Marketing, as a whole, is more focused on measurement than ever before, and this is particular true for customer marketing and reference programs. CEOs are demanding that marketing be accountable for finding and cultivating prospective buyers, and technology is making attribution possible in ways that didn’t exist a decade ago.
Gartner’s CMO Spend Survey report found that “Analytics and insights continue their reign as the most strategically important capabilities, while Marketing Operations grows in strategic stature.” It’s all about the data.
So, what about customer marketing, which, more often than not, calls the marketing department home? Within our customer base, we see a wide range of commitment to measurement. When one of our customer contacts isn’t concerned about quantifying their program’s contributions relative to their organization’s growth, we worry. Their health status is automatically set to amber in the red/amber/green spectrum. Why? Because. customer reference programs that don’t quantify impact faulted and die.
Here are the most common reasons we hear related to why metrics aren’t being defined and monitored by customer marketing managers, and why that’s problematic.
“Leadership isn’t asking for any reports.”
A lack of interest in metrics generally indicates leadership doesn’t know how to measure the customer marketing program’s value, see its importance to achieving corporate goals, or it’s just not on their radar at the moment. It’s tempting to assume a customer reference program can fly under the radar forever. It can’t.
Experience tells us that when budget cuts are called for (pre-IPO, economy slowdowns), all programs come under scrutiny. There will be a swarm of report requests to help inform those decisions. If, as program manager, these reports are difficult or impossible to produce, your program is in jeopardy. The result: high contribution programs stay; low or unknown contribution programs go.
You probably know by now that a change in leadership can be a stressful time. When the customer reference program gets a new senior executive, either due to a transfer of the program to a different department or a change in the executive staff, there will be renewed scrutiny. To get a handle on your program, new executives will ask for data. Maybe the former executive was fine taking a leap of faith on the reason for your program’s existence. The new executive could be a “data head.” Uh-oh.
“I don’t have time.”
The trap here is believing that being extremely busy getting stuff done is enough proof of the customer reference program’s validity. Not so. If there’s no data to document the activities and results of your efforts, it’s as if they never happened. Sounds crazy, right? Who would cut a program so obviously busy? To executives, contributions aren’t legitimate unless they can be quantified, and there is a clear connection between program activity and corporate imperatives. Again, it is very, very difficult to piece together meaningful statistics from email, Slack, or Chatter correspondence over the past quarter or year. Not running regular reports and tying the results to company goals will sell yourself, and the customer reference program, short.
“I don’t know what’s really important to track or what to aim for.”
Think in terms of outcomes and corporate goal alignment. There are very few things that matter at the end of the day. Is your program helping to close business? Are the program membership and content library changing or growing to support company growth goals? Are the program’s assets helping to generate more demand (i.e., leads)?
“I’m not good at creating reports.”
Unless you’re lucky enough to have a business analyst-type resource at your disposal, you must consider this an essential skill set and develop it. Analysis is iterative. You start with a broad report. Then you’ll change the filter criteria, add data elements, remove data elements, group, and subtotal until you get the picture of the data you need. It is experimental and dynamic. You won’t want to have to wait on anyone else’s availability to get to report nirvana. If you use Salesforce, you’ll find a variety of Trailheads on the reporting topic, and they’re free!
“My program stats aren’t impressive, and I don’t want anyone to find out.”
This is not a sustainable position. Ultimately someone will ask for numbers. It’s a legitimate and reasonable request. If you’re tracking numeric goals early on, and they aren’t acceptable, then this is an opportunity to call in support. Customer reference programs are cross-departmental and interdependent by nature. If there is a failure in the ecosystem, all the parts need to be assessed and adjustments made. Here are a few examples of common issues and fixes:
You don’t want to be that marketer that can’t quantify their value. It’s a career-limiting attribute. Success begets success. When you have the numbers to show your program’s contributions, more resources follow. With more resources, the program grows and has an even greater impact. Want to read more on this topic? Here are some related posts:
Customer Reference Program Measurement
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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