Data analytics allows us to understand the reasons why our clients are not loyal.
Knowing these reasons, we can take actions to retain them.
Churn prevention has became one of the biggest challenges for all companies, specially for banks, insurance and telecommunications companies. Indeed, it is much cheaper to retain existing clients than to acquire new ones.
However, it is not easy to detect the dissatisfaction of a client, and many times they just stop using our services without any previous warning. Some of the factors that influence churn are the following:
Therefore, it is essential to develop new methods that are useful to discover our dissatisfied clients.
Advanced analytics allows companies to manage large amounts of data and find early signs of desertion before it is too late.
Determine the probability of desertion identifying your dissatisfied clients.
Study the reasons of abandonment taking into account the characteristics of the clients.
Create solutions to recover their loyalty before it is too late.
Retain customers, increase sales among current clients and improve customers satisfaction.
The final objective of these techniques is to develop loyalty programs and retention campaigns to keep as many customers as possible in our company.
Neural Designer uses machine learning to build predictive models capable of assessing the risk of churn of clients.
It allows us to easily set the analyze the customer features that are more relevant for the churn and design the neural networks that best fits the case of study.