5 Strategies for Data-Driven Membership Recruitment

The acceleration of “big data” is changing member expectations. Companies like Amazon are collecting and using data about their customers to provide an unimaginable level of personalized service. That means your members now expect the same from you.

A one-size-fits-all approach will not get your association results. That said, data collection and analysis is difficult and time consuming. Here are five strategies to get you moving towards a data-driven membership recruitment culture:

1. Focus by identifying key metrics.

Perhaps you have too much data and don’t know what to do with it. Or you don’t have enough and have developed a 100 question member survey to collect everything you could ever want to know. Taking time to evaluate your organizational goals and strategy to determine the key metrics and information you need will help you focus, leading to better data and better results.

2. Create a user-friendly dashboard of key member metrics.

Conveying key data in an easy-to-read format, preferably visual, is the first step in analysis. Using a consistent dashboard format allows you to establish what your metrics are. Updating frequently allows you to identify patterns and trends.

3. Build a hypothesis and then prove it.

You probably already have several hypotheses floating around your board, staff and committees. Assumptions that start with “everyone” or “no one” are a good place to start. Starting with assumptions and then proving or disproving them is a great way to move toward data-driven decisions.

4. Take it one problem at a time.

Define the problem or hypothesis. Measure relevant data and conduct basic analysis. Analyze correlations and patterns. Implement improvements based on the information. Control the change by deploying tests and monitoring key performance indicators.

5. Consolidate your data.

Consolidating your data into one central receptacle (database, dashboard) is key to easily monitoring, building and analyzing your information. If data is difficult to pull, you will not likely compile often enough to make significant improvements.