Optimizing CRM in Telecom with Data Mining


With over 700 million people using mobile phones across the country, India has fast emerged as the third largest telecom market in the world. The industry is facing tremendous competition today with the emergence of a number of vendors, each with unique brand propositions. In a market where the customer has no dearth of choices and the cost of switching over is minimal, a key strategy for companies to retain customers is through Customer Relationship Management. Within the ambit of CRM applications, data mining is very popular in the telecom industry. In many ways, this is a foundation for several of the core business processes in this sector.

Why use data mining for Telecom CRM?
Gaining a comprehensive view of the customer is one of the key benefits sought from data mining. The telecom industry is specifically customer-oriented.
  • From customer care to billing and online services, there are many touch points where an operator needs to connect with customers. These are not merely channels of communication but act as an extension of the brand and product itself.
  • When a customer logs on to the company website, he/she may be looking to pay bills, find an ideal data plan or track their usage. Hence, companies must understand such customer needs and requirements and cater to these in the most effective ways to retain clients and build loyalty.
  • Data mining can help them derive the consumer insights required to proactively engage and serve the customer.
  • A unique capability of data mining is to create compact consumer profiles based on their usage. Every call made over a telecom network gets recorded as a call record. These can give a comprehensive understanding of a customer’s usage habits and trends over a period of time. Such information is not only useful to customer care agents but is also instrumental in improving the service offer.
  • Operators can create better deals and plans by understanding how the customer uses their service.

Data mining for CRM in Telecom will provide following advantages: 

Customer Care (via phone and the company’s website)
  • Data mining can be used to create effective IVR menus and interactive websites. For example, clients often tend to have similar and repetitive queries. Data mining can help identify these so that vendors can build their customer care to answer these in the quickest and easiest ways.
  • Data mining equips customer care agents with the right information to handle queries and resolve issues with speed and accuracy. It is this tool which ensures that agents have client information such as billing history, usage, services availed and more, at the click of a button.
Sales Management
  • Data mining can help optimize sales channels by shortening sales cycles, identifying opportunities and aiding closure of deals.
  • Sales teams can be provided with valuable customer information to take them through the entire procedure of turning a prospect to a client.
  • Identification of sales opportunities is facilitated through an understanding of market trends, customer needs, competition and responses from different media channels, all brought about by applying data mining techniques.
  • Managers can also predict sales volumes by foreseeing demand and creating provisions for the same.
  • Complete records of all customer usage and interactions aids holistic management of the entire sales process.
  • Lastly, historical information can provide crucial customer insight to aid cross-selling and up-selling of products and services. 
Marketing
  • Consumer profiles created through data mining can be used to plan highly targeted marketing campaigns. One of the most popular applications for data mining is in creating successful promotions. Special promotions such as calling circles, reduced rates to certain numbers or at certain times of the day, data and talk time packages and much more are especially created to attract prospective customers as well as increase loyalty and usage of current customers.
  • Customer call records can help classify the customer base into categories such as business, students, residential and much more. Each of these groups can then be targeted with different and specific marketing techniques.
  • Historical data can also help predict customer lapses. Once the company is aware of the possibility of a customer leaving, they can take the necessary steps to prevent this and retain the customer. This saves a lot of lost revenue as well as the additional costs of attracting new customers.

The applicability of data mining techniques within the telecom industry is wide and varied. From network reports to fraud detection, it can be applied across various business processes of any telecom company. Efficient data mining can help streamline core business processes to improve productivity and maintain profitability. But at the same time, telecom companies must be aware of and fully implement the privacy norms involved with handling such personal data. A lapse here can have a major bearing on the brand and its reputation, not to mention financial losses. In this quickly evolving and dynamic sector, telecom operators need to concentrate on a CRM solution that utilizes data mining to gain crucial competitive advantage for progressive growth.

Neha Kapoor 

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