How to predict and prevent member churn

Sep 10, 2020

About this event

Retaining your members doesn’t have to be complicated or require sophisticated tools. In this workshop, we learned from two predictive analytics experts who taught us how to predict which members are likely to leave your organization, and how you can prevent them from leaving.

Dray McFarlane and Thomas Altman offered a simple Microsoft Excel workbook that can use the data you already have to forecast the likelihood a member will leave. They showed us how to craft strategies to target specific groups of members, and give you a framework to understand if and how much of a discount you can offer members to keep them.


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Dray McFarlane

Co-Founder of Tasio

After an education focused on technology and economics, Dray has spent over a decade providing associations with technology solutions. In that time, Dray loved getting to dive deeply into the goals and challenges of a group driven by passion to support their missions in the best ways possible. Immersing himself in their needs and getting an understanding of their business has been a constantly evolving and incredibly rewarding experience. Founding Tasio gave Dray the opportunity to continue on this path, applying all the knowledge and expertise he’s gained about associations in new and interesting ways.

Thomas Altman

Co-Founder of Tasio

He started working with associations after getting a graduate degree in applied data modeling techniques. His focus was on using those techniques to solve business problems, and one of the first things he noticed when working with associations is that, while associations do a great job of collecting data, hardly anyone is really putting that data to use. Thomas has seen too many associations needlessly fall behind in delivering on their mission because they didn’t have the right data analytic tools. He founded Tasio to change that. It’s Thomas’ goal to bring advanced data science techniques to associations so they can be far more successful delivering value to their members.

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