Purpose – Online customer relationship management (CRM) is an important issue for implementing digital marketing of electronic commerce or social commerce. The purpose of this study is to establish valuable markets for discovering customer knowledge from data-driven CRM systems for enhancing growth rates of businesses. Airline or travel agency industries are online businesses in the world. Therefore, the industries in Taiwan will be an empirical case for this study. Design/methodology/approach – This research applied a procedure with an applied proposed model for establishing valuable markets from data-driven CRM systems. However, the study used a proposed customer value model (recency, frequency and monetary [RFM]; RFM model-based), the analytic hierarchy process (AHP) procedure and a proposed equation for estimating customer values. Findings – For enhancing the data-driven CRM marketing of the industries, in this research, the market of air travelers can be partitioned into eight markets by the proposed model. As well, the markets can be ranked by the AHP procedure. Furthermore, the travelers’ customer values can be estimated by a proposed customer value equation. Originality/value – Via the applied proposed procedure, online airlines, travel agencies or other online businesses can implement the research procedure as their data-driven marketing strategy on their online large-scale or Big Data customers’ databases for enhancing sales rates.

Introduction

Airfare always takes the major portion of a traveling budget for transportation costs of an international travel plan. Hence, low-cost carriers (LCCs) attract more international travelers for their travel plans. In Taiwan, a new LCC was launched by China Airlines (Tigerair Taiwan). In other words, the impact of airline markets in Taiwan between regular airlines and LCC airlines will be extremely competitive in the near future. Therefore, for enhancing online customer relationship management (CRM) systems of international regular airlines in Taiwan, the purpose of this work is to analyze customer values of international travelers for marketing strategies of online CRM systems in the regular airline industry in Taiwan. However, a data-driven marketing strategy for online CRM is an important issue for airlines’ ecommerce or social commerce. The results of this research can be applied in their online merchandising or social commerce systems for enhancing the sales rates. Typically, retailers can realize their markets by using a questionnaire, survey or some investigation methods with designed variables of customer shopping benefit. Hence, the markets can be identified by recency, frequency and monetary (RFM) model as well (Kotler and Keller, 2016; Chiang, 2018). However, air travelers and retailers’ shoppers have different shopping behaviors. Thus, the RFM model can be modified due to different characteristics of industries (Chiang, 2012, 2018). Regarding the model, the researcher discussed with three scholars and managers in airlines’ management field, and the discussion results showed that three variables can identify travelers’ customer values. In accordance with the discussions, the research proposed a novel model for airlines and travel agencies to identify travelers’ customer values and markets, which consists of frequency, monetary and average number of group travelers (FMA model, RFM model-based). Furthermore, the FMA variables can be substituted for other businesses. The FMA model (markets) can be ranked via the well-known decision-making procedure of analytic hierarchy process (AHP, Saaty, 1990), because the AHP procedure can identify the weights of markets’ customer values. Via the weights of rank markets, the research proposed a customer value equation. The travelers’ customer values can be obtained using the proposed equation. However, the airlines/travel agents’ group or other businesses may implement customized marketing plans in their online marketing systems. Different types of enterprises can use the RFM model in various ways to plan their marketing projects for enhancing customer value or extending customers’ life cycle (Berry and Linoff, 2004). This research revises the RFM model to be the FMA model for airlines and travel agents’ group; the F variable is “frequency travel times in a specific period”, M variable is “average travel monetary in a specific period” and A is “average travel member number of group travelers in a specific period.” Via the analysis of the FMA model, the travelers’ customer values of family tourists can be discovered clearly. Hence, the study enhances the RFM model to become more suitable for observing the customer values of group travelers.