We’re true believers in the change management model from Prosci. Successful customer marketing and advocacy programs (CMA) all have effective change management at the center of their operations. Often it is the program manager’s innate understanding of what’s required rather than an organization having people formerly trained in the discipline. The Prosci model includes Awareness, Desire, Knowledge, Ability and Reinforcement (ADKAR) components, and each one must be addressed to help people move from current to future state smoothly and completely.
This post is all about the Reinforcement component, the actions taken to ensure that change sticks in the long term. Since organizations naturally change, a change manager must be thoughtful, persistent and vigilant to behaviors sliding back to the “old way.” Champions in leadership come and go. CMA stakeholders in sales, marketing, customer success and elsewhere turnover. Each time the personnel change there is the possibility for regression, which can spread through an organization like a virus.
To build up an immunity to regression, the best course is to embed your CMA program into the company’s DNA. That means it becomes a part of existing and new processes, events, and systems with the end goal of becoming entrenched in the collective headspace of the organization. To continue with the biology metaphor, if this new CMA “organism” isn’t recognized by the “body” it has a high likelihood of being rejected, as opposed to a symbiotic relationship that is viewed as mutually beneficial and important to sustain.
Lots of hypotheticals so far. Let’s talk specifics.
This is your opportunity to establish the desired behaviors and prevent regressions starting with day one of new employees. The onboarding agenda should include a session on your program, how advocates can and should be used in various roles (e.g. lead gen), why they should be used, what services your program provides, and any systems that support the CMA function. By exposing new hires early on, you address the Awareness, Desire, Knowledge and Ability components of change-management. One of the most squishy areas to pin down is Desire. A discussion regarding the common reasons people resist changes that come with a CMA program is totally appropriate at this point. Many new hires will have come from organizations not yet enlightened about CMA, so the change in their case is from past experience to your enlightened organization. How do you know if the information conveyed stuck? Test them!
As a CMA leader, you want maximum visibility among your stakeholder teams such as events, PR, social, digital, and content; as well as sales and customer success or account management. Repetition is key. You don’t want to just show up once in a while, or only when you think you have something important to share. You want to become a fixture in meetings and establish a cadence of information sharing and solicitation. Trust in you and your program removes resistance to reliance on you. Getting to know you, how you think, and hearing examples of how you’ve supported campaigns, opportunities and events; this lays the foundation for trust. Being part of team meetings makes you a part of those teams, which is not only the perception, but the reality you want to create. You’re there to help them meet their goals, and therefore the organization’s goals.
If you use technology like Seismic, then you are familiar with playbooks. Playbooks provide guidance to employees creating and managing campaigns, managing various phases of opportunities, planning events, you name it. They contain repeatable steps that have produced successful results. Your program should be represented in the relevant playbooks. That’s another way to stay top-of-mind at the right junctures in a whole variety of processes. Not being in these playbooks sends the message that CMA is not sanctioned (and supported) by the organization. It’s not important.
Just like meetings, company communications provide an avenue for you to be visible. And just like meetings, your visibility should be consistent—ever present. So whether it’s a weekly report, newsletter, Slack, video or any other method that’s used to keep the “troops” informed, be there. Share your advocate expertise, program successes, and added resources or services.
If dashboards are a common way to share information with stakeholder teams, or the entire organization, be sure CMA is represented. It could be the number of opportunities influenced by advocates this month or quarter. It could be a view of your advocate pool for specific, high-demand segments. Leaderboards for campaigns you’re running always encourage participation. Choose whatever is of most interest to your stakeholders, something they’ll pay attention to, and which helps tell your CMA program story.
We’ve written a lot about this topic in previous posts, because it’s so important. If your program is built to support your CxOs’ growth goals it will automatically demonstrate its integration into the organization’s DNA. Back to the biology metaphor, the CMA program becomes an integrated, necessary function in a complex business organism, which would be harmed should it cease to exist.
Establishing a Customer Marketing and Advocacy program in your organization goes way beyond launch. You must maintain a mindset of achieving program integration with the organization. From onboarding new talent to ensuring visibility through meetings and communications and exuding alignment with CxO goals, each fortifies the CMA’s role and ultimately modifies the organizations DNA. This is how the CMA program becomes a vital component in achieving long-term success and builds resilience against regression. Remember, the real victory in change management lies not just in initiating change, but in making it stick. For more resources on building a strong customer reference program, check out our ebook, 7 Priorities for Building a Customer Reference Program.
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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