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The strategic objective of CRM as Customer Profitability Management is to develop long-lasting, profitable relationships with customers. This is achieved by increasing customer loyalty and exploiting the potential of the customer base. In Customer Profitability Management, a company has to identify and nurture profitable customer relationships. Unprofitable relationships have to be made profitable or abandoned. Extensive data analysis that will not only differentiate between profitable and unprofitable customers, but will also target product offers to individual customers, can support this task. In a first step, a company has to implement loyalty management, customer profiling, and customer scoring processes.

Customer profiling develops a profile for each customer, which forms the foundation of long-term strategic customer planning. Customer scoring, moreover, discovers individual cross- and up-selling opportunities. The results are transferred to the campaign and sales management process. This CRM approach employs methods for the monetary assessment of customer relationships to establish equilibrium between investments in customer relationships and realized profits.

Besides customer assessment, precise definition and control of CRM measures in the context of loyalty management are necessary. Within performance management, the profitability of CRM measures and the development of customer segments are monitored. A data warehouse and other analytic CRM systems make up the core of the information systems infrastructure. As in Customer Contact Management, operational and collaborative CRM systems enable employees’ efficient management of customer data, communication, and contacts.

How to improve Sales Productivity ?

Organisations have all the information they need to improve sales. What most of the lack is insight in to that information.

With SFA applications, organisations automated the sales process and managed data. The managers should have a clear picture of what works and what doesn’t. They need this information to make intelligent , proactive decisions, not two weeks after the quarter ends.

Mangers are challenged to determine such basic data points as sales by channel, customer and territory or projects of revenue by product and sales rep before the end of the quarter. How these interdependent dynamics influence each other and how they can be tweaked to boost sales performance is often mere guesswork.

In a recent study on sales effectiveness conducted by Accenture, out of 178 senior executives polled, the most often cited sales performance issues were related to leads. According to Accenture, " Along with problems with qualifying and managing leads effectively, the lack of performance metrics, inadequate customer data, and lack of capabilities for analysing customer data rounded out the list of top performance challenges." The study reported that a total of 55% of respondents found it difficult to assess which leads were qualified.

That’s where analytic application comes in. Sales analytics can play a key role in driving greater productivity and efficiency, especially during periods of slow sales. Many organisations have realized they need to go beyond simply automating current sales operations.

These companies are enhancing their sales operations and promoting shorter sales cycles by providing the field with an intelligent, 360 degree view of their customers.