«Silent signals». Hidden customer churn

The customer placed 2–3 orders and disappeared. Dissatisfied with the price? Went to a competitor? Not interested? The user deleted the app or did not renew their subscription. Why? What's going on? Hidden churn is especially dangerous for small businesses because it often goes unnoticed until revenue starts to decline.

Customers don't complain, they leave. Only 1 in 26 report a problem, according to experts at Halla Systems Korea. The other 25 simply turn away silently. Without a fuss. Companies that monitor ‘silent’ signals reduce churn by 25-30%. The task for businesses is to learn to read the subtle signs of dissatisfaction and respond before it is too late.

Halla Systems Co. Ltd analyses customer behaviour on a daily basis for dozens of companies from around the world. Most often, churn begins long before the actual departure. It's just that businesses don't notice it in time. What should you pay attention to? What ‘silent signals’ can you track?

The customer has started visiting less frequently

This signal is most noticeable in subscription models and online services, where user behaviour can be tracked in near real time. A customer who previously visited the website or app regularly begins to appear less and less often. They skip newsletters, do not respond to push notifications, and stop following new products. Such changes may seem insignificant, but they are most often preceded by complete departure.

Decreased use of features

Customers start using the product less than before — another warning sign. For example, a customer who previously actively used different sections of the platform or regularly tested new features now limits themselves to basic actions. This means that they no longer find value in the features that were previously important to them. It's as if they are still with you, but their interest is waning. This is a sign that it's time to help the customer re-familiarise themselves with the product, simplify the interface, or review the benefits they are getting — perhaps they no longer seem important to them.

Cohort analysis

Do customers who arrived at the same time behave in the same way — active at first, then leaving? Sometimes churn is not a coincidence, but a pattern.

Customer cohort analysis, or cohort analysis, is a great way to identify weaknesses in the funnel. By grouping customers by the date of their first interaction, you can see how each cohort behaves. By analysing data (Naver Analytics, Kakao Analytics, Google Analytics 4), you can track traffic sources or geography and determine exactly when the outflow begins.

If, for example, customers who came through the same ad start to lose interest after three months, something is wrong. Perhaps you promised more than you delivered, or you didn't explain how to use the product well enough.

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Buying behaviour

In e-commerce and subscription models, you can see an outflow due to changing buying habits. Basket sizes are getting smaller, orders are being placed less frequently, and repeat purchases are being postponed indefinitely. All these signals indicate that the customer is either finding it unprofitable or uninteresting. Sometimes this is due to competition, sometimes to a deterioration in the user experience.

Time since last interaction

If a customer has not been active for a long time, this is not a ‘pause.’ Most likely, they are leaving. It is especially important to track such users in services where interaction with the platform is regular. The longer the gap between actions, the higher the risk that the customer has already said goodbye.

The loyalty programme is not working

If a customer has stopped using their accumulated points, participating in promotions, or activating coupons, this is a serious warning sign. Especially if they previously actively used these opportunities. A loyalty programme only works when there is an emotional connection with the brand. And when that connection is broken, behaviour shows it first, not words.

Loyalty index trends

In 2003, consultant and sales expert Fred Reichheld proposed evaluating customer experience separately. Since then, his NPS (Net Promoter Score) or strategy of sincere customer engagement has been one of the most popular tools for measuring loyalty. The NPS methodology allows you to evaluate your business not as a whole, but by segments: delivery, sales, service.

Regular NPS surveys and satisfaction metrics can also signal an outflow. Even if the responses are not critical, negative dynamics (even if only by 0.5–1 point) are a reason to investigate. They indicate that the attitude of the user, client, or customer is changing. Trends in ratings often precede actual churn and provide an opportunity to intervene in time.

Retention rate by segment

Not all customers leave for the same reason. Some leave because of the price, some because of the complexity of the interface, and some simply because they don't see the value. By segmenting your audience by type, age, interests, or interaction history, you can understand which groups are most prone to ‘silent’ churn and work with them in a targeted manner.

What to do?

Connect a web analytics service: Naver Analytics, Kakao Analytics, Google Analytics 4.
Set up tracking for key events: adding a product to the basket, placing an order, registration, subscription, order cancellation, visiting important pages.
Once a week or month, analyse reports on visits, conversions, and customer retention. Pay attention to groups that have started to behave differently.
Connect email marketing to analytics and monitor mailing activity — who has stopped opening emails, who is not clicking on links.
If you have a CRM, regularly analyse the time since the last contact and the history of customer orders.
Use the capabilities of automatic real-time behaviour monitoring — for example, through individual solutions from Halla Systems company. We help