
In this episode of Associations NOW Presents: Industry Partner Edition, guest host Sharon Pare of HighRoad Solutions sits down with Georgina Donahue, Director of Community Innovation and Strategy at Higher Logic, and Rachel Mace, CAE, Director of IT and Database at the National Pest Management Association, to discuss how associations can better understand members and use that insight to drive smarter strategy. They explain how most organizations have plenty of data but little usable intelligence because systems don’t integrate and staff lack a unified, individual-level view across programs, leading to decisions based on gut instinct and missed warning signs like “silent churners.” The guests distinguish reports from behavioral signals and patterns that predict engagement and renewal, share examples of targeted outreach and pandemic-era webinars boosting recruitment and retention, and discuss using engagement scoring, dashboards, and guidance to act at scale. They recommend auditing where data lives, focusing on high-signal sources, and making incremental improvements rather than chasing perfect data.
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Transcript
Sharon Pare: [00:00:00] Welcome to this episode of Associations NOW Presents: Industry Partner Series, an original podcast from the American Society of Association Executives. I'm Sharon Pare, Partnerships Director at Highroad, and your host of this series throughout the year. This episode is sponsored by Higher Logic.
Today, we're excited to welcome Georgina Donahue, Director of Community Innovation and Strategy at Higher Logic, along with Rachel Mace, CAE, Director of IT and Database at the National Pest Management Association.
Our conversation today is about how associations can better understand their members and turn that insight into smarter strategy. Georgina, Rachel, welcome to the show.
So I think this is something a lot of associations are quietly dealing with, so why don't we jump in? So let's start with something most associations don't want to say out loud. Most of them are making decisions about their members based on very [00:01:00] little actual insight. Why is that, and how common is it?
Georgina Donahue: I think that most associations have more data than they've ever had, right? They have data coming in from all over the place. They have their AMS records, their event history. They have a community platform.
They have email opens, right? So they have this huge bulk of data, but the problem is that almost none of it actually talks to each other, so they end up flying blind even though they have this embarrassment of riches, but they can't access it. They don't know which members are thriving and which ones are drifting, which ones are gonna silently churn in a couple months from now.
And the problem actually is not just small organizations who don't have the resources to wrangle the data. It's large, sophisticated tech stacks see this problem as well because the data exists, but it's just really siloed
Rachel Mace, CAE: Yeah, I would have to echo that. There's a lot of silos. [00:02:00] Almost every time I start a job at an association or even at a vendor that services associations, the first thing we have to deal with is untangle the glut of information that they have, what they want to actually access and use.
And then we also have to talk through, okay, once we decide what we're gonna use, how are we gonna get it there? Integrations remain such a huge problem with most associations. We find that our data lives in completely separate places, and that data doesn't pipe into new places very easily. So that's been a big issue, and it's not the association staff's fault.
We are not integration engineers. We are not high-level data scientists. We came here to work in the nonprofit industry and serve our members. We don't have a background in that expertise. So that data mess exists everywhere, large associations or small associations, and we find that more and more association professionals, whether they like to admit it or not, are starting to realize that they can't make decisions based on the gut anymore, which is how we were making decisions.[00:03:00]
I can even recall way back in the 20-teens encountering a situation where an association professional said, "I have an idea. We're gonna use the power of social credit, so to speak, to get people to reach out to each other and encourage them to join the association." But the problem was this professional was working in a trade association environment, so the other member associations or prospect member associations were competitors, and it's very hard to convince a competitor to join the same association as you.
But their gut said, "I've seen referral campaigns work throughout the private sector or in professional societies where it's the individual that's the member." So they went with their gut, and that campaign didn't work out, and they thought this is a personal failure. It's not. It's just you didn't have access to the insights and data that you needed to safely feel you could experiment with those types of campaigns in a way that's a bit more controlled with a bit more information behind it
Georgina Donahue: Yeah.
I think the other thing that we're seeing in the space is that [00:04:00] as our industry standards for social interaction and for engagement with for-profit brands, for social brands, anything, it rises, right? We're used to having the Netflix algorithm know exactly what show we want to watch next. We're used to logging into a new platform and selecting our content preferences immediately, and then having really sophisticated algorithms understand who we are, know who we are.
So at the same time that our association professionals are trying to sort through this, sometimes relying on that gut instinct, the base of members, their standards are rising because they're used to it in other areas, right? And so that gut instinct is becoming less and less effective for them because there was some grace, there was some buffer there, right?
And now members, because of what they're experiencing in the consumer space, do not have [00:05:00] that grace that they're willing to offer. They're a little bit more frustrated, and they expect us to know who they are, and they expect us to tailor and segment our message specifically to their journey
Sharon Pare: I wanna dig into the gut instinct part a little bit later, but you, Georgina, talked about something you call the silent churner.
Can you explain what that is? Is that like the quiet quitter? I- is that a little bit similar? Tell us a little bit about that.
Georgina Donahue: It kind of is. It is. It's the most dangerous member that you have, because everybody has the members that are squeaky wheels, that maybe they're frustrated, maybe there's some dissatisfaction, and they are telling you the areas that they would like to see improvement.
While sometimes a sassy email might be difficult to receive in the moment, they are giving you very clear instructions about what they need in order to continue to receive value from the association. The silent churner is the most dangerous. They just go quiet, and then by the time they don't renew, they've already made the decision not to renew three or [00:06:00] four months ago, and they've already been quietly stepping away, so they stop attending events, they stop posting in the community, they stop sending sassy emails asking for their hopes and dreams to be fulfilled, right?
And many associations don't find out that a member has churned until the renewal doesn't come through, and it's way too late to make a change because there's already a history of taking a step back and looking for other resources for support.
Rachel Mace, CAE: And this is an area where I feel like associations, their gut actually is probably correct.
They already know who's not gonna renew inside. We know that if you're a new member and you don't do enough with us in that first year, you're probably not going to renew. We know if you're an existing member and your engagement falls off, we know you're not going to renew. We know if you're nearing retirement, you're not gonna renew.
So we in our guts understand and know who isn't going to renew, but the challenge is identifying them proactively and being able to do something about it six months before that renewal cycle [00:07:00] hits. Because once you get to the renewal cycle, it's a little too late to ask someone to open up their wallet and invest in membership again.
So we really need intelligence to tell us, "Hey, I've flagged these bottom 20% of engagers. I need those people to do something, anything." And what they really need, I've always told this to people, is you need to put them in a low barrier to access activity, not something that's gonna require a huge outlay of cash.
If I'm new to ASAE, I'm not gonna tell you to go to the ASAE Annual Conference. That's a huge outlay of cash. But I might say, "Hey, why don't you go into ASAE Collaborate and ask a burning question? It's a private, safe space where you can ask something that maybe you wouldn't wanna ask on LinkedIn or publicly."
It's a great way to get me engaged, give me something sticky to do, and maybe I will think about that as I renew next year. It's not the big ask, it's the ask that's practical and reasonable for me, a low engager. But we as association professionals, [00:08:00] we know that the low engagers, those are the ones who are gonna silently churn, if anyone
Sharon Pare: I want to unpack this a little bit more, and I know you started to dig into this a little bit too, Rachel, but what's actually causing this?
Why can't most associations see the full picture of their members?
Georgina Donahue: I think the reason why it's so endemic across the entire sector is not because association professionals don't want to have a better view, or it hasn't occurred to them that a better view would be advantageous. I think that they're really, they really want this.
But the tools that they use were never designed to talk to each other by default, right? And a lot of times you're making really the decisions about your technology choices, about your technology s- stack. You are choosing best-in-class tools, right? And the best events platform and the best member management platform and the best education platform, but they weren't designed together.
They were designed separately. And so it means that [00:09:00] no single staff member has a unified view of the individual member, right? The membership team sees one thing, the education team sees another thing, the events team has a different perspective. It's all broken up, and it's organized by program, right? I can see which events had the most attendees, but it's not broken out by the individual human, by the person.
I don't necessarily just want to see, okay, which event topic was the most popular. I want to see, okay, who are my bottom 20% and which events did they say no to or yes to, and what kinds of conversations in the community pulled them in, and what kind of emails were most valuable to them? It's this lack of a unified view by individuals across programs is just really elusive.
Rachel Mace, CAE: Yeah, and it's not a problem with the association staff, although they often take the blame and feel guilty when they talk about this issue, but the actual issue is [00:10:00] an architecture problem. These platforms are sold to you, and one of the things that they're trying to give you is the best possible user experience.
So they want you to have the best possible user experience. So their investment when they deliver these tools to you, these best-in-class tools, is often on that user experience. Integrations is often a place where th- we forget, hey, we have to integrate this data, or we have to pull this data into some sort of central mechanism where we can see the whole picture of the whole member, and that's often thrown by the wayside because we wanna make sure that, A, member-facing things are good, and B, association staff user experience is good.
But when I worked in the vendor space, a lot of times integrations were the most frustrating things we had ever had conversations about because we had everything we needed to give the association staff what, what they were asking for, but then we would get held up by simple things like, "Oh, we can't integrate that data because that data doesn't really exist there.
It's a calculated column." And I'm like, "We can't get that calculated column?" And they're like, "No, we have to create a new [00:11:00] table." And you would go down these rabbit holes of these crazy blockers, and you're like, "Wow, how is it 2020 whatever, and I still cannot integrate my data relatively seamlessly?" And it's something that I'm not even seeing AI do a good job of addressing.
These integrations still continue to be a challenge. And I know that when I worked at American Bankers Association, when I first got there, I thought, "Well, I will have so many more resources to integrate the data and see that big picture of the member." And I remember walking in there at that big association with all the investment they can make in technology, and it's worse.
They have more systems, more layers, more silos. I'm like, "Wait, I can't even figure out who's engaging with each other in the community, and I work in membership." So I-- it can be even worse at big associations because you have layers of silos of people that are like, "I'm not gonna make you an admin in my system," or, "That's my system, and I don't really wanna pipe that data back there."
So we have this huge problem, and it's compounded by [00:12:00] silos. It's compounded by architecture. It's compounded by integrations. So even in 2026, where we expect AI will solve all our problems, this is something that I'm not sure that AI at this point can solve.
Sharon Pare: So it really sounds more less a people problem and more of a systems architecture problem, right?
So I guess let's build on that. There's a difference between having data and having insight. What does member intelligence actually mean in practice, and how is it different from just pulling a report?
Georgina Donahue: The data points that you gather are just the stuff that your systems log, right? The logins, the registrations, the email opens, all of that, right?
The signals and the insights are the story that multiple of those data points together paint for you, right? And you need to be able to pull from many different mediums in order to see the story that those data points are telling you. So behavioral signals are what actually predicts [00:13:00] engagement and renewal, and that's the narrative insight that you're really looking for.
So the signals that matter most aren't demographics or clicks or logins or sessions or anything like that. They're the patterns, right? The login frequency, the types of content that's being consumed. And so that's the difference between data and intelligence. It's the context. So a login, if you tell me a login to an online community, I can't really do very much with that.
But if you show me a member who logged in every single week for six months and then stopped logging in at all three months ago, that's a signal. Did the email go dead? Did you get a new job? Are you starting to feel like this is not the right place for you? Are you feeling boxed out? Is there a clique going on that you don't wanna enter into, right?
Things like that. And so those are the types of insights that we're looking for. I'll give an example, and I know Rachel has a really good example of [00:14:00] this too that she'll share. So I previously worked for an education organization, and we provided educational sessions and training, and there was an online community for all of the alumni of that program.
And we had resources about each of the courses in the community, and we were able to manually, mind you, because the architecture wasn't supporting us either, we were able to pull a list of everyone who had reviewed community library content on topic A, and then we cross-referenced it with everybody who had taken the course on topic A.
And we found about 50% of the people who were viewing those library resources hadn't taken the course, and we wanted to drive education. So we created a targeted outreach campaign and said, "Hey, I can see that you're really interested in this topic. I would love to support your development and ongoing education.
I have a course for you. It was so successful, Sharon. It was crazy. We were all [00:15:00] delighted. We had a 50% close rate and success rate on that course, and people were genuinely grateful and so happy. And so that is a story that we built from the data, and then a success-driving approach that we used to bring something really personal that came from that, that we never would've gotten from just how many people viewed library documents, right?
I know that Rachel has examples of this as well, when we finally wrangled the data enough to paint that picture.
Rachel Mace, CAE: Yeah, and I'll lead with the example. So I had the privilege of working with American Bankers during the pandemic, and I say privilege because what I witnessed in terms of how they came together to serve their members was nothing short of jaw-dropping.
So as we went into the beginnings of the pandemic, we had some staff members become subject matter experts on what was going on with the virus, just general stuff from the CDC, and really being thoughtful about how they delivered that messaging. It was a [00:16:00] source of comfort for the staff and a source of kind of that predictable, what's the next step?
Where are we going from here? Is there a plan? And that person and the people supporting that person realized that this was so beneficial to the staff. The staff were giving a lot of good feedback. They took that feedback and said, "Maybe we should be offering this to our members." And they started these webinars offering that to that m- to those members.
And as we're seeing these members hop on these calls, we're also seeing that non-members are hopping on the calls, 'cause we didn't feel, at that point, it was a crisis, we didn't feel we should be exclusionary. What happened was a lot of these non-members getting on the call saw our commitment to delivering timely, relevant, and good information to our members.
They became members. We saw a jump in our retention rate and a jump in our recruitment rate as a result immediately during and following the pandemic because they were like, "Look, this is an organization that's going to support us even through the worst of times." And because we were [00:17:00] providing these resources and being intentional in how we evaluated that data, are we getting non-members coming?
Are we getting members coming? Okay, these five non-members came. Can someone give them a call? Because we were taking action and being very agile in what we were doing with that data, we were able to break records that I don't think even the highest level of management thought were possible, and that's because data is not about reporting.
It is not about sending a metric to your boss and saying, "Okay, we're up 200 members this year." Great. Awesome. It's about informing. We're up 200 members this year because it appears people really love the webinar series we did about the state of the industry. That's the story. That's the why. And if you cannot isolate these things to the why, and you're just reporting, you'll never move to that next step of growing.
And associations do need to grow because there's a lot of competition out there. And Georgina said earlier, the expectation is that you're listening to your members' behaviors. You're watching [00:18:00] what they do with you and adjusting your strategy to match that energy of what they're expressing to you via behaviors what they want.
Sharon Pare: Let's take a quick break for a word from our episode sponsor, Higher Logic. Higher Logic unifies your community, marketing, learning, events, and more into one connected engagement platform so every member touchpoint feels personal. With AI-powered campaigns and vibrant online communities, your members feel seen, supported, and excited to engage every day.
Because everything works together, your team spends less time managing technology and more time advancing your mission. Plus, you get built-in strategic guidance and hands-on support to boost retention and turn passive members into passionate advocates. See how Higher Logic is revolutionizing engagement by booking your demo at higherlogic.com.
So we talk about that bottom 20%, [00:19:00] so let's flip that for a second. On the flip side of the at-risk members, you also talk about power users, your most engaged members. Are most associations actually leveraging those people?
Georgina Donahue: Yes, many are, but many wish that they were able to do so to a greater capacity, right?
Because engagement data is not just gonna tell you about who to save, and we've talked a lot about mitigating risks so far in this conversation. But engagement data is not just about who to save. It tells you who to invest in further, who to really give extra love and care and development to because they are really ready for it, and there's a benefit to your member, and there's a benefit to the organization as well, right?
And so the real heart and the real strength of any association is absolutely its members. And so everybody wants to find a way to leverage members for advocacy, for mentorship, for volunteer pipelines, for peer-to-peer recruitment, for board [00:20:00] leadership positions, anything, right? And that's where the real strength and kind of flywheel of success comes from.
So when you can identify the top 5%, 10% of engaged members, it's really likely that you are looking at a list of your next committee chairs, of your conference speakers, of your community moderators, right? And so if we can find a way to identify them and then throw more and more engagement opportunities to help level them up in their engagement maturity, then that is a win-win for everybody.
It feels really good to members to be recognized for your investment and for your desires to grow alongside an association, and it strengthens the organization to have more insight, more knowledge directly coming from the member base.
Rachel Mace, CAE: And we at the National Pest Management Association do something I actually don't see at associations very often, but it's modeled a little bit after [00:21:00] DELP.
But I don't want to say modeled after DELP, because I don't want to not give them credit. They have done this phenomenal thing, and this is where they identify people who are relatively engaged, and they put them into a program that prepares them for leadership in a board or volunteer leadership in general.
It moves them to the next step educationally so that they always have an incoming class of people who are ready to be the leaders of that industry for the next generation. So one of the things that you wanna look for when you're looking for who might fit well isn't, "I've checked all the boxes." That's a big thing, especially at Association Linux, we would get clients that say, "I'll look for someone who's done a little bit of everything."
That doesn't necessarily mean that your pool of volunteers should come from there. Sometimes your pool of volunteers comes from somebody who attends the annual meeting many times. Sometimes that pool of volunteers comes from somebody who always attends your legislative day. You don't wanna misinterpret that the fact that someone's not engaging in all [00:22:00] the pieces of the pie as some sort of signal that they're not ready to engage as a volunteer leader.
It's a very big problem I think we have, because we're used to wanting to see parts of a whole, and we're like, "Okay, if you complete all five things, you're ready to go." Mm. But you need to meet people where they are. So when you look into your data, you wanna discover patterns. Rachel Mace goes to annual meeting every year, and sometimes she pops into MMCT, but she doesn't always go on to Collaborate, or she doesn't always attend webinars.
Does that mean that she can't be an effective board member? No, it means that maybe she values more in-person encounters than digital connection. So it's very important when you're looking through engagement data to realize that there's always going to be some level of interpretation here. Am I looking for somebody who checks all the boxes?
Probably not. You're looking for somebody who's engaged, and engaged in the way that fits best for them. And that's how you'll discover, when you go through this process, you're gonna have a hidden gem pile, where you're like, "Oh, wait a minute, [00:23:00] this person, we would have never considered as a volunteer, but they really should be a volunteer because they are participating in a meaningful way.
It's just maybe they're an introvert, and they're the inverse of Rachel, and they only want to participate digitally." They can still be an effective leader, even if they're more of a digital participator than an in-person participator. So it's very important as you look at your engagement data not to get too, I call it perfectionist.
Like, with your, with, check all the boxes and do all the things. No. Look for those hidden gems. Look for those insights where somebody is almost all digital. Think about different ways to look at that data, not just, you did an annual meeting, you did the Collaborate, you did this, you did that. Think of it more of, is somebody clustering their engagement in a certain modality?
Are they clustering their engagement in a certain season? Because they could still be an amazing and effective volunteer or a highly engaged member that helps build your membership further.
Sharon Pare: So you've described a data problem that's really an architecture problem. Everything is siloed, right? We've talked about that at the beginning of [00:24:00] this podcast. What does it actually take to fix that?
Where does that technology come in?
Georgina Donahue: It's a really good question. It's one that I am really excited about and think a lot about. We've talked a lot about how most associations, the reason that they're data dark isn't a lack of motivation, it's architecture, right? These tools are not designed to share information.
You can have five great platforms, and you still have a zero unified view of who your member is, right? And so it can be very tempting to be like, "Okay, my tools aren't talking to each other. I need different tools," right? The fix is not to replace everything. The fix is not to rip out all of your tools and try to slot in new ones.
It's convergence. It's creating a single space where all the signals from your existing systems can really come together so that then you do have the ability for an individual staff person to look at one screen and see the full member picture, right? And so at Higher Logic, we [00:25:00] know this is the path that is required, creating that converged space for existing tools, because we've invested so deeply in customer partnerships.
So at Higher Logic, we spearhead something, a group that's called the Customer Innovation Lab, and we have enlisted our members, our association members and customers, to really deeply co-create with us so that we're building exactly what they need, right? And so at any software organization, you need to know exactly what the problems are and exactly where the sticking points are in order to provide a solution that is actually going to create meaningful change.
One of the most exciting things about my role and the way that I interact with associations is by participating in this Customer Innovation Lab and co-creating alongside, right? And because of the fact that we haven't just assumed what's necessary, we're using feedback and ideation sessions that are fueling Higher Logic to [00:26:00] develop a new product.
We are creating a 360-degree view of your member, so a single source of truth that pulls together all of your members' activities across Higher Logic tools and systems, and every other system that your association uses, right? So you pull in the data from your AMS, from your email platform, your event tools, anywhere that you are gathering data and any surface area where those interactions are happening with your members.
We have built this tool with integrations at the center and visibility at the center. So for the first time- You can come in and you can look at one record, and you can see the complete picture of that member. And so you can finally know your member as well as they expect you to and as well as you want them to.
So you have your community behavior, your event history, content consumption, all of it in a single place. So I'm really excited to have [00:27:00] worked so closely with our customers and with association professionals to craft this solution and offer it back to the people that are doing such important work.
Rachel Mace, CAE: And with that being said, you're giving us something new to work with, but the onus is on the association.
We're seeing this shift where vendors are like, "We want to give you what you're looking for." Then when we get what we're looking for, we as association professionals have a big job to do, and that first job is to make sure that our staff, 'cause architecture is a problem, but silos are, too. Our staff need to understand, hey, here is this new tool.
We don't need to silo our Higher Logic or our AMS. We don't need to silo these tools. We need to encourage staff members to get into these tools and start using that data. And if you sit in a role like I do, information technology and database, which is a big many hat role actually, your job also is to serve just like you would serve a member, is to serve your [00:28:00] staff and say, "Look, here is a tool you can use.
Here's what you can get from it. Let me know where the gaps exist," and encourage them to take some experimental leaps into these tools and start making informed decisions. Because a lot of times you'll deliver a tool to someone, and I know this from the vendor side, and they'll say, "Okay, now what?" The “now what” is you, and we need to find a way to come together as association staff.
It's not, "This is my member data over here" anymore. It's, "This is our member. How can we each make a difference serving them?" So part of the role of an IT professional in the association space is to socialize using that data, starting to experiment with that data, and making informed decisions using that data.
It- the onus has to be on someone. Someone has to take ownership of that, or that data will just sit there. You'll have an amazing tool, and that data will just sit there. So it's ex- incredibly important that as we get tools like this, not only do we [00:29:00] use them in the roles that are like the community manager, but we encourage the rest of the staff at large to take part in using these tools.
And then as we get using these tools, if there are deficits, rather than stop using the tool, it's important to relay back to our partners, like Higher Logic or other partners in the space, "Hey, you've built this tool. I really like this tool, but here's where it's not serving me." Because if you don't give that feedback to these vendors, they can't possibly know what you want.
They'll just know that you stopped using it, but they won't know the why. So it is on us also to give data back to them and say, "Okay, I'm having a hard time getting my membership and meetings team using this data because..." and then you answer that question.
Sharon Pare: So now you have a unified member view, but most asso- associations have thousands of members, sometimes maybe tens of thousands.
How do you actually act on all that data at scale? How do you go from visibility to strategy?
Rachel Mace, CAE: So this is something that frustrates me as an association professional because [00:30:00] a lot of tools will get you right to that point. I've even worked with several very brilliant people on a predictive tool, and it hands you on a silver platter the data.
It says, "Oh, these are the people that are likely to renew. These are the people not likely to renew." You get that, and then your customer said, "Okay, now what?" You're like, "Well, do something with it." They're like, "What do I do?" And this is because association professionals have a very unfair lot in life because they are expected to be data scientists, strategic professionals, executives.
They're expected to be so many roles, all those hats we always talk about. But at the same time, when you get all this data, you're like, "I don't want to put anything at risk by making a decision I shouldn't make, and this is a little outside of my normal purview." So you have this discomfort with what do I even do with this information?
Georgina Donahue: And I completely agree with Rachel that visibility is step one, but then what are you supposed to do with [00:31:00] it after? Once you have the information, what's the next step? And so the answer there is really surfacing and support. And we, as a vendor that supports associations, think a lot about that. Not just how do I hand the data over, but how do I fully support this group of professionals and help guide them through the best choices based on the data that we have, right?
So one of the things that we've been working on, and that I have the honor of working on directly, is using dashboards and engagement scoring to let the data tell you where to focus. So you shouldn't have to dig through every single record. The system should show you. The system should say, "Here's your at-risk members, here's your power users, here's your enga- engagement that's trending, and here's the next step.
Here's what most people tend to do when they have these types of results. Here are the best practices for how you fix this problem. Here [00:32:00] is the triaging phase," right? "Your data shows this. Here's the diagnosis. Here's the most likely approach that is going to create a positive outcome for you." So that's one of the things that we're building with Higher Logic's new suite of dashboards, specifically for the community product, is really surfacing all of the engagement signals that matter across your full community member base and pairing them with the actions and next steps, right?
We don't just want to give people a chart. We want to give them a pathway, guidance on how to interpret your data, validated recommendations for next steps based on years of community data from our user group, HUG, right? All of the next steps, the signals, the things that point you towards the areas to focus next.
And that way you can really support your membership base without burning out your staff, asking them to do 200 different jobs at an A+ level 100% of the time. Of course, support is [00:33:00] required.
Rachel Mace, CAE: And I'm very excited about this development because a lot of associations, even big ones, don't have a really big community staff looking at that data, working with that data, fostering the engagement in the platform.
So having this is like having an unpaid assistant on your staff. Now you have somebody kind of serving up this information to you so that you can just be action-oriented. More actions, more experimentation, more work, as opposed to more chasing numbers or reporting numbers. So I'm extremely enthusiastic to see what comes out of this.
Sharon Pare: Because visibility alone isn't enough, right? You want to actually do something with it. All right, so let's make this real. Rachel, let's turn this to you. Let's talk about what actually changes day to day for association staff when they have this kind of member intelligence. How does a job look different?
Rachel Mace, CAE: So one of the things that we were working on in Association Analytics, myself and Heather were talking through what do we inform people about what their job will look like? Because a lot of [00:34:00] times there's a little bit of fear. Okay, I have all these tools now that are doing part of my day-to-day. It's painful work.
No one loves doing VLOOKUPs all day, but at the same time, you're like, "What am I going to do next?" I want to give you hope. This means that you get to use the whole part of your brain. Your job is no longer reacting to data, reacting to numbers. Now you're proactive. Now you get to be strategic. You get to grow, you get to experiment.
You get to actually move the needle on what members want and value. And if something doesn't, you can factor in, "If this doesn't work out, we'll pivot to this." Factor in your pivots. This will make your career so much more robust. Now you're becoming an expert in these types of decisions, as opposed to a reactor who reports numbers.
And if you really want to grow as a professional, it's important for you to get ahead of reaction and start thinking proactively about doing something new. One of the things that really attracted me to NPMA was that even though they have data challenges, they're extremely proactive. They're like, "Let's get [00:35:00] ahead of this.
Members seem to be talking about this. I see enthusiasm behind this." They look out at the marketplace, and they react to those inputs, even though they have to do a lot of it manually, because they are essentially a member-driven decision engine, not a member-driven reporting engine. And they spend less of their time digging and sifting through numbers, and now that they've hired me, I can dig and sift a little bit for them so that they can actually get some validation behind these programs.
But they run on all cylinders member facing. Member facing is the ultimate and first priority, and I would love to see more of that in the association space, because a lot of times we get stuck in our job or we're just reporting internally. We're almost invisible. But once you get out there, your entire staff is fostering relationships with the members that they serve, you're going to see that your members become obsessed with your association.
They're like, "This is somewhere I want to be. I want to be a part of this." Naturally, just by you engaging in that way with your members, your membership will start becoming more sticky. [00:36:00] Your meetings will have a feel of authenticity and enthusiasm that they didn't have before. So it's important to embrace that part of that slugging through reports may be a p- a thing of the past.
Embrace these tools and get out there and start producing things that your members can see and give you feedback on, ultimately value.
Sharon Pare: For an association that's still flying blind right now, no unified views, decisions based on that gut instinct we talked about earlier, what's the one thing you'd tell them to do first?
Georgina Donahue: I think they're gonna take this advice, Sharon, because the picture and the beautiful vision of the future that Rachel just painted is so exciting, and I'm betting that folks are gonna be really galvanized by that. I would say that the first step is do an overview, take an-- Start with an audit of where your member data actually lives today.
And I'm not talking about the kind of hopeful interpretation of where it should be or the vision of the [00:37:00] future just yet. Where is it actually? And list every system that knows something about a member that you use to make decisions about serving your members, right? And then ask which of those systems has the richest signal source.
Where are you getting the insights from? Where does the story start to jump out at you from in terms of those systems? For most associations, it's community behavior that is the m- that is the richest, the logins, the posts, the replies, and also event data, what people are attending, because those signals are reflecting active engagement more than passive receipt, right?
So that tends to be where it will come from. But of course, look at what makes sense for you. It might be different in your association, so look at that. And then, of course, I also recommend keep an eye on us. Keep an eye on Higher Logic. This is gonna be a really exciting second half of this year, and I am so jazzed to bring this to the space, [00:38:00] because that unified view of your member that is deeply built on visibility, highly sophisticated integrations that you're supported through, as well as dashboards and data that walks you through the next steps, is gonna be an incredible game changer.
And there's all sorts of, of kind of fun and really powerful features that are in there. Dynamic list building, show me everyone who this story applies to, those types of things, as well as automations. And of course, there's a little AI mixed in there, too, as every new product has. And so I'm really excited to see what types of changes happen there.
But for today, start with where the data actually lives. Look for the systems that are giving you the richest signals and the most compelling stories.
Rachel Mace, CAE: I totally agree, and I will add a piece of advice that I have said for years and I wish that more people would take to heart. And I'm talking to myself first because this was a hard point for me to change in my own personal professional journey.
[00:39:00] I am the culprit of this more than probably anyone else, but stop chasing perfection in data to make decisions. The longer you slug over validating data, the longer you go through the process of, is this the right data? Is it perfect? Most people also are fighting over the last 5% of data and then not making decisions because the last 5% isn't correct.
Instead, enough for a trend, that's all you need to start making decisions. Stop chasing perfection. Get good enough to make an incremental improvement and make those incremental improvements, observe, and then improve more. I have a prioritization board right now, and it's all based on incrementalism. I'm not looking to reinvent the wheel with our tech stack overnight.
It's let's use this one feature. In fact, I'll be finding people at Higher Logic Super Forum to ask a couple of questions to make the user experience for our staff members better on the Higher Logic side because I want incremental improvements so we can continue progressing how we use these tools. [00:40:00] So today you could go look at your members up for renewal if that's the time of year for you, or if this is the time of year where you're opening up registration for a major conference in the fall, look for one incremental improvement you might be able to make to that process.
Can I send a better letter to my members before I even invoice them? Can I send them a quick survey or some sort of communication? Can I normalize talking about what we've done throughout the association throughout the year before I send out the invoice so they know, hey, I'm not just asking you for money, I have delivered for you this year.
Do one thing, monitor it, look at it. Don't wait for perfect data and say, "Look, data's pointing to this being pretty effective. Let's expand on that." Incrementalism, stop chasing perfection, and I think you will see a huge payoff from that effort.
Sharon Pare: Rachel, Georgina, this has been a really incredible conversation.
I know we could talk more about it, and I know you've got a big conference next week to be able to really [00:41:00] dig into this with your users and of course your clients as well. There's a lot of really practical insight here for associations, so again, thank you so much for taking the time today. Thank you.
Thank you. Thanks to everyone for listening to this episode of Associations NOW Presents Industry Partner Series. Join us each month as we explore key topics relevant to association professionals, discuss the challenges and opportunities in the field today, and highlight the significant impact associations have on the economy, the US, and the world.
We want to give a big thanks again to our episode sponsor, Higher Logic. For more information or to book a demo, visit higherlogic.com. Be sure to subscribe to our podcast on Apple, Spotify, or wherever you listen to your favorite podcasts. And for more information on topics impacting the association space, visit Associations Now online at [00:42:00] associationsnow.com.
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