Customer advocacy has undergone a significant transformation over the past decade, evolving from an informal, relationship-driven activity into a strategic business function that directly impacts growth, credibility, and customer trust. In this video, Carlos Gonzales, a respected voice in customer marketing and advocacy, shares his perspective on how advocacy has changed, why it matters more than ever, and what organizations must do to build modern, scalable advocacy programs.
Historically, customer advocacy was often limited to reactive reference requests or ad hoc case studies managed by sales or marketing teams. While these efforts provided value, they were rarely measurable, repeatable, or sustainable. As buying behaviors changed—especially in B2B environments—so did the role of customer advocacy. Today’s buyers rely heavily on peer validation, real customer stories, and authentic proof points throughout the entire buyer’s journey. As Carlos explains, advocacy has become a critical trust signal that influences purchasing decisions long before a prospect ever speaks to sales.
Carlos highlights how successful advocacy programs now sit at the intersection of customer success, marketing, and sales. Rather than treating advocates as transactional assets, leading organizations focus on building long-term, mutually beneficial relationships with their customers. Advocacy is no longer about “asking for favors,” but about recognizing customer achievements, amplifying their voices, and creating opportunities for them to lead, share, and connect with their peers.
The video also explores the growing importance of the voice of the customer (VoC) in shaping advocacy strategies. Carlos emphasizes that modern advocacy programs must be rooted in genuine customer feedback, outcomes, and experiences. By aligning advocacy initiatives with real customer value and measurable outcomes, organizations can create content and engagement opportunities that resonate more deeply with prospects and internal teams alike.
Another key theme discussed is scalability. As advocacy programs mature, manual processes and spreadsheets quickly become limiting. Carlos touches on the need for structure, governance, and technology to support advocate recruitment, engagement, and measurement—while also preventing advocate burnout. Scalable advocacy enables organizations to deliver the right customer story at the right time, without overusing their most engaged customers.
Finally, Carlos looks ahead to the future of customer advocacy, where personalization, automation, and data-driven insights will play an even greater role. As customer expectations rise, advocacy programs must continue to evolve—becoming more strategic, more customer-centric, and more aligned with overall business objectives.
This video is a must-watch for:
Whether you’re building a new program or refining an existing one, this video offers practical insights to help you create a stronger, more impactful advocacy strategy.
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.
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