When a revenue engine is stuck, the first variable I ask for is frequency. Who is in the system the most. That one number tells me more than revenue ever will.
Frequency is close to a Boolean. Nobody returns to a product every day that they hate. Your highest-frequency accounts love it, even the ones who complain the loudest, and they are not going anywhere.
Find the handful of profiles that live in the product daily. Learn exactly what they love. Then go find everyone in your database who looks just like them but barely logs in. The gap between the two is your entire growth plan.
Whatever the business is, I know how to build revenue, and I know how to do it without guessing. There are only a couple of variables I need, and the first one is almost always the same. Especially in a service or a product where people come to you to get something done. Before I look at revenue, before I look at the pipeline, before I look at the logos, I want to know one thing. Who uses this the most. Who has the highest frequency of use with me. That is the first thing I care about, every time.
Most people expect me to start with the accounts that are leaving. The angry ones, the renewals that look shaky, the names the team is already worried about. I do the opposite. I start with the people who cannot put it down. Frequency is the cleanest signal a customer ever gives you, and almost nobody is reading it.
Frequency is a Boolean.
Here is why I trust it. Frequency is close to a yes or a no. If someone uses your product more than a few times a week, they love it. I have never met a person who opens something every single day and tells you it is useless. They will have complaints, plenty of them, the loudest complaints you will hear all year. But you do not spend your day inside a tool that is wasting your time. The high-frequency users have already voted, with the most honest currency they have, which is their attention.
That is also why frequency clears the noise so fast. The people who do not like your product quietly stop showing up. So when you sort by who is in the system the most, you are looking at a filtered list of the customers getting real value, and you did not have to run a single survey to find them.
The research backs this from a useful angle. Sean Ellis, who ran early growth at Dropbox and Eventbrite, built the most-used product-market-fit test there is. You ask users one question. How would you feel if you could no longer use this. The companies that grow almost always have more than 40 percent answer "very disappointed." The detail people skip is who he tells you to ask. Only the users who recently experienced the product, the ones who used it at least twice in the last two weeks. Frequency is not a footnote in that test, frequency decides who even counts.
Find the six profiles, not the six logos.
When you really look at the daily users, a pattern shows up almost every time. It is not one giant account. It is a handful of profiles, often around six, certain kinds of companies that all behave the same way. A type of dealer. A type of operator. A role inside a certain size of business. And here is the part that catches people off guard. They are usually not paying you any more than anybody else. Same plan, same spend. They are just using it far more. The frequency is way higher than the rest of the book, and the revenue line does not show it.
So that is where the work goes. Not into the accounts that never log in. I do not start by calling the people who already left the product on the shelf, because the fastest way to lose a quiet customer is to remind them they are paying for something they do not use. The high-frequency profiles are bulletproof. They are not leaving. So I go deep on those six. Who are they exactly, and what is it they love. Not what we assume they love. What they actually do in the product, day after day, that keeps pulling them back.
The gap between two lookalikes is your growth plan.
Now it gets interesting. Once I know the six profiles cold, I take them back to the database and find everyone else who is technically the same profile but barely touches the product. Same kind of company. Same role. Same use case on paper. Completely different behavior. Then I measure the difference. What does the power-user version of this profile do that the dormant version never started doing. Where are the deltas.
That gap is the whole thing. It is the distance between a customer who built you into their day and an identical customer who never got there. Map it, and you have a knowledge base, the specific moves that convert a lukewarm lookalike into a power user. You are not inventing a playbook. You are copying the one your best customers already wrote with their behavior.
There is real science under this. Eric von Hippel at MIT spent decades studying who actually drives innovation, and he named the group lead users. People who hit a need before the rest of the market does, and who are already solving it for themselves. When von Hippel and his colleagues tested the idea inside 3M, projects built around lead users were forecast to generate roughly eight times the sales of projects run the traditional way, about 146 million dollars each over five years, reported in Management Science. Your power users are your lead users. They are not the edge case. They are the early picture of where the whole segment is going.
Cross one vertical at a time. That is the chasm.
Now I know how to convert. I know what a power user does, and I know what turns a lookalike into one. The next question is which market to go after first, and the answer is one at a time. This is Geoffrey Moore's Crossing the Chasm, and it is still the right map. You do not spray the whole market. You pick one vertical, the head pin, and you knock it down completely before you touch the next one.
So I take the strongest of the six profiles and I crank on it like a vertical. Test the waters, get a few wins rolling, then build the manual. The literal how-to for being wildly successful in that one exact shape. If it is a dealer in Texas running a specific play, you build the playbook for that dealer, in that play, because you already know how the power users in that profile behave. You are not writing it from theory. You are writing down what already works. Then you take the win, the references and the manual and the proof, and you use it to knock down the next pin, the adjacent profile that looks just like the first.
Your angriest customer and your most-frequent customer are both talking. Most teams only listen to the first one. The second one is the one building your next three years. Chris Schafer
Six profiles is more market than you can eat in three years.
Here is where it pays off. Once you have the six profiles understood, the conversion deltas mapped, and one vertical proven, the rest builds off the same foundation. Go-to-market comes out of it. Total addressable market comes out of it, because you finally know exactly who your best-fit customer is and how many of them exist. You are not guessing at a market anymore. Your power users defined it for you.
From those six profiles you will usually find more addressable market than you can work through in the next three years. That is the whole point. You stopped trying to manufacture demand from people who never wanted it, and you started compounding the demand that was already sitting in your own data, telling you the truth the entire time.
The growth you are looking for is probably already in your customer base, hiding in plain sight as frequency. Find the handful of accounts that cannot put your product down, learn what they love, and go build more of them.
Why most teams walk past this.
The reason this gets missed is not intelligence. It is where attention goes. Teams manage by the loudest complaint and the biggest logo, because those are the things that shout. Frequency does not shout. It is a quiet line in the usage data that says someone built your product into their day. You have to go looking for it, and then you have to believe it over the noise.
This is also where the human skill comes in, the part I build with every team I work with. Confirmation, one of the three Cs at the center of the Conversation Intelligence work, means you do not assume what your power users love. You go and confirm it, from their behavior and from their words, before you bet a go-to-market on it. The data points you at the right customers. The discipline is making sure you actually understood them before you scale the bet.
Where this gets built.
Finding the power users is the diagnosis. Building the engine that converts the lookalikes and crosses the verticals one at a time is the work, and it is the work I do. I come in, find the frequency signal the team has been walking past, and turn it into a go-to-market the team can run without me. That last part matters. I fix it fast, but the real product is teaching your team to run it themselves so they do not need me next time. It starts with a free call, where you tell me where the number is stuck and I tell you what I would look at first. The build itself is the revenue leader mentorship.
One thing to go check.
Before you do anything else, pull the list of your highest-frequency users. Not your biggest accounts. Your most-frequent ones. Then ask whether you actually know, in detail, what those people love about you. If the honest answer is not really, that is the most valuable gap in your business, and it is sitting in data you already own.
Power users and revenue. The actual mechanics.
What is the first thing to look at when revenue is stuck?
Frequency. Before revenue, pipeline, or logos, I want to know who uses the product the most. Frequency is close to a Boolean. People do not return every day to something that wastes their time, so your highest-frequency users are the ones getting real value, and they are the cheapest place to find your next growth.
Why frequency instead of revenue or spend?
Because revenue can hide the truth. Your power users often pay the same as everyone else but use the product several times more. The spend looks ordinary while the love is off the charts. Frequency surfaces that gap, and that gap is where a repeatable go-to-market comes from.
How do power users turn into a go-to-market plan?
Find the handful of profiles that use the product daily, usually around six. Learn exactly what they love. Then find everyone in your database who fits the same profile but barely logs in, and measure the difference. That delta is your conversion playbook. Then you cross one vertical at a time, building the manual for each before moving to the next.
Should you focus on customers who are about to churn?
Not first. Calling the accounts that already shelved the product usually just reminds them to cancel. Start where the love already is. Your high-frequency users are bulletproof, and they show you exactly what to scale. You win retention by manufacturing more power users, not by chasing the ones who never engaged.
How does this connect to leadership and the Three Cs?
Through Confirmation. The data tells you who your power users are. Confirmation is the discipline of actually understanding what they love before you bet a go-to-market on it. The three Cs, curiosity, communication, and confirmation, are how a team reads its customers accurately instead of guessing.
Last updated · June 2026