Twitter content strategies to maximize engagement: The case of Thai Banks

– This study aims to examine how the marketer-generated content (MGC) strategies of banks affect their followers’ engagement on Twitter. Design/methodology/approach – A sample of MGC tweets from official Twitter accounts of both public and private banks in Thailand was collected using a Twitter analytic tool. Message features, content, intent, and post engagement were manually and automatically extracted from these tweets. Proposed relationships were analyzed using descriptive statistics and hierarchical regression analyses. Findings – The results indicate the negative influences of two control variables, media type (text), timing (evening), and some sub-types of information-sharing content and emotion-evoking content, as well as positive impacts of public bank type, some message features i.e., hashtags and mentions, media type, some content regarding emotion-evoking and action-inducing, and intent (request). Practical implications – Useful guidance for bank marketers to maximize engagement is offered. The suggestion for revising bank content strategies on Twitter are presented. Originality/value – This study examines the content strategy from a different perspective, which has rarely been employed in the literature. Additionally, this study reveals the Twitter content strategies of the Thai financial sector, which is a crucial sector supporting others. Understanding consumer behavioral engagement could help them to publish the right MGCs.