Decrease churn rate
Situation
In the publishing industry, customer churn is a significant challenge, often driven by a complex interplay of factors. Historical factors, such as content quality, user experience, technological limitations, customer service issues, and offer design, can all contribute to subscriber dissatisfaction. For example, a magazine subscriber might cancel due to a perceived lack of engaging content, delivery issues, or a poor user experience on the digital platform. Identifying the root causes of churn can be complex, as it requires a deep understanding of individual customer behavior and preferences.
Complication
The reasons for termination can be varied. Especially when it comes to ritualized products, there are often several factors that have grown historically. This includes content, usability, technology, customer service and offer design. In the case of a magazine, not only can the content result in cancellation, but also delivery.
In principle, it is easier to make existing customers happier than to win back those who have already turned away from the company as customers. That is why it is important to start early in the customer life cycle when optimizing the churn rate.
Solution
The advantage of users who leave the company as customers is that they enable companies to learn.
This can be based on subjective and objective data. Subjective data describes what the terminators tell the company when they emigrate. The objective data is based on the observation of how the user as a customer has behaved with the product. This data must be brought together and can be very individual.
An example from publishing is when a customer emigrates because they have received too little recipe content from the company. Here you look at which category this user has moved to find out how much “too little” means in this statement.
It is easier than asking these things to measure them and combine them with the subjective feedback from the user.
The benefits of a solution from The Data Institute
At the FUNKE Media Group, The Data Institute has implemented this case in the form of a customer data platform, which automatically questions cancelers and measures behavior in order to obtain information about their motivations.
The feedback from cancelers consists of partly unstructured information, e.g. reviews, but also continuous text.
Use AI-powered models
Our solution analyses feedback using AI text tools and channels it directly to the right place in the company so that appropriate measures can be initiated.
This results in a reduced churn rate and happier existing customers — and sometimes even to winning back cancelers and then doing better.
Questions about the project?
Catherin Hiller, who implemented it on an interdisciplinary basis at FUNKE, was responsible for this project.
The contact to our client can be organized on request.
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