Featured Guest: Antu Buck
On this episode of The CustomerX Files, Alison is joined by Antu Buck from Gigamon. Antu is an accomplished and award-winning marketing leader, currently serving as the Director of Customer Marketing and Community at Gigamon. She also has over a decade of experience at McAfee and continues to demonstrate success in steering customer marketing initiatives through a unique blend of creativity and analytical expertise.
As organizations face increasingly complex buyer landscapes, the role of customer advocates has broadened far beyond traditional reference calls or testimonials. In this episode, Antu and Alison explore how advocacy when approached strategically becomes a multi-dimensional growth lever that strengthens retention, accelerates pipeline velocity, influences buying decisions, and enhances brand credibility. By blending creativity with analytical insight, Antu explains why advocacy initiatives should be central to how companies think about customer experience and go-to-market success.
A central theme of the conversation is the shift from viewing advocacy as a one-off activity to treating it as a repeatable, strategic engine. Antu breaks down the importance of intentional planning including frameworks like creating 30-, 60-, and 90-day plans for customer advocacy work to ensure programs move past early enthusiasm and begin delivering structured, scalable results.
Through the discussion, listeners gain a clear understanding of how advocacy contributes to growth in multiple ways:
The conversation also tackles the practical challenges many teams face when building advocacy programs from balancing resource constraints to aligning cross-functional stakeholders around a shared vision. Antu shares real-world advice on overcoming these obstacles by focusing on clear goals, measurable outcomes, and meaningful customer engagement rather than chasing vanity metrics alone.
Listeners will walk away with a richer understanding of how customer advocacy can be designed to scale, measured for impact, and connected directly to growth metrics that matter to revenue leaders as well as customer marketers. Whether you’re building your first advocacy plan or evolving an existing program, this episode provides inspiration and actionable guidance to help you think bigger about the role advocacy plays in your organization.
Whether you’re a customer marketing leader, an advocacy practitioner, or part of a cross-functional go-to-market team, this episode delivers valuable perspectives on harnessing the full power of advocacy as a core component of your growth strategy.
Listen now to discover how a thoughtful, strategic advocacy program can become a true engine for business momentum.
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}
