Customer Relationship Management: Data Mining - Essay Example

Relationship Management: Data Mining Agreeably, employees interact and engage in conversations with customers and prospects daily about the company as well as the products and services they the company offers. Customer Relationship Management (CRM) is system used for managing the company’s interactions with its customers, and it is limited to activities taking place in the customer facing functions such as marketing customer service, and sales among others (Kincaid 2003, p.42). In most cases, CRM software is used to control lead information, marketing campaigns and market participation, and the information gathered can be analysed to emerge with innovative solutions to common customer related problems. CRM includes various elements such as information needed to understand customer better, the process management required appropriate experiences to customers, software tools, and the training and change management elements (Kincaid 2003, p.37). CRM enables an organization to identify its target customers, maximize sale management, improve its relationships with customers through personalization, and identify customer needs among others. Successful CRM depends on the use of technology such as data mining to organize and synchronize sales, marketing, and customer service among others. This paper explores customer relationship management particularly the data mining technique and its importance in an organization. Every business is highly dependent on its customers hence the need to understand and satisfy customer needs, and excellent customer service is an integral part of CRM (Brink and Berndt 2008, p.21) and it is all about being aware of the needs of the customer and respond to them effectively. CRM plays a leading role in business operation as it helps business executives to understand and respond to customer needs in a consistent and effective way. Customer information is the most important part of customer relationship management, and it serves as a critical component of building loyalty (Kincaid 2003, p.47). It is very difficult and challenging to manage countless customers and have many employees to communicate with each customer. Therefore, customer accounts provide necessary information about the customer such as the contact information, order history, and preferences among others. Customer relationship management software assists business executives to keep track of their contacts and schedules. Moreover, CRM systems help salespeople to keep track of customer interactions, and advances in technology have led to increased use of CRM systems by salespeople and business owners because these systems enable them to save time and expense by organizing and presenting important information about interaction with suppliers, customers and other stakeholders. Currently, using data mining tools in customer relationship management is what is trending in the global economy. Effectively examining and understanding customer behaviours and their qualities and needs are the best ways to develop a competitive CRM strategy. This will help in acquiring and retaining reliable clients and make best use of customer value. Successful CRM has two foundations, that is, relevant and timely data and powerful analytical tools. Data mining is an important component of CRM and it can be used as both descriptive and predicative tool (Miguel 2001, p.383). In CRM, data mining assist in determining the behaviour that surrounds a certain lifecycle event and helps in identifying customers with homogenous behaviour patterns. The main focus of CRM vendors has been finding a way of gathering large amount of data. Their major concern has been obtaining full view of a customer. In most cases, the vendors focus on having detailed information about the customer-company interaction. Literally, data mining technique requires individuals to explore and analyse large amount of data. It enables an organization to understand its customers better and improve its marketing, sales and customer support activities. Data mining can create various models including classification, cluster analysis, and association among others. More so, data-mining techniques reinforces the knowledge management process and enables individuals in the marketing department to perfectly know their customer and provide better services that satisfies their customers’ needs. According to Miguel (2001, p.382), descriptive data mining method helps in understanding differences and particularities of various customers and so it enables customer segmentation and creation of various categories of customers based on their qualities. Arguably, data mining is one common data analysis techniques that are used in the identification of most and least profitable customers (Ryals 2003, p.343). Data mining can provide customer insight and this is very important when coming up with an effective CRM strategy. In addition, it can result in personalized interactions with customers and this in turn leads to increased satisfaction and profitable customer relationships via data analysis. Moreover, data mining can support an individualized and optimum customer management in the all phases of the customer lifecycle starting from the acquisition and creation of a strong relationship to the prevention of attrition and attracting again the lost customers. Marketing personnel are more concerned with achieving a greater market share as well as a greater market share of their customers. They can effectively attract, develop and keep many customers by using data mining models. Moreover, there are some rules and equations in the data mining models, which are useful in the identification of vital data patterns, understanding and predicting individuals’ behaviours. Notably, data mining procedure has various stages and so certain software packages known as data mining tools have been established to support the entire data mining procedure. Data mining uses various techniques to analyse large amounts of information to acquire necessary knowledge. More so, data mining is capable of converting large amount of data into knowledge and understandable information. To address CRM objectives successfully, companies have to fully understand their customers and satisfy their needs. This is possible through analytical CRM, which helps them to analyse the available customer information in a more effective manner. Data mining can assist in retaining customers since it allows timely identification of valuable customers with increased likelihood to leave enabling an organization to have enough time to develop and implement retention campaigns. In brief, some of the benefits that can be achieved through the framework of CRM from data mining perspectives include improved marketing strategy, increased reachability to customer with better analysis, and increased customer acquisition among others (Ranjan and Bhatnagar 2009, p.161). Some of the application of data mining is customer segmentation and this is evidently seen in all organizations where data mining technique is used to enclose segments in their customer bases, secondly, customer loyalty is the main focus of every organization and achieving this will give the organization a competitive advantage over others. Ideally, using data mining can be very useful to organizations, as this technique will help them in the identification of certain qualities of customers especially of those customers who are likely to remain loyal to the organization. In conclusion, customer relationship management is a very useful tool in an organization as it assists organizations to manage their interactions with customers. CRM allows organizations to identify its target and improve their relationships with the customers by interacting with them and identifying their needs. Effective CRM involves the use of technology such as data mining technique to be able to successfully organize and synchronize sales, market, and improve customer service. In today’s global economy, data mining is the most common technique used in customer relationship management. Data mining is the exploration and analysis of large quantities of data and generally, it enables an organization to understand its customers best and improve its marketing and sales activities. Data mining can provide necessary information about the customer and this will enable an organization to know their customer well and successfully come up with effective strategies to satisfy their needs and retain them. Various marketing personnel use data mining models to effectively attract, develop and retain as many customers as possible. Therefore, data mining can help bring a significant change in an organization based on company-customer relationship. References Brink, A., and Berndt, A., 2008, Relationship Marketing and Customer Relationship Management, Lansdowne, South Africa, Juta. Kincaid, J. W., 2003, Customer Relationship Management: Getting It Right! Upper Saddle River, NJ [u.a.], Prentice Hall PTR. Miguel, A. 2001, Measuring the impact of data mining on churn management, Internet Research, vol. 11, no. 5, pp. 375-387. Ranjan, J. and Bhatnagar, V. 2009, A holistic framework for mCRM - data mining perspective, Information Management & Computer Security, vol. 17, no. 2, pp. 151-165. Ryals, L. 2003, Creating profitable customers through the magic of data mining, Journal of Targeting, Measurement and Analysis for Marketing, vol. 11, no. 4, pp. 343-349. Read More