Customer segmentation using k-means clustering for developing sustainable marketing strategies

Abstract

Sales and marketing is the indispensable department of an organization which leads to the generation of revenue and building customer relationship. Marketing is the process of finding the potential customers and sales is the process of converting those potential customers into real customers. Hence, it is imperative that marketing and sales go hand in hand. Developing marketing strategies needs proper market research which can cover the relevant pointers like demographics, culture, spending power, income and many more. The process of segmentation, targeting and positioning (STP) is carried out to develop marketing and sales strategies. STP is done by collection of the marketing intelligence. For this process, surveys are also used but data mining has far more effective and better results so far. Organizations tend to take risk because of the importance and relevance of the marketing and sales department. Most of the budget in the organizations is allocated for marketing and promotional activities. For making data-driven and accurate decisions, data mining is used in various fields to extract valuable information and patterns. This paper discusses the use of the data mining concept on marketing. This paper aims to analyze marketing data with k-means data mining clustering techniques and to find the relationship between marketing and k-means data mining clustering techniques.