Predicting your community’s behavior can be hard. Many organizations find themselves guessing at member information, outreach and retention tactics. But the data is all there – in fact, you probably already have a plethora of data to help you draw conclusions about member predictors. It’s taking that data to the next level and organizing it that can seem daunting.
Let’s meet community members A and B. They are both avid blog readers within your community, and they’re both up for membership renewal. Wouldn’t it be nice to set up a process to encourage them to do more blog reading, or even start writing or sharing those blogs, in order to increase their chances of renewing? Beyond that, what if A and B have different interests and corresponding community behavior that’s captured somewhere, but no one sees it?
With the right tracking tools, you could compare members A and B using that data collection: transactional data, event attendance data, community discussion data, etc.
Half the battle is simply starting. Your organization has a preexisting informational ecosystem – AMS/CRM database, community platform, website, events, resources, maybe even a learning management system. What data do you pull and why?
The current trend is for large organizations to hire “Data Scientists” on staff. A lot of organizations are too small to dedicate full-time staff resources.
But it’s this line of thinking that should and will trickle down into organizational thinking from the marketing and technical side of things. And when executives are eager to pursue big data endeavors, they will salivate over member data sets you were able to pull and synthesize already.
Anyone can dive into data analysis, and everyone should – it’s information that will pay off in the long-run.
ASAE is conducting a study using its Net Promoter Score data, member retention data, purchase histories and activity data from the community. It’s leveraging automation within the community to take action on its findings. The results are impressive: member satisfaction and retention correlates to member activity within the community.
The ASAE team compiled 56 unique automation rules and 35 monthly KPIs associated with its new onboarding process, with subsequent A/B testing to prove ROI. Initial email conversion results include 16% increase for members’ first posts, 50% increase to keep conversations going and 17% increase for welcoming new members in discussions. Conventional email marketing conversion rates generally hover between 1-2%.
It’s a common thought process to peruse your member data and think, “Great, we only need to track X activities and that will give us the right insight for future programs and campaigns.”
But the whole point of collecting as many data points as possible is to drive future processes and campaigns that will leverage those novel data points, ultimately bringing you better analysis on historic trends. You can’t find trends without tracking.
Here is what might smell like a sales pitch but it really isn’t -- engagement data is largely otherwise ephemeral. You can only get it at the time the activity takes place.
If you limit yourself to collecting only certain types of member data – whether it’s renewals, event attendance or all of your online community’s logins and discussions – you’ll be left filling in large and unexpected gaps. The ultimate goal is a complete, 360-degree view of your members’ wants and needs. There’s a balance between reading your members’ minds and predicting future behavior for everyone’s advantage.
Here’s my favorite comparison: you can bring Amazon or Netflix-like features into your community data and analysis. Think about it the next time you browse Netflix for a new show or movie. It will often promote or suggest similar content based on what you’ve previously watched.
This is being smart about your data, and it’s more than just saying, “If member X logs in to the community and comments on a discussion, send them an email to encourage them to do Y and Z next time.” That is useful automation, but your data has more depth than that.
The data’s value is seen down the line, when it becomes historic and each additional data point on that member arguably becomes even more valuable than previous data points. It’s continuously painting a richer picture of the member’s activity and lifetime with your organization.
You should still gather the data for those “If X, than Y” campaign scenarios, but that same data will benefit you in the long run. Predictive modeling can help you plan for acquisition/retention programs and increasing spend in the right places.
You know the data’s important and you know members are interacting out there right now - don’t try to tackle it all at once. Your processes should build on one another. Try starting here:1. Align organizational and member goals.
It’s arguably the most important strategic move for your community - is what your organization wants lined up with what your members need? If the community can’t reach a consensus, you’ll forever be plagued with conflicting motives and stop-and-go activity on both sides.2. Look over the data basics.
Not even sure what are the best metrics to track? Check out benchmarking reports and models from successful communities. See what actions those communities are looking at (discussions, profile activity, comments, etc.) that can be compared to your onboarding and retention efforts. Gather it and see what’s moving the needle..
Depending on your goals and your budget, there are reporting tools that can integrate with your current AMS/CRM/LMS and online community. Whether it’s marketing automation software for better email campaigns or simply an easier way to wrangle those spreadsheets, do some research to streamline the process for the future.