Customer clustering using K-means clustering: Supporting customer relationship management system

PT. X is a consumer good company with a variety of products such as consumption salt, packaged cooking oil, soap, sugar, and so on. Currently PT. X has distributors (customers) whose role is to market products directly to consumers. To increase sales from each distributor, PT. X provides special treatment. Special treatment is given manually for certain distributors. This is felt to be less than optimal because the special treatment given is not right on target for each distributor who has the most sold superior product types. Therefore, we need a distributor clustering system using the K-Means method referring to sales history data. The proposed system also has features that can help distributors to place orders independently, confirm payments, submit returns, submit complaints, and exchange reward points for prizes that can be settled by the company. The results of the system have been tested for system acceptance using a questionnaire that was distributed to 5 users. The results of the system acceptance test show the distributors satisfaction level with the system. Distributors feel the convenience and benefits of the system.