Executive support. We all know it’s important. When I hear a client or prospect say, “I’ve got executive support,” I ask, “What’s that look like?” You may know where I’m going with this. There are different flavors of “support,” and they are not equal.
To be fair, I don’t think all program managers articulate what they need in terms of executive support. When you hear an executive say, “This is important to me. Let me know how I can help.” that’s a good start, but not in and of itself the definition of executive support. You cannot expect an executive to know what you need from them to make your program successful. This is on you.
You’ll need different things at different times. Let’s separate what’s required in terms of leadership involvement (1) leading up to and including program launch, and then (2) post-launch.
Specifically, what does executive support look like?
In short, it is explicit, not passive involvement. It is visible actions to back up words (which do matter). It is sustained rather than fleeting interest.
Channels
The medium may be written (email, Slack/Teams), video (internal communications videos), or spoken (team or all-hands meetings); whatever has proven to be the most effective channel(s).
Cadence
Communication is not a one-and-done task. You know the adage: “Tell ’em what you’re going to tell ’em; then tell ’em; then tell ’em what you told ’em.” That all applies here. Work with leaders on a recurring communications plan; build a communications calendar. The cadence could be weekly to start, then bi-weekly, and ultimately monthly. But it should never stop.
Content
It’s easier to edit than to create. Some executives completely get the value of customer advocates. Some understand it intellectually, but it isn’t yet emotionally internalized. The latter group could benefit from your guidance. Write some or all of the suggested pieces for them.
Pre-Launch
Build excitement, set expectations.
Post-Launch
Strategic Planning Inclusion
“Getting a seat at the table” is the ultimate goal for many customer marketing managers. That means being invited to key planning meetings that include directors, VPs and CxOs. These meetings give program managers critical visibility into upcoming advocate needs for email campaigns, webinars, earnings calls, digital marketing, etc. You can then suggest ways in which the program can help; ways which no one would have thought of without you being in the conversation.
Executives have the influence needed to get you that seat. Once they understand the advocate expertise you have and the “assets” the program has to offer, they’ll be able to identify advocate opportunities: “That’s a great idea! Did you talk to customer marketing to get their thoughts? They have some strong advocates in that segment you should leverage.” Customer marketing is still a relatively young function and often not considered the strategic discipline that it should be. Changing this perception may take persistence and change management effort on your part. But, the benefits to the organization are worth it!
Their participation ensures they understand what’s working and what’s not, which they can help solve. They can bring big picture perspective into the conversations. Likewise, the more they know about the program the more they can infuse executive conversations with insights into how customer advocates are being used across the enterprise, which will likely spark creative customer advocate applications.
I’ve laid out how we believe executive support should work. If the version of it at your company doesn’t include the elements described above, you don’t have it—yet. If you’re not sure how to get it, read our post: How to Capture and Keep CxO Engagement. In short, you must think like an executive and talk in terms of their areas of interest, their priorities, and connect the dots to your program. Do not assume they will connect those dots on their own.
Don’t be shy about asking for genuine support from your executives. The ask alone sets an expectation: Customer reference management is a team sport, and executives are on that team.
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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