Telecom Customer Churn Analysis.

The dataset was available in Excel and was loaded in PowerBi was cleaning using Power Query .DAX was used for calculation and PowerBi visuals to create a detailed report of the analysis. The following insights were generated.

1. Dataset consisted of 7043 rows out of which 1869 (26.54%) consisted of churn customer data.
2. There had been a total revenue loss of $3.68M(17.22%) due to customer churn.
3. Majority of churned customers were unmarried female who were on Month to Month subscription.
4. San Diego and Los Angeles observed to have the most number of churned customer.
5. It was noticed that a majority of customers were churned due to competitors better service and lack of proper customer service at the present telecom company.

Recommendations

1. Better market research should be conducted to know how the competitors are behaving and accordingly changes to be made in the existing system.
2. The customer service staff should be trained and told about the imp of efficient customer service.
3. Better marketing strategies should be implemented in the top 10 cities where there were max churn rate.
4. Special offers to be proposed to the customers on Month to Month subscription to reduce churn rate and convert their subscription to yearly.
5. Time to time surveys should be conducted to know about the customer experience.