Leveraging AI in Retails Industry

AI in Industries

Traditional analytics worked perfectly to provide data to the retail industry for many years. Over the last few years, however, AI (Artificial Intelligence) and ML (Machine Learning) have brought a completely new level of information processing that offers business insights that were simply not available in the past.

This is an unstoppable trend, with the number of retailers using AI/Machine Learning solutions increasing sevenfold over the last four years.

How is AI used in the retail industry?

The number of AI applications in the retail industry is increasing rapidly. Below are a couple of examples where AI is already transforming the industry.

Cashierless stores

Robotic stores will bring about fewer employees, huge cost savings, and increases in ROI, shorter lines, and reduced waiting times for customers. Human error is virtually eliminated.

Chatbots that help with customer service

AI chatbots can provide a tailor-made level of customer service based on that individual’s past buying and current browsing history. They can help customers find the right products, suggest similar or complementary products, and even send notifications about the latest collections.

Smart shelf tags

These make paper price tags redundant and can even provide nutritional information, video ads, and promotions on the displays. Thanks to their live inventory monitoring capabilities, they can also help with stock management.

Supply chain management

An AI service can be used in the supply chain to help calculate future demand for a particular product by taking into account weather, location, sales history, promotions, trends, and more. This information can in turn be used to calculate restocking levels with a much higher degree of accuracy than before.

Virtual fitting rooms

This is probably one of the most exciting applications of AI in the retails industry. A virtual fitting room is an amazing way to locate the ideal outfit with every element perfectly matched without spending hours in the process. A virtual fitting kiosk will scan the customer in 20 seconds and in the process measure up to 200 000 points of his or her body.

Visual search

When a customer has spent half an hour searching for something, he or she would often lose their appetite for buying something that is referred to as ‘buyer burnout’ in the industry. To prevent this, retailers are starting to implement what is known as ‘computer vision’. Driven by AI algorithms, a customer can take pictures of any item of clothing he or she likes, and virtually immediately get served with details about similar products that are available.

Tracking customer satisfaction

AI applications are now able to detect a customer’s mood by using facial recognition systems. Cameras can e.g. be installed at checkout lanes, and if a customer looks angry or annoyed, a human shop representative can be informed. The latter can then talk to this customer to prevent relations with him or her being harmed permanently.

Predicting customer behavior

There are already AI platforms on the market that can build an individual profile of each customer based on behavioral economics. These platforms analyze the person’s emotions and psychology to increase the probability of him or her buying something. The algorithm also analyses the customer’s behavior and emotional responses during previous shopping experienced and then suggest optimal pricing offers for that particular individual.

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