Recommender Systems for Personalized Business Marketing: Employing Artificial Intelligence and Business Intelligence in Machine Learning Techniques

The prediction of a business plays a major role in market analysis. In order to look for the business potential in the market, we have conducted a study to explore how the combination of artificial intelligence (AI) and business intelligence (BI) techniques can be used for regional market analysis to get the best potential in an area and predict the business. Our research focused on analyzing and interpreting data from various sources, such as demographics, economic indicators, consumer behavior, and social media. Decisions are made in terms of two parameters: insight and forecast. We aimed to generate insights and forecasts that would assist businesses in making informed decisions. To achieve the insight and forecast, we used the OSEMN framework. OSEMN stands for Obtain, Scrub, Explore, Manipulate, and Interpret. This framework is useful in gathering relevant data, cleaning and preparing it for analysis, exploring patterns and trends, manipulating the data as needed, and interpreting the findings. We conducted a regional market analysis case study, by employing machine learning algorithms and data mining techniques within this framework. Our project resulted in providing a piece of valuable information on market trends, customer preferences, and potential investment opportunities. These results demonstrated the potential of AI and BI in enhancing business intelligence and decision-making processes, particularly in the context of regional market analysis. We highlighted the benefits of utilizing AI and BI technologies while acknowledging the boundaries and challenges they may present. We also discussed the implications and limitations of this approach. We have suggested some potential areas for further study in this field, recognizing the need for ongoing research to refine and expand upon these techniques.