Featuring special guest:
Dave Hansen, Global Customer Advocacy Program Manager, Siemens
In this episode of The CustomerX Files, we tackle a challenge that’s becoming more common — yet remains surprisingly under-addressed — in customer marketing: the divide between customer advocacy and customer community. These two functions often operate in separate silos, but they’re more powerful together. When aligned, they can amplify engagement, deepen relationships, and prove measurable business value. In our no-fluff conversation, host Alison is joined by Dave Hansen, Global Customer Advocacy Program Manager at Siemens, to unpack how to end this turf war — and why doing so could dramatically accelerate your program’s influence.
Dave and Alison begin by exploring how organizations often treat advocacy and community as distinct, disconnected engines. On the one hand, advocacy programs are built to identify and activate your most enthusiastic customers — champions who can act as references, provide testimonials, or participate in case studies. On the other hand, community teams focus on online engagement, discussion forums, peer learning, and product feedback. While both are critical, they frequently lack communication, shared goals, or intentional overlap.
This separation creates friction and inefficiency. Programs miss out on advocates who can strengthen the community, just as communities lack structured paths to escalate their most engaged participants into advocacy roles. The result? Missed opportunities, wasted resources, and a fractured experience for your customer base.
Dave offers a clear, practical framework for bridging the gap — one rooted in collaboration, shared ownership, and intentional strategy. Here are some of the key tactics discussed:
Rather than forcing advocacy and community to “get along,” approach them as complementary parts of a unified customer engagement engine. Develop shared goals around customer influence, retention, and satisfaction.
Use community signals as a way to surface potential advocates. Look for highly engaged community members, subject-matter contributors, or peer helpers. These individuals already show up and contribute — which often makes them ideal advocate candidates.
Design workflows and measurement frameworks that span both functions. Use advocacy metrics (like reference usage or content contribution) alongside community KPIs (such as active users, posts, and peer interactions). Then tie both sets of data back to business outcomes — whether sales, renewal, or customer satisfaction.
Advocacy and community teams should not just talk — they should plan together. Create cross-functional working groups, joint roadmaps, and recurring alignment rituals. Building shared ownership helps ensure both sides are working toward mutual value, not competing priorities.
This episode doesn’t just cover theory — it’s a call to action. Dave and Alison emphasize that if your customer marketing strategy is in “maintenance mode,” you’re missing a chance to shift into momentum. By terminating the turf war, you can transform stagnant or siloed programs into coordinated, high-impact movements that generate ROI, deepen customer loyalty, and amplify your most powerful voices.
The payoff is real: smarter connections, a pipeline of advocates emerging from your most engaged community members, and a unified measurement model that proves the value of both functions.
Who Should Listen
This conversation is tailored for anyone working at the intersection of community and customer advocacy — especially:
If you believe your advocacy and community efforts could be more than parallel tracks — if you want them to drive shared impact — this is a must-listen episode.
It's only natural that many advocacy leaders have landed on the same objective: make the program easier to use by meeting users where they're already working.
Today, that increasingly means Microsoft Copilot, ChatGPT, Claude, Gemini or whatever generative AI assistant employees happen to have open.
Imagine a salesperson simply asking AI, "Find me three German healthcare customers using product Y, willing to speak with a prospect," instead of navigating to another interface, or waiting for someone from advocacy, or elsewhere, to respond. It's easy to see the appeal. Removing friction has always been one of the fastest ways to increase adoption.
It is exactly the right instinct.
The difficult parts, arguably the reason program managers exist, occur before and after AI says, "Here are your three best matches."
The value advocacy professionals bring is the ability to operationalize and scale customer advocacy for maximum impact. Quality advocate information doesn't just appear, it's the result of a system.
Now that the user has three advocates, what should happen?
Notice what happened. The search was completed.
The next steps are just as manual as ever if AI search is the be all, end all.
Reality Check
AI can tell you who could participate. It can't tell you who should participate unless someone (or something) has been keeping score.
This is where the story starts to feel strangely familiar.
Many companies still operate their program using spreadsheets, scattered CRM fields, shared drives, email folders, and the remarkable memories of a handful of program managers.
Eventually, organizations realize they aren't managing an advocacy program at all. They're managing lists that happen to contain advocates.
But the shortcomings are real:
Purpose-built advocacy platforms emerged because advocacy is much more than a search problem.
Ironically, AI has convinced some organizations to revisit the same shortcut they worked so hard to escape.
Let's imagine two different worlds.
In the first, AI recommends an advocate for a sales call.
Months later, AI knows this customer recently participated and may deserve a break before being asked again.
Now imagine the second world.
Three months later someone asks how many customer reference contributed to the revenue this quarter.
Silence. Nobody really knows.
The advocacy happened...hopefully. The program didn't. Collectively, the organization slowly stopped feeding the very system it depended on to understand its advocacy program.
Reality Check
If AI helps facilitate twenty closed-won opportunities this quarter, but none are recorded, your executive dashboard still says zero.
One of the easiest mistakes to make in an AI-first world is assuming that successful interactions somehow become organizational knowledge on their own.
They don't.
If a customer agrees to speak with a prospect and nobody records it, the organization loses far more than a single activity.
The most valuable advocacy data isn't simply who your customers are.
It's everything they've done.
That's the story AI actually wants to read.
It's often said that AI needs good data.
That's true.
But operational history is far more valuable than static customer information.
Those aren't search results.Those are patterns.
Remove any one of those pieces and AI becomes little more than an exceptionally fast search engine.
Reality Check
Every workflow skipped today is a pattern AI won't discover tomorrow.
The AI revolution has created tremendous excitement, and rightly so. Finding the right advocate is becoming dramatically easier than it was only a few years ago.
That's worth celebrating.
Just don't confuse a better search experience with a better advocacy program. Search is only one chapter in the story.
The organizations that see the greatest return from AI won't necessarily be the ones with the most sophisticated models.
They'll be the ones with the richest operational history.
Those organizations won't use AI merely to answer the question, "Who should we ask?"
They'll use AI to answer far more valuable questions.
That's when AI stops behaving like a better Google search.
That's when it starts behaving like a strategic partner.
Finding the right advocate has always been the opening scene.
If your AI can find advocates but your program can't learn from using them, you've built a remarkable search engine instead of a remarkable advocacy program.
.svg){kind=icon}
