How This Company is Redefining Retail Experience with Generative AI

The retail giant has built sophisticated algorithms to accurately predict future customer demand, which helps the retailer optimise its buying, distribution, price, and promotions.
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For over a century, Tesco has been a leading player in the retail industry, continuously adapting and leveraging emerging technologies to stay ahead of the curve. The company has over 4,700 stores and employs roughly 3.5 lakh people worldwide. It’s only expanding. 

In a recent interaction with AIM, Tesco Business Solutions director of enterprise analytics, Venkat Raghavan disclosed how it is leveraging Generative AI and other technologies to enhance customer experience, predict demand, analyse customer behaviour, prevent fraudulent activities and more. 

“One area where generative AI can play a big role is in extracting insights out of a lot of reports and dashboards that we build,” he said.

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Besides, Tesco is also exploring how Generative AI can be used on the customer service side. The retailer gets a lot of queries from customers and a major chunk of them gets answered through Whatsapp. Hence, Tesco is exploring if the interaction could be made more engaging with generative AI for better customer experience.  

Building volatile forecasting models

There’s more. Demand forecasting plays a crucial role in the success of retailers. However, if we go back 10-15 years, the classical approach for forecasting was time series.

“Time series says if you are retailing for 20 years, year over year, you will see a certain pattern on trend of sales, certain seasonal impact,” said Raghavan. 

Further, he said with COVID coming into the picture, most retailers have realised that sales is a volatile thing.“But time series believes that history will repeat in some form, either as a trend or as a cyclic or seasonal effect. So the big realisation that we had three years ago was the fact that this philosophy of forecasting is probably not going to work anymore,” said Raghavan, saying that it has now shifted to volatile models. 

In this line, Tesco has built sophisticated algorithms to accurately predict future customer demand, which helps the retailer optimise its buying, distribution, price, and promotions. 

Consumer behavioural insights

Understanding customer preferences and behaviour helps Tesco optimise its supply chain, improve inventory management, and develop targeted marketing campaigns.

The retailer gathers information on customer purchases and their behaviour in stores to understand better what they want, need, and deserve from their products. This data is collected through channels like the Tesco Clubcard scheme, Tesco Mobile App, and customer feedback channels. 

Based on these insights, Tesco has created personalised promotions for customers based on their shopping behaviours. 

“What has helped us is our strong capability to derive insights from our stores, primary research, contact centre feedback, and external data partners to view a connected customer journey and make improvements where possible,” shared Raghavan.

Besides, a deep understanding of its customers also helps Tesco offer personalised rewards and promotions that will have the highest relevance.

Understand Fraudulent Customer behaviour

Fraud in retail can happen in many places. While it’s a broad topic, Raghavan points out two critical aspects- fraud that happens at customers’ end and fraud that happens at the employees’ end. 

A fraud happens, for example, when somebody buys goods from Tesco using credit card details purchased from the dark web.

“While it’s very difficult to understand fraudulent credit cards, it’s relatively easier to understand fraudulent customer behaviour,” he said.

Further, by analysing geofencing data in combination with the types of orders being placed, it is possible to identify patterns in fraudulent orders. 

“My team’s job is to understand how they think. Can I run a real time algorithm to catch the thinking? One of the thinking aspects is understanding that they will want to increase value per unit.

“That’s one of the variables. Besides, there are a lot of other variables and we put all of this into a real time model which is trying to detect fraudulent activities, and on a monthly and yearly basis, we have stopped huge numbers of fraudulent transactions in real time,” Raghavan said.

Unleashing Tesco’s Tech Prowess 

“Throughout our history, we have constantly explored ways to infuse emerging technologies to improve how we operate our business,” said Raghavan.

“Some prime examples are our foray into online retailing in the 1990s, much ahead of most retailers, and our Clubcard programme launched over two decades ago, one of the first retail loyalty programmes in the retail industry,” said Raghavan. 

In the present age, Tesco is leveraging emerging technologies to continue being a dominant force. “We have taken a data-driven approach to every decision we make, from customer engagement to supply chain management. This has been a key factor in our success and is now one of our most valuable assets,” concluded Raghavan. 

Pritam Bordoloi
I have a keen interest in creative writing and artificial intelligence. As a journalist, I deep dive into the world of technology and analyse how it’s restructuring business models and reshaping society.

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