Market Basket Analysis

Market Basket Analysis is used to identify or gain interesting insights into the way customers buy items. It finds out the combination of items which are most likely to be bought together. For example buying milk and bread together can lead to buying butter. Identifying such patterns from the transaction data collected over the years provide new window of opportunity to explore and understand the purchasing behavior and thus can be used to increase sales through cross selling and targeted marketing. Market basket analysis is not limited to retail sales but are applied to a wide range of areas like analyzing credit card purchases, fraud detection for insurance claims and so on. Data Mining technique called association rule mining is usually used. Algorithms like FP-Growth and Apriori algorithm are usually used for mining the transaction data to get the desired patterns.