saikumarnerella / customer-segmentation

Customer-Segmentation

The project serves purpose of understanding the nature of customers of a retail store in order to benefit the business involved. The perceptions are based on real time sales data available, the decision relies on characteristic analysis on customers and product which in return should be able to imply the categorization of customers belonged in sales and will be belonging in the future benefit goal. The profiling based on cluster analysis will help the store manager to know their customers and products in a better way and assist them to make effective decisions to improve the revenue of the supply chain as well as the customer service.

The intent of this undertaking is to explore new business goals and trends using data segmentation which could be accomplished with help of the concepts of K-Means clustering since the data is categorical. The approach is to find the subgroups using the data such that it can be profiled on basis of different features that are recorded by the store over time. Once we have analysed the data we came up with the profiles with respect to the respective categories, the manager can use these insights and develop strategies and activities that will provide value to the business in number of areas. The advantage of clustering is that it is not based on any predetermined thresholds or rules but relies on data itself to reveal different patterns.