Predicting Customer Buying Behavior Using the BG/NBD Model to Support Business Sustainability in a Self-Service Context

Customer loyalty is crucial for (while fueled by) business sustainability. Loyal customers advocate for a company’s offer and sustainable practices, while their steady support generates stable revenue stream, lower acquisition costs, and predictable cash flows that enable long-term business viability. Such a stable revenue stream is especially critical in periods of intense competition or macroeconomic disruption (e.g., COVID-19 pandemic) which profoundly influenced consumer behavior. In this context, the purpose of the current paper is to test the BG/NBD prediction model for its potential validation as a practical tool in estimating the buying behavior of customers of a self-service car washing company before and within the COVID-19 pandemic period. To achieving this, transaction data of the company’s customers was retrieved from the company’s internal information system and used as input for BG/NBD model. The model proved its effectiveness in estimating the total number of repeated transactions for the year 2020 based on the 2019 data at total customer base and at loyal customer level. Loyal customers were considered from the behavioral loyalty perspective only and defined as customers which used the company’s services at least once in both years. In the estimation of the repeated transactions frequencies, the model’s prediction accuracy increases with higher frequencies of loyal customers.