Exploring Elements of Content Marketing Using a Natural Language Processing: The Case of Native Woven Clothing
Keywords:
Content Marketing, Natural Language Processing, Native Woven Clothing, SMEsAbstract
The extensive implementation of online social media among Thai small and medium-sized enterprises (SMEs) underlines a significance of effective use of content marketing strategies. However, most Thai SMEs still suffer from applying content marketing without a clear expertise. This study adopts Ashley and Tuten’s (2015) message strategies to investigate elements of text messages necessary for content marketing among SMEs in a native woven clothing market by categorizing them into three message appeals (i.e., functional, emotional, and experiential appeals). The study used a natural language processing to adopt a pre-train model, fine-tune the model, and subsequently proceed to a deployment. Training data was collected from 137 text messages posted by eight native woven clothing SMEs on Facebook pages. The findings offer Thai native woven clothing SME managers, and managers of small and medium enterprises in general, guidelines for creating content marketing economically and effectively. We also extend the application Ashley and Tuten’s (2015) message strategies into an SME context in a growing economy country.
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