You’ve rolled out ReferenceEdge, your shiny new customer advocacy platform. It’s packed with the features you dreamed of—dashboards, automations, time-saving tools galore. The promise? Scale your program, 10x your impact.
But here’s the catch: if no one uses it, it’s just a cool, digital trophy gathering dust on a shelf. Pretty? Sure. But that’s not what you or your leadership team signed up for. This is where an adoption plan comes in.
User adoption of a new technology is essentially how well and how quickly individuals begin to use and embrace a new system, tool, or process as part of their day-to-day work.
Adoption is the human side of change. Change doesn’t install like software. It’s a process. People need to opt in, shift habits, and sometimes let go of the old ways (even if the old ways were inefficient and held together by spreadsheets, duct tape, and hope). As your technology partner, we don’t just understand this—we plan for it. We’re not here to drop off a tool and walk away. We’re in it with you to help change how work gets done.
This isn’t a check-the-box support role. Your Point of Reference account director is in the trenches with you—week after week—invested in your success like it’s their own. Because in many ways, it is. When your program thrives, they do too. This is a real partnership, not a perfunctory pass-off.
And like any good partnership, it works best when the commitment is mutual.
Your account director will bring the guidance, playbooks, proactive red flags, and a full heart to the table. What they can’t do is secure your budget, get your execs to show up, or move mountains solo. They need you in the game—engaged, honest, responsive, and ready to keep the momentum going.
Account directors are there for you as you choreograph the success of your program: weekly syncs, making space for strategy, flagging what’s not working early. Your account director is your guide, strategist, and (yes) occasional tough-love truth-teller. They’ve danced with many partners; they know what works and doesn’t. When they raise a red flag, it’s not drama—it’s wisdom. And when they offer a new way forward, it’s grounded in experience, not guesswork.
They’ll help you craft training that sticks, messaging that engages, and incentives that actually drive change. They’ll help you translate program goals into the language your leadership understands. And yes—they’ll be the quiet voice reminding you to measure your wins before anyone else is even asking.
At the end of the day, this isn’t just about software. It’s about people. It’s about the process. And it’s about partnership.
Contact us today to get started.
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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