Predictive analysis of “Churn rate” with the Big Data approach
In a hyper-competitive context in the telecoms market, retaining subscribers becomes a crucial issue for operators. In this context, LINCOLN (specialist subsidiary of the ALTEN group) has rolled out a Data Science service centre with a telecoms operator to develop a “Client Scoring” tool used to predict churn rate risks and implement customized marketing actions.
The French market of operators and internet service providers is one of the most competitive. Prices are among the lowest in the world, and an operator can lose several million subscribers within a few years.
To help our operator customer increase its subscriber loyalty, LINCOLN has mobilized more than 20 consultants (Data mining developers, Data Scientists, etc.) on the:
- Overhaul of the business intelligence information system
- Creation of a “Customer Knowledge” oriented Big Data platform
- Statistical modelling of the “Client Scoring” to predict the probability of loss of the subscriber
By analysing an extremely large amount of data in real time (consumption, billing, customer after-sales service, technical after-sales service, etc.), the tool can rapidly trigger targeted Marketing actions. This Big Data/Artificial intelligence approach has enabled our customer to reduce the number of contract terminations and optimize the cost of its marketing actions.