In my experience, quite a few association executives have a difficult time describing how they would categorize their “best” members. One of the reasons this is a challenge is due to the fact that association/member relationships are incredibly multifaceted. They are therefore much harder to quantify in value than a typical vendor/customer relationship. Since members are so much more than customers, their activities within an organization need to be considered along with more traditional metrics such as years of renewal and financial transactions.
The concept of tracking and acting on the level of
member engagement is increasingly becoming a hot topic with executives I speak to. The goal is to define an aggregate score that incorporates data from a variety of activities into a singular measure that can easily be evaluated. Just as examples consider factors such as:
- Meeting attendance
- Earning/Maintaining Certifications
- Committee positions
- On-line forum moderation
- Social networking involvement
- Speaking assignments
- Authoring articles in a journal
- Financial Activities/Impact(Buying Products, Renewing Dues/etc)
Each association is different, so the weightings tied to each activity type need to be different. Additionally, the approach to weightings may change over time based on the strategic plan of the organization and its areas of focus.
Once you have a conceptual framework for defining engagement levels,
use the information. For one thing, make sure that whatever system you are using to manage the data displays the engagement score prominently to users. Additionally, leverage this engagement score in your marketing and outreach as well as throughout your service delivery when considering the level of prioritization you afford to each inquiry. As I mentioned in a
prior post, you can use this type of information in a predictive analysis effort quite effectively too.
Most importantly, experiment with different models and stay agile so that you find the approach that suits the characteristics of your organization best.