In this project we have analyze the dataset of the telecom company. The company wanted to forecast the customer churn rate of the company.
Objective:
The objective was to analyze the telecom company's Churn dataset and find the customers who are at potential risk of loosing. Define proper KPIs. Create a dashboard for the retention manager reflecting the KPIs.
Tool I Use: 1- Microsoft Excel 2- Microsoft PowerBI
My Findings:
1- The churn is more likely to be 'YES' when internet service is fiber optic, it is around approximatly 43.93% of the total churn rate, it indicates that there may be some problem with fiber optic service and it needs to be address.
2- As tenure decreases the likelihood of Churn = 'YES', inceases. For example the fall of 24.56 in tenure leads to a 8.48x growth in churn likelihood. This insight i gain from Key Influencers in powerbi.