Customer-Oriented development of NPK fertilizers using data mining(Case Study: Agricultural Cooperatives)

The current study aims to provide a data mining approach to customer-oriented development of new products with a focus on one type of fertilizer. The problem considered in this study was due to the high volume and variety of customer demand on the one hand and the limitation of agricultural cooperatives in the variety of available fertilizers on the other hand. Accordingly, the data related to the real needs and priorities of customers in terms of fertilizer type, price, and purchase time were collected using survey tools firstly, and then analyzed based on the CRISP algorithm in data mining. In the first step of data analysis and in order to develop customer-oriented new products, the clustering method was used and thus the variety of fertilizers introduced by customers was reduced from 37 to 5; In a way, the features of the new products were very close to the needs of most customers. Then, using the decision tree method, the desired quality forecast was done for each new product in different time periods and based on, the supply and production pattern of products was provided according to the desire and demand of customers in each season. In general, and according to the results obtained, it can be said that the use of data mining can be useful in the development of new products in a customer-oriented way and this approach is able to respond to issues such as data diversity management as well as customer-centric supply chain management planning.