If you’re in the customer advocate practitioner community you already know why developing and curating customer-centric content is a must-have component of your customer advocate program. When it comes to making decisions about technology, B2B buyers value peer opinions above all other vendor-produced content.
Setting a quota of X case studies or videos in a vacuum is not a viable program goal. Aligning your content development plan to your company’s primary growth goals, your north star, is paramount. This eBook covers the process of goal alignment. Once you’ve got that locked in, take these things into account.
What’s surprising, given all this data on the value of customer content, is that many companies aren’t optimizing their use of customer stories beyond the marketing qualified lead generation stage. According to the Content Marketing Institute’s 2019 B2B Trends survey, employing well developed customer-centric content throughout the sales cycle is still relatively rare. Certainly, customer stories are great tools for lead generation, but once prospects do connect with sales, it is even more critical to deliver the most meaningful content to propel prospects through the rest of the journey.
The sales journey isn’t straight or consistent from prospect to prospect. Different questions and concerns will surface at different times. Still, you need to provide a variety of customer-derived content to meet prospects’ needs. When prospects are just testing the waters, short, catchy sound bites or video testimonials can be just the thing to grab attention and open the door. Later on, a robust ROI case study may be the tipping point leading to a final reference call or site visit. A Gartner study found, “95% of buyers buy from someone who gave them content at each stage of the buying process.”
How do you ensure you’re spending your content production time wisely? By consulting with your stakeholders to pinpoint exactly what they need, and when. Here are the most common stakeholders that should be included in your discovery process because they rely on your program’s “assets.”
Here are the questions that you should ask when meeting with your peer groups:
This last question comes from a context of ranking all content on a spectrum relative to the content’s level of candor and granularity. More granularity assumes the buyer is ready to commit more attention and effort to understanding your solution. Think ROI case studies or analyst reports.
The clear takeaway is that if you make your content easy to find and designed to meet the needs of Marketing and Sales, you’ll be ahead of many of your competitors. Gartner found that “Less than 40% of marketers engaged in content marketing have a defined and documented strategy.” Without that strategy, how can a Sales or Marketing organization deliver precisely what your prospects want—relevant, trustworthy content that speaks directly to their requirements and increasing confidence in their decision.
Producing the content is just the beginning of the process. Here’s how you maximize your investment:
To find out more ways of making your customer reference program indispensable, download our free eBook or read our customers' success stories.
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.
.svg){kind=icon}
