Explain the Causes of Customer Dissatisfaction based on Text Mining Analysis

Abstract

Customer satisfaction requires the customer to be happy both in daily and long-term and global interactions. People's opinions about the products of a company on websites and social media can provide useful information for companies to evaluate customer satisfaction. In this research, using the methodology text mining and k- means clustering, customers' opinions about the three brands of Snowa, Pakshoma and Parskhazar from domestic appliances and comments on the three brands of Samsung, LG, and Tefal from external home appliances in the website of Digikala.com were analyzed. The results of this study show that dissatisfaction factors were clustered in six attributes, product failure, and price proportions with performance, efficiency, design, manufacturing quality and after-sales services. In domestic appliances, the most dissatisfaction factors were the product failure, price proportions with performance, manufacturing quality, after-sales service, efficiency, and design. And the factors causing dissatisfaction in external home appliances were manufacturing quality, product failure, design, after-sales service, price proportions with performance, and efficiency.

Keywords

• : clustering
• text mining
• customers dissatisfaction
• home appliance