Using a data-driven marketing strategy on customer relationship management: an empirical case of urban coffee shops in Taiwan

Abstract

PurposeNowadays, the agricultural business environment is expended to the whole world. Transaction records in point of sales and customer relationship management (CRM) systems can be large-scale data for long-established global chain businesses. Thus, the purpose of this paper is to using a proposed data mining approach to discover valuable markets/customers of urban coffee shop industry (retailer) in current environment of Taiwan, which can implement the industry's data-driven marketing strategy on a CRM system.Design/methodology/approachIn this research approach, Ward's method, C5.0 decision tree and a proposed model are applied for discovering valuable markets and mining useful customer rules.FindingsThese found markets and discovered rules can be applied on marketing information or CRM system for identifying valuable customers and target markets.Originality/valueIn this study, the CRM system can be the media for the data-driven marketing strategy in environment of Taiwan. The approach of this research can be applied on other businesses for their data-driven marketing strategies as well.