USE CASES
Telecom Customer Churn Prediction
Customer churn is rampant in the telecom industry largely due to the ease with which customers can switch allegiance. Telecom companies are aggressively soliciting new customers and desperately trying to retain their current ones. The ability to make even a small improvement in retaining or acquiring new customers results in a staggeringly large revenue improvement – an aspect that all telecom companies are aware of.
The ability to predict which customers are likely to flee, or, for that matter, what profile of prospects are likely to join plays a significant role in determining the health of the organization.
USE CASES
Telecom Customer Churn Prediction
Customer churn is rampant in the telecom industry largely due to the ease with which customers can switch allegiance. Telecom companies are aggressively soliciting new customers and desperately trying to retain their current ones. The ability to make even a small improvement in retaining or acquiring new customers results in a staggeringly large revenue improvement – an aspect that all telecom companies are aware of.
The ability to predict which customers are likely to flee, or, for that matter, what profile of prospects are likely to join plays a significant role in determining the health of the organization.
Reduce Customer Churn results in huge benefits
- Minimize loss of revenue
- Maximize ability to cross and upsell products
- Avoid high acquisition cost of new customers
- High customer satisfaction levels
Reduce Customer Churn results in huge benefits
- Minimize loss of revenue
- Maximize ability to cross and upsell products
- High customer satisfaction levels
- Avoid high acquisition cost of new customers
Approach
NEMESIS provides actionable insights through easy, but powerful, data modeling, customizable dashboards, and the ability to take immediate action with its case management module.
With NEMESIS, you can:
- Access and analyze your data with a simple click, identifying the factors that most affect customer churn.
- Predict churn with a rich library of predictive models that can be activated in a drag-and-drop environment so as to allow those without technical knowledge to use them most effectively. The models include but are not limited to Naïve Bayes, Random Forest, Logistic regression, and SVM.
- Customize dashboards to address the needs of different levels of management, directly pinpoints the problem areas, and estimated the impact of various strategies.
- Take corrective action through an integrated case management system, assigning tasks to specific groups to improve the level of satisfaction within the customer base.
Analysis & Results
Consider customer churn as one of the company’s top issues
28% of customers have left this telecom company, resulting in a relatively high customer churn situation. As the telecom industry reached a saturation point and people have multiple internet call alternatives to choose from, retaining customers is of paramount importance for the company.
Better customer service, more customer engagement
Ineffective customer care service could be one of the major reasons that lead to high customer attrition. In this case, higher average customer care calls related to customer retention were observed. Accordingly, to reduce customer attrition, making more follow-up calls by the customer service team and training staff accordingly as user-end customer supports in order to offer quality service were recommended.
Maximize the value of each customer through segmentation
After segmenting the customers, a group of customers with a certain range of customer equipment days was found that composed the most critical group of the churn situation, as customers in this group are more likely to cancel the subscription than others are. Promotions and marketing strategies like providing free or cheaper equipment, longer quality maintenance service for customers could be effective to keep existing customers.
There’s a one-year seasonality in customer attrition. An extreme increase in customer attrition was found within 11-12 months in service. It’s highly possible that this result is related to the specific one-year prepaid plan. To keep those customers, the company could offer additional and extended special offers for customers to renew the plan.
Consider customer churn as one of the company’s top issues
There are 28% of customers who have left this telecom company, resulting in a relatively high customer churn situation. As the telecom industry reached a saturation point and people have multiple internet call substitutes to choose from, retaining customers is of paramount importance for the company.
Better customer service, more customer engagement
Ineffective customer care service could be one of the major reasons that lead to high customer attrition. In this case, higher average customer care calls related to customer retention were observed. Accordingly, to reduce customer attrition, making more follow up calls by the customer service team and training staff accordingly as user-end customer supports in order to offer quality service were recommended.
Maximize the value of each customer through segmentation
After segmenting the customers, a group of customers with a certain range of customer equipment days was found that composed the most critical group of the churn situation, as customers in this group are more likely to cancel the subscription than others are. Promotions and marketing strategies like providing free or cheaper equipment, longer quality maintenance service for customers could be effective to keep existing customers.
There’s a one-year seasonality in customer attrition. An extreme increase in customer attrition was found within 11-12 months in service. It’s highly possible that this result is related to the specific one-year prepaid plan. To keep those customers, the company could offer additional and extended special offers for customers to renew the plan.
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