Aptify

I have had the pleasure of working in the association industry for a very long time and remember when business analytics consisted of relatively few metrics like:

• Is our membership growing or declining?
• How many Active v. Associate v. Student v. Inactive v. Retired members do we have?
• Are we tracking to budget?

You get the picture. The ability to pull information was limited to a few variables which generally took hours if not days to compile in spite of a centralized data repository. By the time the information was ready for presentation it was stale…but it was the best we had.

Today with the phenomenal tools we have at our disposal there is little reason why any organization should lack the wherewithal to provide real time or near real time metrics on a wildly expanded number of metrics with a granularity previously unthinkable.

I recently met with a client who is beginning to embrace analytics in an assertive manner. This association is collecting data points on each member with a goal of creating member segmentation beyond the traditional groups. They believe the outcome will be the identification of crossover groups of members (think Venn Diagrams).

By using a minutely segmented model, they hope to develop precise areas of interest based on very specific member attributes. A benefit of this approach is the reduction in superfluous email blasts to members. The CEO confided they often send fifteen or more emails per week to each member. Not only is this a waste of the association’s resources, it has been a grand annoyance to the organization’s members when the vast majority of the emails hold absolutely no relevance to that member.

Once the association knows the needs of a particular group, the plan is to identify and model a number of potential programs for each niche group. The association already has a pretty good understanding of the penetration rate for programs offered to their members. Likewise they are able to assess the cost of producing, marketing and delivering the program over the program’s relevant life cycle to determine the break-even point and estimate if or when they are able to reach profitability.

An interesting corollary to offering programs tailored to a group’s specific needs, the association expects the perceived hassle factor experienced by members to decrease by virtue of receiving fewer irrelevant emails and blanket marketing promotions which by extension will reap significant positives for the association. The supposition is by demonstrating an understanding of the individual needs of every member, the association expects to increase member retention and acquisition so while a particular program may result in marginal new revenue the association expects to enjoy collateral benefits which they believe will impact gross membership volume; provide an increase in member participation via social media, content creation, increased volunteer activities and amplified attendance at quarterly and annual events.

I plan to stay in touch with the association and will report to you on their progress, successes and lessons learned.