Development of An Artificial Intelligence-Based Model To Improve Digital Marketing Effectiveness For Tempe Chips MSME A.M.J

Abstract

Micro, Small, and Medium Enterprises (MSMEs) in the food sector increasingly use digital channels to reach consumers, yet many still rely on general promotion strategies that are not supported by systematic customer data analysis. This study aims to develop an artificial intelligence (AI)-based digital marketing model for Tempe Chips MSME A.M.J by combining customer segmentation, promotional content optimization, transaction-flow support, and chatbot-assisted interaction in a web-based prototype. The study employed a Research and Development approach with prototyping stages consisting of problem identification, data requirement analysis, system design, prototype implementation, and limited functional validation. The prototype was designed to support product presentation, product detail exploration, shopping cart management, checkout, invoice generation, WhatsApp-based payment confirmation, and chatbot-based customer assistance. The result indicates that the proposed model can organize digital marketing activities into an integrated customer journey from product discovery to order confirmation. The main contribution of this study is a practical AI-oriented framework for MSME digital marketing that links customer data processing with web-based sales support. However, the current validation remains functional and descriptive; conversion-rate improvement still requires longitudinal testing using real campaign analytics, customer interaction logs, and comparative pre- and post-implementation measurements.