One of the most important tools for any store is trying to predict what a customer will want to buy and how to market their products to that person based on those predictions. Artificial intelligence works to log and categorize each product in a store according to its characteristics, and uses a customer’s viewing and purchasing history alongside what other customers who bought similar products have liked. A computer algorithm then judges which products they’ll be most likely to find attractive next. Building consistently more accurate recommendation engines is the next frontier for online shopping.

Again utilizing the millions of searching and buying data points generated by online consumers, a reliable search engine is the first step in retention and satisfaction. A search engine must act as the online sales representative, directing the shopper to exactly the item they were looking for.  And through machine learning, as the system sees more searches and hit results, it will continuously improve its output.

Artificial intelligence can be used for more than just customer interaction. Connect your inventory database to a machine learning system to improve the processes through which inventory is managed and re-stocked as well as predict when certain products will be in high demand and ensure that you can be prepared accordingly.

Almost every modern consumer product provider is vertically oriented, in that their product passes through many different stages and in many cases through several different enterprises, before the final product is ready to be sold to the public. Artificial intelligence helps to integrate that supply chain and make it more manageable for all parties, limiting carrying costs and conveying information in real time across stages of production.