October 11, 2017
In 1956, John McCarthy, then a young assistant professor of Mathematics at Dartmouth College, organised a summer workshop to brainstorm ideas on thinking machines. It was in this very workshop that the concept of artificial intelligence (AI), as we know it today, was birthed.
While AI has been in existence for over 60 years, it is only in recent years that we have witnessed breakthrough applications of this technology due to the availability of rich useable data and high-speed computing systems.
Retail is testament to this fact. With changing lifestyles and growing time constraints, AI has considerably changed the face of retail over the last few years, with retailers looking to create a fun-filled and rewarding experience for their customers.
Every retailer dreams of having the right product on the right shelf at the right time. AI can make this dream a reality. Based on previous sales data and information about events, weather and demographics, machine learning models can be built to help predict the demand for a product weeks ahead, so that the right quantity of the product can be ordered from the suppliers.
Based on the customers’ shopping data, it is possible to infer the products that they will buy together the next time they shop. Using AI, retailers can decide where to place their products strategically and also create a more ideal store layout.
It is also important to replenish products on the shelves to ensure they are not sold out. Not filling the gaps in the shelves is a missed sales opportunity for the retailer. While traditionally identifying gaps in the shelves has been a manual process, with the help of AI this process can be automated.
By capturing images of the shelves from in-store cameras or using a robot that walks along the aisles of the store, and analysing those images using deep learning algorithms, gaps can be detected and instructions given to replenish the products.
The shopping journey of customers can also be revolutionised with the help of AI. Customers can interact with digital assistants in the store to help them locate a product, arrange for an unavailable product to be delivered or even understand alternate product choices.
With advancements made in the field of natural language processing (NLP), it is possible to create human-like interactions with these digital assistants. By linking customer data with sales data and analysing the customer’s purchase pattern, it is possible to get a deep understanding of the customer and their needs even before they do.
Using face recognition technology, it is possible to identify the customer and with our understanding of the customer’s shopping preference and behaviour, it is possible to offer them personalised product suggestions and coupons.
The check-out queue is possibly the biggest shopping woe for an in-store customer. While retailers have been trying to address this problem using self-service checkouts and better queue management solutions, it remains an area of concern for many.
AI can help create a seamless check-out experience where the customer enters a store, picks the products he or she wants and simply walks out of the store without the need to stand in any queue at all.
On entering the store, the customer can be identified using their loyalty card or by using facial recognition system in the in-store cameras. Their actions of picking or browsing the shelves can be captured using machine learning-based activity detection systems.
The products picked up by the customer can again be identified using image classification systems and will be automatically added to their basket. When the customer walks out of the store, the items in the basket will be billed and charged to their linked payment account.
Fitting rooms is another issue that is being addressed with the use of AI and augmented reality. A virtual fitting room allows the customer to try out various dresses and accessories before buying one. With AI-based fashion recommendations that considers various factors such as style, fit, body shape and fashion trends, customers can virtually try out different dresses before buying any.
Undoubtedly, such AI-based applications are only the ‘tip of the iceberg’ and its potential is humongous. What was yesterday’s fiction, has now become today’s reality. A fact that is here to stay and re-define the world of retail.
(The writer is lead search scientist at Tesco, Bengaluru)
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