THE IMPACT OF ONLINE MARKETING, SERVICE QUALITY AND CUSTOMER LIFESTYLE FACTORS AFFECTING CUSTOMER ENGAGEMENT IN MYANMAR PEOPLE’S TOURISM MARKET

Abstract

In this study, statistical methods were used to analyze the impact of online marketing, service quality, and customer lifestyle on customer engagement in Myanmar’s tourism market. Specifically, regression analysis was employed to examine the relationships between these independent variables (online marketing, service quality, and customer lifestyle) and the dependent variable (customer engagement). Additionally, descriptive statistics, including frequency, percentage, mean, and standard deviation, were used to summarize demographic data and provide an overview of participant responses. Using survey questionnaires to collect data from the 400 respondents, consumers interested in tourism from Myanmar, and the convenience sampling technique which is a non-probability sampling method was used to collect the data by using the Google forms. The questionnaires include standardized scales to measure consumer purchasing decisions regarding online marketing, service quality, and customer lifestyle. These statistical approaches allowed for a clear understanding of the extent to which each factor influences customer engagement, guiding targeted strategies for Myanmar’s tourism businesses.

The hypothesis testing in this study provided insights into the impact of online marketing, service quality, and customer lifestyle on customer engagement in Myanmar’s tourism market. Results indicate that online marketing factors, particularly content and messaging (p = 0.001) and digital advertising (p < 0.001), For service quality, all tested factors—operational excellence, customer interaction, and post-service feedback—showed a significant positive impact on customer engagement, with p-values of 0.002, 0.000, and 0.017 and customer lifestyle factors such as travel preference (p = 0.003), demographics and psychographics (p = 0.000), and sustainability practices (p = 0.000) were found to be significant predictors of customer engagement.