When the problem isn't churn, it's utilization

🔄 When the problem isn’t churn, it’s utilization
How a behavioral analysis changed the diagnosis of a B2B platform

1. The request: “We have a churn problem”

A B2B company approached my consultancy believing they were losing many clients. The message was direct:

“Customers are canceling because they can’t sell.”

It was a platform that connected suppliers of large automotive parts (engines, transmissions, etc.) with corporate buyers — a B2B-to-B2B marketplace. But when I asked:

“What is your churn rate?”
no one could answer.

They had perceptions, not data. And that was the first lesson.

🧩 Lesson 1 — You can’t fix a problem you’re not measuring

Before thinking about retention actions, you need to define what churn is and have visibility into it. Many companies confuse:

• Leads who never activated → with customers who canceled;
• Periods of inactivity → with real loss of revenue.

So the first step was to go back to basics: measure.

2. Back to basics: understanding the size of the problem

We created a simple but powerful spreadsheet with four columns:

• How many customers were acquired per month;
• How many became paying;
• How many canceled and why;
• And what the real cancellation rate was.

The exercise revealed two things: much of the “cancellations” were just leads who never activated. The real churn — of paying customers — hovered around 2 %, with occasional spikes.

In other words, the problem wasn’t as big as it seemed. But it still existed — and needed deeper diagnosis.

💡 Lesson 2 — Without defining what churn is, you create ghosts

Many teams spend their time “putting out fires” over metrics that were never clearly defined. Clarity about what is truly a cancellation completely changes the focus of strategy.

3. Discovering what’s behind churn

We decided to investigate churn holistically, combining two fronts:

• Qualitative analysis — categorizing the reasons for cancellation given by customers.
• Behavioral analysis — mapping how customers used (or failed to use) the platform before leaving.

That’s when the story changed.

4. The big discovery: churn wasn’t about lack of use

The data showed that customers did use the platform — but inefficiently. They received an average of more than 2,300 quotes per month, but made offers on less than 10 % of them.

In other words, the problem wasn’t lack of opportunity. It was the lack of utilization of the opportunities that already existed. Even so, customers said:

“The platform doesn’t help me sell.”

And in a way they were right — not because there were no opportunities, but because the effort to take advantage of them was too high.

⚙️ Lesson 3 — Churn rarely starts at the end of the journey

Cancellation is the symptom. The problem usually begins earlier — when the customer stops perceiving value. That’s why looking only at “why they left” is superficial; you need to observe when they started to disconnect.

5. Going beyond reasons: analyzing behavior

When we cross‑referenced the data, we noticed a pattern:

• 17 % of clients had never made a single offer;
• The average conversion rate of those who did make offers was 22 %;
• And the main barrier was the manual work and the excessive volume of quotations.

In other words: those who used the platform made sales — but few used it correctly.

🧐 Lesson 4 — The problem isn’t “low usage”, it’s “inefficient usage”

In B2B products, a client can be active but still not extract value. That’s why looking only at logins or screens can be misleading. What matters is whether the user’s behavior generates economic results.

6. The impact on perceived value

The analysis showed two distinct dynamics:

• Voluntary cancellations: clients who gave up early (within up to four months) because they didn’t see quick results.
• Cancellations due to delinquency: clients who used the platform but stopped paying because they didn’t perceive enough return.

In both cases, the issue was the same: lack of perceived ROI. When the client doesn’t understand how the tool is helping generate results, it becomes a cost — and costs get cut.

💭 Lesson 5 — People don’t cancel products. They cancel unfulfilled promises

If the client doesn’t see results quickly, they won’t wait for a “learning curve.” Showing perceived value from the first days is the strongest antidote against churn.

7. Turning discoveries into strategy

Based on the data and interviews, we created three practical lines of action:

1. Increase utilization of opportunities — introduce smart filters and automatic reminders to prioritize the most relevant quotations.
2. Reduce response effort — design simple automations and even AI‑based price suggestions to help suppliers respond faster.
3. Reinforce perceived value — show within the dashboard how much the client has already earned through the platform: quotes received, offers made and sales closed.

🧭 Lesson 6 — The best retention action is to make the client successful

Instead of creating “reactivation campaigns”, the focus needs to be on continuous activation. A client who understands how to extract value doesn’t need to be “retained.” They stay because it makes sense to stay.

8. The final learning

In the end, the diagnosis was counterintuitive: the problem wasn’t churn, it was utilization. Clients were faced with thousands of opportunities but lacked the time, clarity or structure to convert them. The result was predictable: low results → low perception of value → cancellation.

💡 Lesson 7 — Not every churn is a sign of loss; sometimes it’s a symptom of a misunderstood product

The real work of reducing churn isn’t to stop the client from leaving, but to ensure they see return before thinking of leaving.

9. The case summary

This project showed how data and behavior tell different stories. While the raw numbers showed “few cancellations”, the behavior revealed low engagement with the activities that generated value.

By putting both sides on the table, we realized that:

• Retention starts with correct usage;
• Client success depends not only on the offer, but on how they interpret the return;
• And that churn, when properly investigated, is not an end — it’s a diagnosis.