Many years ago a client, a top five strategic consulting firm, asked if we had any tools to help get her arms around the customer advocate program she recently inherited. It just seemed there were so many pieces and parts and some stakeholders yelled more than others, and that’s how the program evolved before she arrived on the scene. It didn’t seem to have a master plan.
In the consulting world, the standard “tool” for sizing up a situation is a maturity model. It provides a benchmark for companies seeking continuous improvement. We got to work on building a maturity model for customer advocate programs. By identifying 11 discrete parts of a program (or a collection of processes, if “program” is too generous), we found a way to simplify the assessment of each area and avoid getting overwhelmed. Analysis paralysis is so common in our field.
For each of these areas there needed to be a scale so that the current situation could be pegged to a stage of evolution. A user would need a way to identify each program facet with one stage or another, so we described four progressively more sophisticated stages in detail for all 11 elements.
The result is a self-assessment tool that helps all stakeholders understand what’s working and what’s not. It also provides a path to evolving to higher levels of performance and acts as a touchstone used monthly, quarterly and annually so that the big picture isn’t lost in the dust of the day-to-day.
What this tool does best is professionalize (shows method and discipline) the program, which is so important to executives being asked to bet on an unknown horse. Knowing there is a vision, and that the vision supports and aligns to the company’s growth goals―the most important of all― makes that bet a lot less risky, and in the hands of the right leader a sure thing. Read more about capturing and keeping C-Suite engagement.
The best thing about our maturity model is that it’s valuable for managers of existing programs, and to those tasked with putting a program in place. In both situations, it makes clear both the assets and liabilities of the current state and makes prioritizing next steps much easier.
When developing your plan, be sure to include both short and long-term goals. There will be many goals that will take time, and they’re worthy of accomplishing. However, short-term goals produce quick wins, and everyone likes to see progress.
In your quest to build a program that produces astounding results and has the highest visibility in your company, don’t forget to establish an advisory board for your program. This board is made up of the people who have the most to gain from your success (sales, marketing). Make this a team effort and see how much more engagement you garner and the results that come with it.
Click this link to download a PDF copy of our Maturity Model tool.
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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