Having a strong spreadsheet template—along with valuable data points from within your organization—can help make member forecasting an essential planning tool. It can even help you boost renewals.
When it comes to understanding what your membership picture will look like a year or two from now, a little data crunching can go a long way.
Beyond being a boon for spreadsheet nerds, a strong member forecasting tool can lead to effective ways to boost renewals and increase interest in member services.
Robin Muthig, who served as director of membership at the Biotechnology Innovation Organization (BIO) before leaving that role earlier this month, says that the strategy is particularly effective for organizational members who have to account for member dues within their annual budget.
“For us, it feels like an extra way to make sure that they’re going to renew their membership,” Muthig says. “Right before most people are planning their fiscal year and for their budgets in September, [in] October, we send them an email that says, ‘Here’s what we think you owe and dues for us next year.’ So, we rarely get a phone call that says we forgot to budget for renewal.”
Of course, “rarely” has exceptions—during the pandemic, the renewal picture faced uncertainty. The good news was that most members were renewed through 2020, but the question was whether they would stick around through 2021. Muthig—who recently presented insights on this topic at ASAE’s Marketing, Membership & Communications Conference (MMCC)—says BIO took a conservative approach in their forecast, but the organization was able to avoid many of the worst potential fallouts because of strong investment in the industry.
“Our member companies were doing well, even those that aren’t working on COVID,” she says. “We were very lucky there.”
Some suggestions from Muthig for effective member forecasting:
Find a good template. Muthig speaks of the spreadsheet BIO uses, which was the basis of the template she shared during MMCC, in hallowed terms. “That is our magic document that we live in all year,” she says. The spreadsheet requires a bit of setup—Muthig says that every association member needs to be accounted for, including their dues basis (how much they paid in prior years, how much they expect to pay next year, when their renewal date is, and so on), as well as traditional retention and drop rates—but the result is a document that your organization can build around each year as you optimize your member renewal operations. “The other thing that’s key is to know how your accounting works,” she adds—explaining that quirks in the way people pay could have an impact on the overall shape of the forecast.
Learn what makes members stay. A good approach to member forecasting can help to highlight areas in which the association can improve data points such as retention rate. In the case of BIO, Muthig says that, at a high level, there’s an 85 percent chance that any member is going to stay. But parsing out the data opens up an opportunity: If a member signs up for the organization’s purchasing group, the odds become closer to 99 percent. “It is a chicken and egg kind of thing there, but looking at our engagement has made us better understand our retention and vice versa,” she says.
Build your forecasting program with input across departments. While spreadsheets can play a key part in building your member forecasting, their value increases if they begin with input from departments that can help shape the final result, Muthig says. For organizations starting out, it helps to get relevant stakeholders together to determine the approach. “You want your membership team, your finance team, and then you want someone from whatever departments are interacting with members on a regular basis,” she says. For BIO, Muthig says that they brought in the policy team, which often interacts with members around federal government relations—and that those teams were able to offer up useful information around whether members were likely to renew. Also important: collaborating with the IT department so that the most valuable data—quantitative and qualitative—can be accessed.
Account for different membership models. Clearly, a forecasting model would work most easily if everyone were on a calendar cycle, allowing for forecasting that can be consistently and reliably measured. But that’s not how memberships always function—members may sign up during different times of the year, or there may be external factors that discourage a calendar-based approach. In the case of BIO, there was the need to account for members who want to sign up for the annual meeting—away from the calendar cycle. “That’s a key factor to bring into that spreadsheet when you build it,” Muthig says, so that you don’t add income for the next year onto the current cycle.