Proactive renewals and churn prevention

Preventing churn is the most effective way to build a relationship with your customers based on their loyalty and trust. Churn prevention and interaction with the customers is a crucial part of understanding their needs and avoiding complaints.

Business case

Companies all around the world are troubled by customer churn. Some of them fail to detect the potential dissatisfaction of the customers, which leads to the natural churn. At that point, a retention campaign might be the only option. However, that can be costly and not consistently efficient. Churn prevention and interaction with the customers are crucial in understanding their needs, avoiding complaints, and building a relationship based on their loyalty and trust. Modern AI/ML solutions can predict the potential churn in advance. The key information could be hidden in e-mails, phone calls, or decreasing activity.


Customer history contains all possible interactions, such as phone calls, chats, e-mails, or NPSs. Our solution, based on predictive modelling of potential churn, offers the opportunity to analyse churned customers’ behaviour by training ML algorithms. Implementing natural language processing methods helps extract the keywords and understand the communication sentiment, and categorise churning customers in order to find the solution to their problem or complaint. Some of these issues can be solved simply by automatically generated answers, some can be routed to the respective specialist. Others could be tagged as potential churn and prevented.


  • Sentiment analysis and critical topics or problems detection encourage positive attitude of the customers as their complaints can be resolved more efficiently, which helps to prevent customer churn.
  • Machine learning algorithms can categorise issues and choose the right solution, which saves time and helps keep customers satisfied with the response.

Need to Know More?

Ask us anything

Key contacts

Bob Hroch - DataSentics

Bob Hroch

Business Development

Václav Kautský - DataSentics

Václav Kautský

Data scientist