Personalization of Supermarket Product Recommendations

Grocery shopping is a daily activity for most people. Not only do people buy what they need but probably also what is promoted at the time. Super markets promote some products daily, or weekly. The problem is that they promote the same products to all people. Some people might like the products whereas some might not. What is lacking is a personalized promotions so that super markets will promote products based on user’s shopping history and history of people with similar history. Such promotions will introduce new products to users besides the same ones, which will broaden their product range. We believe that this a win-win situation since users will be promoted products that they are likely to buy and super markets will increase their sells.

To achieve this goal, we are going to use some existing data from supermarkets and some other platforms. We are going to develop a model with the help of content based and collaborative filtering.