The use of Artificial Intelligence to offer personalized recommendations to customers is an increasingly popular strategy among businesses. This is due to the increase in data volumes and the development of more sophisticated AI technologies. With the help of AI, companies can offer more accurate and effective recommendations to their customers.
For example, imagine you have an online store that sells clothing. With the help of AI, you can gather data on your customers’ interests and preferences through their previous purchases, clicks, and interactions on the website. From this data, you can create a customer profile and offer personalized product recommendations that match their preferences and interests. This not only improves the customer experience but can also increase sales and customer loyalty.
Another interesting application, in the case of supermarkets, is through the data collected from previous purchases and customer preferences. A recommender can help identify and create “savings packs” by analyzing data, rather than relying solely on intuition.
But how does AI offer these personalized recommendations? In short, AI analyzes customer data and compares it to other similar customer data to identify patterns and similarities. From here, AI makes personalized recommendations for customers based on their data and the data of other similar customers.
