Every day, community managers spot opportunities hiding in plain sight. A member’s pointed questions about a product they don’t yet own hint at interest. Another drops insights that practically scream “future advocate.” Yet, these moments often fail to make their way into the hands of other teams or larger business strategies.
It’s a common disconnect—and one explored in the latest episode of “Power of Connection.” Host Paul Schneider from Higher Logic sat down with community leader Nicole Saunders to tackle how AI is finally bridging the gap between community interactions and business outcomes. Here’s a look at the key takeaways.
Note: Elements of this content have been lightly edited for concision and clarity.
At its best, an online community connects user activity and business insights. But for many teams, realizing that potential comes with a challenge: the work is both manual and, often, handled by a small team.
Nicole shared her experience: “My team used to call me the spreadsheet queen. I had spreadsheets upon spreadsheets tracking which users were engaging with specific topics or areas of the product. Then I’d flag it to their CSM to bring it up in their next meeting. Or I’d notice a user suddenly providing a lot of feedback on one area of the product and think, ‘We better get their account manager involved.’”
The approach worked, but only because of the sheer effort involved. Tracking user behavior, identifying patterns, and flagging opportunities required hours of manual work—hours she didn’t always have.
And Nicole’s not alone. As Paul pointed out: “For many, managing the community is a job on top of their job. Even when a company has a full-time community manager, their focus is usually on strategy. They don’t have the capacity to track every potential business opportunity in the community.”
This tension—between what a community could deliver and the resources available to make it happen—is the defining challenge for modern community management. The solution isn’t asking more of already overstretched teams. It’s giving them the tools to surface the right signals at the right time, so no opportunity slips through the cracks.
For overburdened community managers, AI offers more than just efficiency—it’s a way to change how they work. By automating manual tasks and surfacing critical signals, AI shifts the focus from micromanaging details to driving high-level strategy.
Paul described how tools like Higher Logic’s upcoming Nexus technology aims to bridge the gap: “Communities tell a big part of the story, but only part. When we integrate community data with a CRM and other tools that house customer data, we can identify meaningful signals—like a user repeatedly viewing an add-on product they don’t own—and alert the right team members with all the context they need to act on it.”
These signals translate into tangible business outcomes. “You no longer have to hope the community manager notices every trend. Now, systems like Nexus surface opportunities automatically,” Paul explained.
While some of these capabilities exist today, such as integrating community data with customer success platforms to enrich account profiles or trigger alerts, Nexus represents the next leap forward. It broadens the scope, making these insights more accessible and actionable by connecting the dots across the entire customer ecosystem.
Nicole also called out how AI is poised to change advocacy and engagement programs. “It’d be amazing to understand who’s starting to be more active, who’s starting to produce content instead of just asking questions. Those are the people I should be getting into my advocacy program. If I can automate an invitation or at least a ping to a CSM to say, ‘Hey, should we bring this person in for advocacy?’ that’d be a huge win.”
AI is shifting community management from reactive to proactive, giving teams the tools to spot and act on opportunities with precision. But there’s another layer to the conversation: demonstrating the measurable impact of these efforts.
One of the biggest challenges for communities has always been proving their business impact. Community managers know their work drives engagement, loyalty, and advocacy. But tying those activities directly to outcomes like revenue or customer retention is a tougher sell.
Nicole put it simply: “Every time there’s a recession, we see contraction in the community space. People intuitively understand that relationships are important and that communities hold a wealth of data, but extracting that data and articulating its impact has always been hard.”
This disconnect complicates ROI conversations and creates barriers to internal buy-in. Without clear links between community activities and team goals, departments like product or customer success can be reluctant to engage.
“It’s a constant battle,” Nicole explained. However, this lack of alignment isn’t for a lack of trying. Community managers often go to great lengths to engage other teams, offering incentives, building dashboards, or requiring participation quotas.
But even with these efforts, Nicole shared how participation can feel like searching for a needle in a haystack: “They’re swimming around, looking for a customer name they recognize. And depending on the setup, they might not even recognize the avatar or username, which makes it harder to connect the dots.”
And the missed opportunities pile up. A customer’s comment about a challenge they’re facing might signal a cross-sell opportunity, but it goes unnoticed. A member’s growing activity could indicate renewal risk, but without context, it’s just another post in the mix.
This is where AI steps in, not as a replacement, but as an amplifier. AI can sift through the noise, surface patterns, and provide the clarity that has eluded community teams for so long.
With AI, community managers can:
Instead of a disconnected stream of posts and comments, communities become a source of intent signals. Teams start to see the community as a strategic partner. Engagement becomes a business lever, not a black box.
By making these connections clear, AI helps communities prove their value, not just in terms of warm-and-fuzzy engagement metrics, but as undeniable drivers of growth and efficiency.
For Nicole and Pauls’ full take on what AI means for community management, subscribe and catch the full episode. They also dive into how AI is pushing communities to own the industry conversation. Plus Nicole makes the case for merging community and customer marketing, drawing from her experience leading both teams.