The large volume of customer information, and also the growing complexity of interaction with these pushed data mining on the front side line in the process of conversion associated with potential and current customers. Combined with the CRM data mining they could help to identify potential customers on which to target, to bid additional products and services in order to current clients, to offer them the right for them product or service and to conduct the marketing campaign aimed at pre-defined customer team.
Also we can preliminarily identify clients who intend to leave us and pro-actively to react in any of the stations for contact with the client (CRM channels). The result is increased income due to the multiple improved opportunities to speak with each client individually and in the most effective way, which leads to optimization of the product sales process and reduces costs.
Data mining can help us analyze very best impact of external market aspects like inflation, bank interest rates, energy prices and other on the businesses as well as the behavior of our customers and in mixture with CRM to show us the very best approach to working with them in the marketing and advertising environment.
In practice this requires the collection of complete information about customers as well as the potential ones to interact with all of them more effectively during all stages of our own relationship with them. These stages these are known as Customer Life Cycle and include 3 main phases:
– Attracting new clients;
– Increasing the value of the existing ones and building long term human relationships with them, turning them into faithful and increasing the period during which they may be customers of the company (lifetime value);
– Identifying and retaining clients of the company who intend to depart.
Data mining can enjoy a key role in each stage, increasing the opportunities for revenue. It must become a key company process, implemented in processes for example sales, customer service, risk management and in the introduction of new products and services.
Application associated with Data Mining techniques to CRM can assist in analyzing the information received through the access points with customers to get its correlation with the business routines of the company reflected in CRM and financial transactions in ENTERPRISE RESOURCE PLANNING systems. It can help for the optimisation of process of sales and the planning of action plans and techniques.
One of the conditions necessary prior to the introduction of a CRM system is transforming the organizational structure and details from product to customer-oriented as well as the reengineering of processes associated with controlling customer relationships. Changes in company culture also require every worker to know and accept the concept of client value and the importance of customer human relationships. It is necessary for the manager group of the company to be familiar with the viewpoint of CRM, to be supportive within the development of business strategy and inspired to attain it.