When you combine deep analytics with insight into your membership, you can make informed, powerful decisions that will maximize membership engagement. But, how can you turn analytics into more engaging interactions, content and relationships?
Data analysis is about performance
Simply said, it's a way of understanding more about your association through collecting data, analyzing it, comparing it to your desired results, and making decisions based on that comparison. Data analysis is all about performance - how well is your association doing vs. how well do you want it to do. With actionable metrics in hand, analytics will help drive your decision making process to run your association more smoothly, but in order to do so, you need to have to have an understanding of how it works.
- What do you want to understand? It begins with identifying your key performance indicator or KPI, which becomes the basis of evaluating the association's objective. What is it that you want insights on, for example, the number of new members joining the association each month.
- How will you determine the effectiveness? Next, you have to gather the metrics that you need in order to track and understand that area. For example, the number of people that go through your onboarding process each month.
- How will you track that data? This is where we get into being able to measure and track your data. Do you have reports that breakdown this information for you?
- What is your desired result? You set a target for the measurement. What is your ultimate goal or target? An example could be 30 new membership inquiries a month.
- What do you do if your results are not met? If your measurement is less than your target, you need to be able to identify at what point you no longer will be able to meet your goal. In other words, identify your threshold.
The most important thing about all this data is that it drives the decisions you make and helps your association perform better.
Different types of association metrics
Of course, there are lots of different metrics you can measure, and it's important to do so, in order to become more member-centric and successful. While some can be measured directly with existing data, some metrics require a little more research, in order to get the bigger picture.
- Engagement - the amount of time members spend interacting with your communications or your community.
- Individual revenue spend - the amount individual members spend on their membership dues, event registrations, product sales.
- Total revenue spend - how much money your association is bringing in on a periodic basis, subdivided by areas such as membership types, sponsorship fees, event registrations, product sales, etc.
- Lifetime value - the average lifetime value of a member and how long they have been part of your organization.
- Advocacy - which members are more active when it comes to promoting membership to their contacts through referrals.
- Marketing - tying areas like advocacy, membership inquiries, email performance, how active the association has been and more to help push marketing efforts.
- Profitability - the difference between what you make from membership dues and what you spend.
Intelligence in your data: cause and correlation
One vital area to consider is how all of your data fits together and influences the actions of your members. The right association management software can give you deep insight into cause and effect - how what you are doing in your association influences what your members do. For example:
- open rates on emails and engagement with your CTA's
- participation in your online community and how it relates to membership renewal
- number of events vs. the likelihood of increased registrations
This type of information can really help drive membership success, and maximize renewals. When you identify positive trends, you can repeat the actions that caused them and continually improve things overtime.
Using metrics to enhance your association and member engagement
It's worth restating - data analytics and metrics are only worthwhile if they drive action in your association, and they need to be tied back to the decisions you make. For example, if you’re measuring the effectiveness of your association’s marketing, you would want to know the main places your new members are coming from. If your data analytics tells you it's primarily through social media, you might want to put more funding into Facebook advertising.
Another way to use data is to test things — if you find out that members are leaving because of renewal pricing you can test out different rates to find the right balance of cost and value.
Data analytics can also be used as part of a “continual improvement” process. Data shows you there’s something not working well in your organization, you fix it, keep an eye on the data and see if the fix worked. If it did, you move onto something else, if it didn’t, you try a different fix. You do this over and over, optimizing every part of your operations. This becomes a continual feedback loop and lets you polish everything in your association to perfection.