Basket Analysis & Product Recommendation

Market basket analysis or product recommendation is where you take inventory and point-of-sale data to predict which combinations of products will sell the best. With a clean sales history, businesses can identify which products tend to be purchased together with the solution. Simply speaking, it allows retailers to identify relationships between the items that people buy.

Using machine learning, retailers can then recommend an additional item to the customer based on the item in their basket.

AI for market basket analysis

This may seem like an obvious and simple business strategy. After all, why wouldn’t I be able to offer customers an additional product based on historical purchase trends? The relational data is difficult to correlate without the extra muscle that is artificial intelligence. In addition, market trends and behaviours are constantly shifting, regardless of the industry, especially in retail.

A valuable feature of product recommendation that wouldn’t be possible without AI is the ability to identify trends and relationships across various dependent variables such as location, demographic, and time.

Benefits of market basket analysis

  • Optimize store layout.
  • Offer special deals and discount.
  • Create product combos to encourage sales for relational products.
  • Manage price and sales inventory.
  • Improve customer satisfaction and brand loyalty.