Making product recommendations by analysing data: Application in an FMCG company

It is important to analyse sales such as to understand customer behaviours, determine new product design, sales strategies, and forecasting in Fast Moving Consumer Goods (FMCG) sector. FMCG companies have large sales teams to have a close relationship with their customers. Because of this reason, following sales has become important to improve brand awareness, company sales, and create new sales strategies for the company by the sales team. Especially these days, there are lots of product launches in the market. Increasing product diversity gives rise to customer loyalty is decreasing. That creates a large area to improve new channels, strategies, and analysing of competitors for companies. To create new strategies customer behaviours data such as which products customers buy and see, the time customers spend in shopping, and how often they buy the product have given information for forecasting. This project, it is aimed to create a recommendation system using customer behaviour data with internal company data for increasing sales and improving internal operations in FMCG companies. A sample data set has been created and it has been seen that the model for increasing sales and enhancing internal processes could be valuable for companies in the FMCG sector.