Several experts and leaders of trade associations joined the Chronicle to discuss how data can help organizations recruit, retain, and engage members.
The panelists agreed that involving other departments — like communications, programs, or operations — is critical to using data to attract and retain members, which includes, for example, establishing priorities or data collection and storing information in a centralized place.
“It’s about a mentality within the organization about sharing with each other,” says Mike Skiados, managing director of membership strategy and engagement at the American Institute of Architects. “This is not your data. This is not my data. This is not the chapter’s data,” says Skiados. “This is our data, and we are all going to use it together in a way to better move the organization forward.”
Skiados was joined on the panel by Katherine Matthews, assistant vice president of data and analytics at the National Council of Architectural Registration Boards, and Amy Hemphill, former senior director of member relations at the American Society of Association Executives. The session, Using Data Analytics to Track and Retain Members, was hosted by Margie Fleming Glennon, director of learning and editorial products at the Chronicle.
Read on for highlights, or watch the video to get all the insights.
How to Decide Which Data to Collect and Analyze
Determining the best data to cultivate donors depends on the organization’s strategy, says Skiados, who noted that sustainability and equity are currently major priorities for the American Institute of Architects. The group has also focused intently on who their potential members are, and uses data to craft different approaches to different groups, from new graduates to industry veterans, for example.
“Using the data to really clearly understand who those individuals are, where they are on their pathway and their career, is helping us to find how we better reach out to the members right now,” he says.
For Hemphill, defining data priorities means first bringing colleagues to the table: An organization’s sponsorship team, for example, will have needs that are distinct from its learning team or events team, she says.
“We all use data in different ways,” says Hemphill, who also emphasized that groups must first lay a sturdy foundation by creating clear processes for collecting data to ensure consistency in the long run, and those processes should be guided by an organization’s overall strategy, as Skiados pointed out at the start.
Practical Applications for Data Insights
Once you know your organization’s data priorities, you can use them to help update your group’s membership structure and offerings to better serve your audience, the panelists said.
At the American Institute of Architests, Skiados has been working on a data-backed project meant to help modify and streamline the group’s longstanding membership structure to better reflect the kinds of services and support members need now.
They’re also using data to better understand their audience and engagement strategies, with the hopes of welcoming a more racially and gender-diverse pool of members.
Hemphill recommends that organizations lean on their members to help with such data-driven overhauls. Oftentimes, she says, members are eager collaborators in data processes meant to improve their experience and can play a vital role in spreading the word to their peers.
At the National Council of Architectural Registration Boards, Matthews has been involved in a process to overhaul the group’s member portal in ways that reflect feedback they’ve received. The organization is including more demographic information and allowing members to change their name and pronouns on their profiles, for example.
“It is really important to take a small slice approach and be in constant contact with that customer feedback,” says Matthews, who noted that communication with members can help avoid the pitfalls of “designing in a vacuum, and then wondering why nobody likes it.”
Tracking Member Engagement
Many groups strive to improve engagement with members, but Skiados says it’s important to start first with defining what engagement is.
The American Institute of Architests has developed a focus on five pillars of member engagement, which range from communication, or the ways that members interact with its content, to satisfaction, a measure of how members feel about the organization in general. The group uses the different frameworks to better understand how members are already engaged and how to assist them in reaching higher levels of engagement, says Skiados.
Matthews sees a lot of enthusiasm among the 55 U.S. architectural registration boards for learning more about how data can help people in their jurisdictions reach career goals.
“We worked with some of our member boards to come up with benchmarks and put together these monthly reports that we share with them,” says Matthews, who noted that tracking the places where members don’t engage or lose track of their career goals can be equally important.
“We’re trying to look at all of the people who are on this path, the different stages they’re going through, and figure out where they’re unable to engage,” she says. By doing so, they can predict and help improve places or stages where candidates for architectures’ licenses are facing setbacks.
Creating Data Hubs
Oftentimes, key data can be spread across different teams in an organization or held in different depositories. The panelists recommended that groups spend time developing a “data lake,” or a centralized place for storing much or all of an organization’s data.
To get started creating a data lake, Matthews says, first try to create a map of your data ecosystem.
At this first step, Mathews says, “you’re not necessarily getting to the part where you are consolidating it all into a data lake. You’re just understanding all of the different places where your data lives, how it’s connected, and how it’s talking back and forth.”
To avoid confusion, be sure all of your colleagues in different departments use the same terms for elements of a member’s data. “If you’re not using that same terminology across the board, you can’t sync things up,” says Hemphill.
From there, it becomes much easier to begin consolidating your information into one place, which can take many different forms and levels of complexity, the panelists say, especially as data teams are first starting out.
