Uncovering the Probiotic Supplement Landscape: Market Offerings, Sales Patterns, and Future Forecasts Using Machine Learning Approach - A Case Study of Montenegro.

Abstract

Global increasing awareness about the health benefits of probiotics resulted to explorational growth in probiotic food supplement market. However, in some countries such as Montenegro, specific probiotic supplement regulation and comprehensive market analysis are absent, hampering the understanding of consumer preferences, market trends, and potential economic impacts of this industry. This article aims to delve into the Montenegrin market of probiotic food supplements, thoroughly examining various product types and their key characteristics. Using the case study of a pharmacy chain, as an example of organizational level, the sales, sale patterns, and trends are examined. Furthermore, we developed and employed a machine learning model for forecasting future sales. The market analysis highlighted the importance of setting national probiotic supplement regulations to enhance Montenegrin consumer understanding and trust, ensuring product efficacy and safety. Our study clearly showed increased interest in probiotic supplements as well as a constant positive trend in probiotic supplement sales. Furthermore, we found the correlation between foreign tourist visits in Montenegro and the yearly seasonality of probiotic supplement sales. Developed support vector regression machine learning model on time series data showed a good forecasting accuracy, clearly indicating that the same could be used for national sales forecasting. The insights from this study could promote the establishment of national probiotic supplement regulations, enhancing consumer protection and market credibility. Additionally, developed machine learning model provides the industry with valuable predictive tool, enabling companies to optimize their supply chains, effectively meet demand, and make data-driven decisions that could support sustainable market growth.