عنوان مقاله [English]
Selling products and understanding customers are two influential factors in todays competitive world. To keep up with the pace, different branches in industry such as food industry have decided to attract and increase their customers, products and services and consumer goods such as edible oil are no exception. Increasing brand awareness and retaining customers are two of objectives in this process. Sciences such as data mining are very helpful in understanding customer behavior. Nowadays, data mining and customer relationship management, as two complementary sciences, help to improve getting to know customers, managing customer relationship properly and increasing revenue. In this paper, a research has been carried out on the data of an edible oil producing company using the above concepts. Using K means algorithm and RFM analysis, different customer clusters have been studied and after calculating the optimum number of clusters, customer behavior has been examined using Customer Lifetime Value analysis and an effort has been made to provide solutions for improving customer relationship and reaching company goals. Finally, due to the similarity between recency concept and market share and also market growth to purchase cash flow or monetary, the two concepts have been combined with growth share matrix and the company in question has been analyzed from market share and growth view points and a solution to increase the two factors, which are fundamental concepts in business continuity, has been proposed.