Six Ways to Use Predictive Analytics to Grow Your Association: Member Retention

February 11, 2021
Thomas Altman
Six Ways to Use Predictive Analytics to Grow Your Association: Member Retention

Part 6 of a 6-part series. 

You can build a great organization and grow pretty quickly, but you can’t sustain it unless you’re actually providing something people want and keeping them around. That’s why member retention is the holy grail—and, unfortunately, one of the greatest pain points—of associations today.

Knowing what people want requires data, and lots of it. And even if you have all the data and processes for collecting feedback from your members, you still need processes and workflows to make sense of that data. This is where predictive analytics comes into play. 

Predictive analytics puts us on the path to finding the holy grail; to finding amazing member retention strategies, the kind that just makes you a blow-away awesome association.Now if you’ve been following this blog series on using predictive analytics to grow your association, then you may have noticed we keep circling back to how each of the applications we’ve covered—member targeting, financial forecasting, risk analytics, market intelligence, and financial modeling—help you retain more members.

But these predictive analytics applications don’t just individually contribute to your member retention rate; they also work synergistically to help us make better roadmap decisions and member experiences that keep people coming back for more.

How to retain members with predictive analytics applications

The ways in which predictive analytics applications work together to retain members are innumerable. Here are just a few of the ways these elements go hand-in-hand to inform member retention activities and “hack” the growth of associations.

  1. Pinpointing potential members and modeling the impact of customized targeting strategies.
  2. Improving the effectiveness of targeting approaches to increase member experiences, drive more revenue, and lower marketing and operational costs.
  3. Building and automating processes for applying data to decision-making.
  4. Streamlining financial forecasts, risk assessments, and market insights.
  5. Building predictive models using forecasts and assessments to help you make more sound decisions.
  6. Predicting the future needs of individual members based on what issues are important to them and the problems they want your association to solve.

So, in essence, predictive analytics and modeling promote member retention by discovering what makes your individual members tick and why. These algorithms and machine learning techniques also go beyond just identifying what members want from their association membership.

They also help you segment your lists and tailor your targeting strategies so you can best serve the wants and needs of your members. Then you can dig into the analytics to refine your custom targeting approaches and membership retention best practices to continually deliver value and solve the problems of each and every one of your members.

Real-world scenarios

Mentorship Program Example

Let’s say you have a network of members that want to connect and/or mentor each other. Identifying this need using good ole’ fashioned outreach (e.g. online community engagement, email campaigns, focus groups, individual outreach) or predictive market intelligence may then prompt you to consider implementing a mentorship program. You could then forecast engagement and risks, and model the impact and strategy of implementing such a program all with the power and insights of predictive analytics.

RELATED ARTICLE>> How COVID-19 Data Can Help Your Association Retain Members

Continuing Education Example

You can also use analytics to predict new member retention opportunities such as untapped continuing education needs within your community. You could then apply predictive analytics to turn this vision into reality by:

  • Forecasting the revenue of providing such a program.
  • Calculating necessary fundraising targets or what funds should be moved around.
  • Anticipating (and mitigating) internal and external threats to offering the program.
  • Modeling different implementation strategies and outcomes.
  • Predicting current and potential member needs and motivations for wanting this type of program.
  • Effectively targeting current and potential members.

Kick-start member retention

Member retention is certainly NOT a simple equation. If you want your members to stick around, you have to demonstrate the value of being in your association. In other words, you have to literally help them on their professional journey and assist them with whatever the reason they decided to join your association in the first place. And this starts on day one of their membership.

The great thing about predictive analytics is it helps ensure valuable data points don’t fall through the cracks—starting on day one. It ensures you’re solving the right problems, engaging members the right way, and tapping into the thoughts and voices of your crowd.

Without processes and techniques to understand and apply the data your organization has collected overtime, it’s easy to get caught in this vacuum kind of thinking where you’re giving your best guesses like, “Yeah, this makes sense because of this.” Instead, you can now use algorithmic forecasting and modeling with an organized dashboard that explicitly says, “Yes, A, B, and C are the right things to do for this type of member because of X, Y, and Z.”
Ready to fine-tune your member retention plan? With the impact of predictive analytics on associations today, it’s never been easier to get a handle on your data and use it for the benefit of your members. Download our free ebook, The Association Retention Playbook: The 5-Step DIY Membership Retention Strategy and Workbook today to get moving on the right track.

Thomas Altman

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