Domain: Telecom
Service Area: AI & ML
Context
Segmentation of the customers and churn out management is essential in Telecom industry due to high competitiveness. Hence, focusing on customer’s needs and predicting and resolving pain areas is required to be done in a timely manner.
Solution
To solve this problem, our team has selected RFM (Recency, Frequency, Monetary) model, This model helps in understanding customer’s prior behavioural actions and applied for organization.
- Recency refers to the time interval in the last interaction from the customer’s end and the purpose of that interaction, if it’s a complaint or a new requirement.
- Frequency refers to how much a customer had to chase during that interaction and what was the final outcome or his satisfaction rate.
- Monetary, focuses on the Billing patterns and purchasing other services from the company.
Outcomes
We started solving this problem by categorizing the customer’s with similar kind of patterns and behaviours and then with the above mentioned model, we generate a list of potential customers which may drop their services to the relevant Telecom operator. As key outcomes:
- Telecom Operator started to plan and target their customers with campaigns specific to that category with positive results on key campaigns KPIs
- Direct impact on customer satisfaction on the operator support service