Investigating Consumer Behavior to Create Expected Customer Value, Using Big Data Analysis

The concept of “value” in a business is a potential product or service that a business promises to deliver to the customer and in general, it is the reason why a customer chooses a brand and prefers it over competing brands. In recent years, with the increasing presence of consumers in social networks, it has become possible to access data related to the interests and expected values of consumers. The purpose of this study is to identify the components of value, to create and provide value to the customer, by analyzing the opinions and user-generated content in social networks. For this purpose, 41904 costumers review relating cell phone from the Digikala online shopping site using machine learning algorithms and topic extraction by inductive approach is analyzed. According to this study, five main groups of values were detected: 1. Functional values, 2. Economic values, 3. Qualitative values, 4. Emotional values, 5. Social values. Also, the components related each group was identified. The results show that by using big data analytics, it is possible to obtain a clearer image than the expected values of the customer with less waste of resources and produce a commodity tailored to customer values.