Unless you’re a data analyst or love numbers, predictive analytics are probably two words that scare you. They’re new, unfamiliar, and sound like math. In reality, you don’t have to love math to leverage predictive analytics – it does the hard part for you!

Can you imagine having a crystal ball foresee which members will renew and which ones need extra attention?

Below is a breakdown of membership predictive analytics and how it can help associations see the future so they can act before it’s too late.

What is membership predictive analytics?

Simply put, it’s a modern way of using data and machine learning to predict how members will behave. By looking at past data and considering different factors, predictive analytics sorts members into groups based on how likely they are to renew.

How does membership predictive analytics work?Membership Predictive

  • Spotlight what matters most – first, we identify what factors have the strongest correlation to membership renewal (with a robust decision tree model but we won’t hurt your head explaining that). Basically, it’s like shining a spotlight on what really matters, so you can focus your marketing and engagement efforts where they count.
  • Create prediction buckets – next, we bucket members into different prediction categories that tell you how likely they are to renew. With a range from “Very Likely to Renew” to “Very Unlikely to Renew”, you can see which members can be fast tracked for quick renewal and which members need a more personalized approach.
  • Tie revenue to prediction buckets – finally, we apply the current year’s dues to the prediction categories which gives you the power to set more realistic dues revenue expectations.

What can you do with membership predictions?

Use your new crystal ball to help build your mid- and end-of-year strategies.

  • Mid-year strategies – use your new predictive categories to adjust your engagement strategies throughout the year. For example, tailor activities for members in the “May or May Not Renew” category based on key renewal factors.
  • End-of-Year Strategies – customize your approach for different renewal groups as the year wraps up. While standard strategies work for “Very Likely to Renew” or “Likely to Renew,” others might need a more personal touch for successful renewal.

How do I get started with predictive analytics?

  • DIY it – there are lots of manual DIY ways to start dabbling with predictive analytics like add-ons in Excel and free tools from Amazon and Microsoft, but they all require a good amount of expertise in data science, aka math.
  • Go old-fashioned – you can go the old-fashioned way and use your judgment and expertise to decide which factors are most important to renewals. Do members who attend your conference usually renew? What about certain member types? This is also a manual exercise.
  • Use a tool – using a platform built to automatically perform predictive analytics (like AcumenAI), based on all your member data points, is the ideal way to get started. Leave the mathing to the machine so you can focus on more important, strategic work!

If you’re interested in learning more about AcumenAI and how it can help your association leverage predictive analytics, visit our product page or schedule a demo with one of our experts today.