key disadvantage of a membership model is they require a large number of subscribers in order to fund the necessary support staff necessary to deliver the service(sl offered. This can be a significant obstacle during start up.


Initiatives that are undertaken to establish, maintain and grow the membership include:

Member SegmentationCategorise members based on a range of segments. Examples include:
– Geographic
– Psychographic
– Behavioural
This is easier as members are well known and is used as a tool when interacting with them
Churn ModellingDetecting at risk members so that steps can be taken to retain them. This requires a rich dataset that includes history and segmentation.
Renewal ModellingIdentify process issues that impede the efficient renewal of memberships. This helps to improve the member’s experience and reduce the head count and therefore cost of operational staff
Data AcquisitionAcquire data from multiple sources to support subsequent modelling. Source to include:
– Website interactions
– Event attendance
– Renewal payments
– Lapsed renewals
– Membership types
– Social media activity
– etc.
Data ModellingSupport Segmentation, Churn, Renewal Modelling, Operational Reporting of key measures like:
– Monthly Recurring Revenue
– Annual Recurring Revenue
– Churn\Attrition Rates
– etc.
Operational Reporting and Data VisualizationPresentation of key performance indicators in an intuitive and visual manner. For example:
– Monthly Recurring Revenue
– Annual Recurring Revenue
– Churn\Attrition Rates
– Memberships in arrears
– Net Promoter Score
Analytical services

Based on delivering the analytical service above, the following can be undertaken more effectively.

Engage – Enhance the service provided to the member and thereby reduce the risk of churn
– Encourage increased event attendance and therefore engagement, thereby reduce the risk of churn
– Target members who are predicted to be at risk of churning
Transition– Target members who have dropped to a lower segment (e.g. reduced the membership type and therefore the revenue generated) and endeavor to transition them back
– Target members who can be transitioned to a higher value segment based on their behavior
Business Outcomes

Over the next few weeks I will be creating supporting posts on the following topics

  • Member Segmentation
  • Churn Modelling
  • Renewal Modelling
  • Data Acquisition
  • Data Modelling
  • Machine Learning and Artificial Intelligence

Hopefully this post has been useful and list of upcoming post will see you following

Image by harshahars from Pixabay

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