How does artificial intelligence in supermarkets help increase sales?

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The use of artificial intelligence in supermarkets is here to stay. At an increasing pace, the artificial intelligence (AI) market is predicted to exceed US$8 billion by 2024, according to research released by Global Market Insights Inc. And the enormous interest in this technology can be easily understood. This happens because, among its countless facets, artificial intelligence: Optimizes processes; Facilitates routine activities; Brings practicality to everyday life; Saves time; Offers intelligent solutions; Values ​​each person’s personal taste.

In the supermarket sector, when used well, it strengthens the relationship between brands and customers, increases store profits and also creates greater public loyalty. But after all, what is this artificial intelligence and how can you apply it in your establishment? Check out our full text and understand more about this trend that is here to stay! What is ws data   artificial intelligence? Firstly, briefly, we can define artificial intelligence as a technology that makes decisions autonomously , without the need for human interference. Thus, some examples of the use of AI that can be seen in everyday life are those presented by Netflix, which suggests options for series and films based on what you have watched before. In another sector, we have Waze, the application that uses artificial intelligence to offer you the best routes in traffic, avoiding traffic jams and accidents.



These and many other applications use artificial intelligence to suggest personalized solutions , depending on each person's profile and taste. When it comes to the supermarket sector, the use of this form of intelligence can be of great value to better understand your customer, closer relationships with them and, thus, offer the best solutions for their daily lives.

Why use AI in your store? Using countless data and information as a basis, artificial intelligence in supermarkets evaluates issues such as: Behavior, profile and preference of each consumer; Average ticket; Frequency of purchases, among others. Crossing all this information intelligently, it makes it possible to predict the customer's need to purchase before they even go to the store. For example: you have a customer who usually buys a 30kg bag of dog food once a month. He always buys the same brand, always in the second half of the month.