Over the years, the basic retail experience has remained more or less the same for the consumers. You go to a store, you look for the right product, and you make a purchase. But for the retailers, it is ever-changing. Analyzing consumer behavior is one of the biggest challenges that CPGs all around the world face. With increasing complexities, traditional auditing methods have proved inefficient.

Recent advancements in artificial intelligence and machine learning have hugely contributed to the growth of Image Recognition and Object Detection in retail. While Image Recognition and Object Detection are used interchangeably, these are two different techniques. Image Recognition is the process of analyzing an input image and predicting its category (also called as a class label) from a set of categories. For instance, consider an automatic store checkout scenario. The user displays an SKU in front of a camera that is powered by an Image Recognition software. The software, when trained on all the SKUs present in the store, can predict the SKU shown by the user as one among all the SKUs.