Do your customer references generate demand? One of the many stakeholders of a comprehensive customer reference program is demand generation. The Demand Gen team focuses on the very, very top of the sales funnel, where enticing email campaigns, webinars, and digital marketing are the name of the game.
B2B buyers are bombarded daily with demand gen communications and content. There’s a lot of noise out there, with each company attempting to differentiate itself from the competition. If you’re a customer reference professional, you’d probably be surprised by what a small percentage of messaging includes real customer stories. Yet, it’s common knowledge that customer stories are more emotionally compelling and relatable than vendor-generated solution claims and analyst opinions.
So, why is that? Probably because, like the other reference customer “consumer” in your company, it is difficult finding reference customers who have the desired story. Locating the perfect fit is just as hard for the events and campaign managers as it is for Sales if customer reference information isn’t centralized, clean, accurate, and searchable.
The key to infusing demand gen activities with captivating customer insights is the same as every other possible reference use case — have a formalized and professional customer reference process.
By building a customer reference resource, you remove obstacles and enable the demand gen folks to effortlessly inject communications and messaging with customer stories, which are more emotionally compelling and relatable than vendor-generated solution claims and analyst papers. There is no better source for the experience of “living with” a solution than a peer in an equivalent business setting (industry, size, geo, etc.).
Peer perspective, including customer reviews (short-form customer stories really) submitted to B2B customer review sites such as TrustRadius, G2, Capterra, etc., gives buyers more confidence in your solution and in their own decision methodology. Buyers love performance stats (ROI, increased X by #, decreased X by #, boosted compliance by X, etc.) when evaluating a solution. But those numbers alone lack context. Numbers started in the real world: measurements from real-world actions, real people, and real things that changed. To make those numbers meaningful. enough to generate demand, they must correlate to real-world implications, and stories are excellent for that purpose. Conversely, the numbers give the story credence.
Rather than talk about your company’s best attributes in demand gen efforts, give customers the “microphone” and the spotlight. Each customer has not just one story but lots of story components to share. Those stories generate demand by delivering an authentic voice. They can:
Customer insights can be effectively incorporated at all stages of the customer journey (including retention), but at the top of the funnel, there are plenty of opportunities, including:
The take-away is that a well-run customer reference program can provide extremely valuable resources to power your company’s demand gen efforts. If customer stories are not used generously now, it’s time to provide a better way for advocates to be found, and/or educate co-workers engaged in activities that prime the pump. Sit down with your demand get team to understand what customer stories they’ll need in the coming months based on their targets. Then you need to determine whether or not the customer reference program can supply those required customer stories, and from the necessary persona perspectives (IT, executive, power users, etc.). The demand gen team will appreciate the help, and Sales will appreciate compressed sales cycles and high win rates due to your efforts at the front end of the customer journey. Contact us today to see how we can help.
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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