Understanding Data Trends Keep Member Retention Rates on the Rise
Every year, association members choose whether to continue their annual membership or cancel. During this time, associations are revising their retention strategies to encourage more renewals.
There are a few member factors that go into the renewal decision-making process. First and foremost, are they happy to be a member?
Aside from having a generally positive experience with the association, members may also consider:
- How often they engage with the association
- How often they use association resources
- How many association events they were able to make
- How many new contacts they’ve made through networking events
- How often they felt a part of an association community
These factors are also a great way to anticipate who will renew and who may be at risk. A lot of associations struggle to categorize members by risk to see who needs a little extra attention.
Understanding these trends is an essential part of strong retention strategies! Introduce predictive analytics into your current retention strategies and see how data can help you retain membership.
What is “Predictive Analytics”?
It’s clear how predictive analytics can help associations develop retention strategies. However, defining predictive analytics may not be as clear. Essentially, it is the process of using and combining historical data and statistical algorithms to give you an accurate depiction of the future. The idea of predictive analytics has been around for quite some time but has only recently started to grow more rapidly.
The reason why it’s become a popular strategy for businesses is that it’s more accessible now than ever before. In the past, this type of data analysis was used mostly by mathematicians and statisticians. Now, anyone can collect this data and interpret it. As data continues to grow over generations and provide more insightful information, it will become more and more valuable to associations.
Predictive Analytics for Association Retention Strategies
There are many reasons why businesses and organizations use predictive analytics. For the most part, it’s used to avoid company fraud, increase high-value leads, optimize marketing efforts, reduce overall risk, and retain current client bases.
For example, everyday use of predictive data that you may be familiar with is your credit score. Credit scores are calculated using this same data interpretation! For associations, predictive analytics can collect data regarding member interactions to help associations target members who are at risk.
A few variables that can be calculated include:
- Email Opens and Activity (do they scan it or actually read emails?)
- Social Media Engagement (how often do they comment or like posts?)
- Content Reads (do they read blog content or online resources?)
- Attendance at Tradeshows and Networking Events
- Web Footprint (how often do they visit and search through the association website?)
- Event Participation (do they often RSVP for association related events?)
Anything else that can identify member engagement can be used as a variable. Collect this data on past and current members and create a data file that links to these variables.
The general process for predictive analytics is this:
- Add a statistical modeling technique that provides an equation related to the variables
- Grade members based on the equation and rank by grade
- Segment members into 10 groups from least to most at risk
- Create a profile for each group explaining their rank
- Form a personalized retention strategy for each group
How to Start Predictive Analytics-Based Retention Strategies
In a perfect world, you could read this blog post and say, “oh, perfect! I’ll get right on that!” and have all this data collected in minutes. Unfortunately, this is not the way of the world. If the idea of spending months collecting data and adding it to a spreadsheet, followed by consistent hours used on maintenance doesn’t appeal to you, well, don’t worry… there are other options.
Using proprietary machine learning algorithms, you can interpret this data in no time. 24/7 data analysis collects all of the variables mentioned above automatically. It analyzes and delivers predictions for what members want to see and be a part of. Using a resource like predictive analytics can help associations truly understand their members in a way that they may not articulate themselves.
Get the Most from Predictive Analytics
Overall, using predictive analytics is a great way to understand your members and segment them to provide personalized services.
In this way, predictive analytics can be used for more than retention strategies. It can also be used to connect with strong leads, delight current members, and give valuable association insights. Through this data, associations can get to know thousands of its members in a matter of minutes.