"I Never Saw
It Coming."

Picture a relationship. Six months in, the calls get shorter. Then the replies slow down. Then they start cancelling plans. You see all of it happening. But when it ends, somehow you still say, "I never saw this coming."

Businesses do this every single quarter. A customer's behaviour shifts. Their engagement drops. Their spend changes. The signals are loud. But nobody is watching. And when that customer walks out, cancels the subscription, switches the provider, churns. The boardroom acts surprised.

Today, using the IBM Telco Customer Churn dataset with 7,043 real telecom customers, I want to show you exactly what those signals look like. Because once you see them, you cannot unsee them.

First: how bad is the problem?

Of 7,043 telecom customers in this dataset, 1,869 churned ,that's a 26.5% churn rate. For every four customers this company has, it's losing one. And those 1,869 customers were paying an average of $74 a month. That's over $139,000 in monthly recurring revenue walking out the door. Every single month.

That's not a customer service problem. That's a pattern recognition problem.

The contract is the commitment.

In a relationship, month-to-month means no commitment. No strings attached. No reason to stay if something better comes along. The same is true in business.

Customers on month-to-month contracts churn at 42.7%. That's nearly one in two. Customers on a two-year contract? 2.8%. Not because two-year customers are more loyal by nature, it's because the structure creates a reason to stay long enough to actually build loyalty.

The first 90 days are everything.

Think about how relationships end. Most of them don't collapse after years, they fizzle in the first few months, before real investment has been made. You never quite settled in. You never fully committed. And so when friction arrives, leaving is easy.

Customers in their first three months churn at 56.8%. Over half. By the time a customer has been with you for five years, that rate is 6.6%. The pattern is clear: every month a customer stays, they become less likely to leave. But you have to survive the beginning.

How you pay says how you feel.

There's a version of this in relationships too. When someone stops showing up automatically, stops making plans without being asked, you notice. The effort disappears.

Customers paying by electronic check churn at 45.3%. But customers on automatic bank transfer or automatic credit card? 16.7% and 15.2% respectively. The payment method isn't just a billing preference. It's a signal of how embedded a customer is in your ecosystem.

Manual payment = low friction to cancel. Automatic payment = the customer has made a decision to stay on autopilot. That decision matters.

The more invested they are, the harder it is to leave.

A customer using one service can cancel in 30 seconds. A customer using seven services has to find alternatives for all seven before they can leave. Depth of relationship creates switching costs and switching costs create loyalty.

Customers using just one service churn at 21.7%. Customers using all seven services? 5.8%. The relationship between service depth and retention is almost linear. Every additional service is another reason to stay.

When the signs align, the exit is almost certain.

None of these signals exist in isolation. The real insight in churn analysis isn't individual risk factors, it's what happens when they stack. In this dataset, there's a specific combination that should set off every alarm in your retention team:

Month-to-month contract + Fiber optic internet + No online security.

These are 1,774 customers. Their churn rate is 58.1%. More than half of them are going to leave. And the business can probably see every one of them in their CRM right now.