Featured Guest: Kristin Sanderson
In this compelling episode of The CustomerX Files, host Alison Bukowski sits down with Kristin Sanderson, Global Customer Advocacy Manager and trusted Point of Reference partner, to explore one of the most powerful — yet often overlooked — drivers of business growth: customer relationships.
While many organizations invest heavily in tools, processes, and performance metrics, Kristin and Alison make a compelling case that true revenue acceleration starts with something far more human. This episode explores how strong, authentic customer relationships go beyond “feel-good” engagement and become a measurable, strategic asset that directly influences pipeline, retention, expansion, and long-term brand trust.
Throughout the discussion, Kristin shares her real-world experience building and scaling advocacy programs that align closely with revenue-generating teams like sales, marketing, and customer success. Together, she and Alison unpack why customer advocacy and relationship management are often misunderstood — and how reframing them as business drivers can elevate their impact across the organization.
One of the central themes of the episode is alignment. Kristin explains how advocacy teams can work more effectively with sales by understanding sales priorities, timing, and pressure points — and how this collaboration helps ensure customers are engaged in ways that feel authentic, respectful, and mutually beneficial. Rather than treating customer advocates as transactional assets, Kristin emphasizes the importance of long-term relationship stewardship that builds trust over time.
The conversation also tackles a challenge many customer marketers face: measurement. How do you quantify the value of relationships in a way that resonates with executive leadership? Kristin and Alison discuss moving beyond vanity metrics to connect customer engagement, advocacy participation, and relationship health to tangible business outcomes such as deal velocity, win rates, renewals, and expansion opportunities. Listeners will gain insight into how to tell a stronger story with data — one that reflects both the emotional and economic value of customer relationships.
Another key takeaway is the role of accountability. Kristin outlines practical frameworks for setting expectations internally, tracking impact, and ensuring advocacy and relationship-building efforts are tied to clear business goals. This includes defining success metrics, establishing feedback loops with internal teams, and continuously refining strategies based on what’s working — and what isn’t.
Whether you’re a customer marketing leader, advocacy practitioner, or part of a cross-functional revenue team, this episode offers practical insights you can apply immediately. It challenges conventional thinking, reinforces the strategic value of human connection, and provides a roadmap for turning relationships into a repeatable revenue engine.
Listen now to discover how prioritizing authentic customer relationships can transform not only how your teams work together — but how your business grows.
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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