Importance of Business Analytics in Telecom industry
Introduction
In the current Indian telecommunication scenario where several new operators are about to claim their share in the highly penetrated mobile market, the telcos are experiencing increasing heat of competition.
And with the implementation of Mobile Number Portability (MNP – by which customers are empowered to change their mobile operators, keeping their mobile number intact) by the year end, the customer churn propensity will increase considerably. Another major challenge for the telcos is to increase the ARPU (Average Revenue Per User) i.e to encourage the customers to spend more. To retain the customers and to enhance their usage, the telcos need to identify and satisfy the unique needs of individual customers. To achieve this, telcos need to know their customers in a more profound manner. Herein lays the importance of the business analytics in the modern telecom industry.
The business analytics helps the telecom service providers to know more about their customer’s preferences, their behavior, their calling pattern and can predict their future actions. In the modern telecom industry, the business analytics can be widely used for the following activities:
Churn management
Customer acquisition and retention is a significant challenge in all industries. In the Telecom industry it affects profitability of the company if a customer churns before the company can earn back the investment it incurred in acquiring the customer. Therefore, it is very critical to indentify the profitable customers and retain them.
By the usage of business analytics and data mining, the telecom operator can build a predictive modeling on the basis of customers’ past behavior and a score is assigned to the individual customers. This score indicates the probability of the customer to leave the services of the operator. Moreover, by identifying the major contributing factors to the generated churn score, the reasons for his/her probable churn can be detected. By addressing those issues successfully, the customer can be made more loyal to the company and can be eventually prevented from churning.
Customer segmentationWith the help of business analytics, the telecom service providers can segment their customer base on the basis of various conditions.
For example: The customer whose monthly usage is above the company’s ARPU (Average revenue per user) can be classified as high revenue earning customer. Specific campaigns can be designed and executed to satisfy this group of customers which will be entirely different from the campaigns to be executed for low usage customers.
The customers having high STD call usage (National Long distance calls) can be targeted with specific STD tariff packs.
In a country like India with various ethnic groups, each having very unique characteristics and behavioral pattern, the usage and needs are significantly different. By analyzing their usage pattern, they can be classified into various ethnic groups.
Therefore, by business analytics and data mining, the operators can identify various segments of customers. With further analysis of the data extracted, the operators can identify and address the specific needs and demands of these customer segments.
Campaign management
The business analytics solutions can provide an integrated platform for campaign design and execution. Based on the customer segmentation, churn score, usage pattern, recharge history; campaigns can be designed for retention, revenue enhancement (increasing customer wallet share) and cross-sell and up sell.
For example: A retention campaign can be designed for the customers who have high usage (monthly usage more than ARPU) and have high churn score. These are valued customers and the company will not like to lose them out.
The campaign’s effectiveness can be measured by capturing the response of the targeted base.
Cross sell and up sellEstablishing a Business analytics platform within the telcos provides an enterprise wise view of the customer. It provides data regarding the customer’s preferences and his/her behavior with reference to all kinds of services provided by the telco.
Analyzing the data extracted regarding the customer usage, their balance availability and their subscription pattern, the telecom service providers can build up data models to identify the product bundling and hence can detect the opportunities for cross sell and up sell.
For example: By analyzing the historic data (say for 6 months) and building a data model, it is found that customers who have high wireless voice usage, also have high sms usage, then a product bundling of voice and sms pack can be targeted for this group of customers.
If a group of customer always upgrades to thelatest equipment and subscribes to the newly launched services, this group of customers can be targeted with a product bundle of latest available equipment and newly launched services (eg: 3G services with handset)
Profitability analysisWith the help of the available data, the telcos can monitor the performance of the individual portfolios. They can measure the return on investments for individual product/services offered, price plans. Based on the performance analysis, the service providers can decide on which plan/products/services to go ahead with in future. They can perform a profitability analysis on the new products.
Credit risk managementBusiness analytics provides views regarding credit payment risk. It can rate the customers based on their historical behavior and credit dues. Therefore, the services need not have to be disconnected for those customers having low credit risk scores, whereas the customers with high credit risk score need to be dealt with lesser tolerance and can be decided for a termination or shifted to pre-paid scheme depending on further data analysis about those customers.
Conclusion
From the above discussion it can be inferred that business analytics can provide the telcos with the required knowledge about their customers, which can be utilized to identify the intricate needs of the customers and help the telcos to serve them better, therefore to achieve an increase in revenue from individual customers and enhance the profitability of the business.
For Enquiries, please contact: arin_mukh@yahoo.com
Link: SAS company details: http://www.sas.com/
Link: Arindam's Profile: http://in.linkedin.com/in/arinmukh
Link: EZine Articles (USA) Publications: http://ezinearticles.com/?SAS---Business-Intelligence---Churn-and-Campaign-Management-Solution-For-Telecom-Industry&id=2598262
In the current Indian telecommunication scenario where several new operators are about to claim their share in the highly penetrated mobile market, the telcos are experiencing increasing heat of competition.
And with the implementation of Mobile Number Portability (MNP – by which customers are empowered to change their mobile operators, keeping their mobile number intact) by the year end, the customer churn propensity will increase considerably. Another major challenge for the telcos is to increase the ARPU (Average Revenue Per User) i.e to encourage the customers to spend more. To retain the customers and to enhance their usage, the telcos need to identify and satisfy the unique needs of individual customers. To achieve this, telcos need to know their customers in a more profound manner. Herein lays the importance of the business analytics in the modern telecom industry.
The business analytics helps the telecom service providers to know more about their customer’s preferences, their behavior, their calling pattern and can predict their future actions. In the modern telecom industry, the business analytics can be widely used for the following activities:
Churn management
Customer acquisition and retention is a significant challenge in all industries. In the Telecom industry it affects profitability of the company if a customer churns before the company can earn back the investment it incurred in acquiring the customer. Therefore, it is very critical to indentify the profitable customers and retain them.
By the usage of business analytics and data mining, the telecom operator can build a predictive modeling on the basis of customers’ past behavior and a score is assigned to the individual customers. This score indicates the probability of the customer to leave the services of the operator. Moreover, by identifying the major contributing factors to the generated churn score, the reasons for his/her probable churn can be detected. By addressing those issues successfully, the customer can be made more loyal to the company and can be eventually prevented from churning.
Customer segmentationWith the help of business analytics, the telecom service providers can segment their customer base on the basis of various conditions.
For example: The customer whose monthly usage is above the company’s ARPU (Average revenue per user) can be classified as high revenue earning customer. Specific campaigns can be designed and executed to satisfy this group of customers which will be entirely different from the campaigns to be executed for low usage customers.
The customers having high STD call usage (National Long distance calls) can be targeted with specific STD tariff packs.
In a country like India with various ethnic groups, each having very unique characteristics and behavioral pattern, the usage and needs are significantly different. By analyzing their usage pattern, they can be classified into various ethnic groups.
Therefore, by business analytics and data mining, the operators can identify various segments of customers. With further analysis of the data extracted, the operators can identify and address the specific needs and demands of these customer segments.
Campaign management
The business analytics solutions can provide an integrated platform for campaign design and execution. Based on the customer segmentation, churn score, usage pattern, recharge history; campaigns can be designed for retention, revenue enhancement (increasing customer wallet share) and cross-sell and up sell.
For example: A retention campaign can be designed for the customers who have high usage (monthly usage more than ARPU) and have high churn score. These are valued customers and the company will not like to lose them out.
The campaign’s effectiveness can be measured by capturing the response of the targeted base.
Cross sell and up sellEstablishing a Business analytics platform within the telcos provides an enterprise wise view of the customer. It provides data regarding the customer’s preferences and his/her behavior with reference to all kinds of services provided by the telco.
Analyzing the data extracted regarding the customer usage, their balance availability and their subscription pattern, the telecom service providers can build up data models to identify the product bundling and hence can detect the opportunities for cross sell and up sell.
For example: By analyzing the historic data (say for 6 months) and building a data model, it is found that customers who have high wireless voice usage, also have high sms usage, then a product bundling of voice and sms pack can be targeted for this group of customers.
If a group of customer always upgrades to thelatest equipment and subscribes to the newly launched services, this group of customers can be targeted with a product bundle of latest available equipment and newly launched services (eg: 3G services with handset)
Profitability analysisWith the help of the available data, the telcos can monitor the performance of the individual portfolios. They can measure the return on investments for individual product/services offered, price plans. Based on the performance analysis, the service providers can decide on which plan/products/services to go ahead with in future. They can perform a profitability analysis on the new products.
Credit risk managementBusiness analytics provides views regarding credit payment risk. It can rate the customers based on their historical behavior and credit dues. Therefore, the services need not have to be disconnected for those customers having low credit risk scores, whereas the customers with high credit risk score need to be dealt with lesser tolerance and can be decided for a termination or shifted to pre-paid scheme depending on further data analysis about those customers.
Conclusion
From the above discussion it can be inferred that business analytics can provide the telcos with the required knowledge about their customers, which can be utilized to identify the intricate needs of the customers and help the telcos to serve them better, therefore to achieve an increase in revenue from individual customers and enhance the profitability of the business.
For Enquiries, please contact: arin_mukh@yahoo.com
Link: SAS company details: http://www.sas.com/
Link: Arindam's Profile: http://in.linkedin.com/in/arinmukh
Link: EZine Articles (USA) Publications: http://ezinearticles.com/?SAS---Business-Intelligence---Churn-and-Campaign-Management-Solution-For-Telecom-Industry&id=2598262
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