Raj Seshadri, who heads the global data and services team at Mastercard, is most excited about Shopping Muse, a generative AI-powered tool that helps retailers personalise the shopping journey for customers. In her opinion, solutions like these are the next step in the retail revolution and are core to putting the customer back at the centre of the buying process. On a recent visit to the country, she spoke to Sudhir Chowdhary about how Mastercard is leveraging machine learning to deliver better outcomes for both brands and customers. Edited excerpts.
Where do data and analytics come in the customer experience personalisation journey?
In today’s rapidly evolving business landscape, customer experience has emerged as the key driver of operational excellence. Understanding ‘how’ an organisation delivers products and services to its customers has gained prominence over ‘what’ it delivers. Personalisation is like a basket of LEGO pieces, in different colours and shapes which can be put together based on the specific needs of the customer.
Personalisation is key to Mastercard — as we empower our customers to unlock a holistic view of consumer behaviour, distill actionable insights and make data-driven decisions. All our products that drive engagement of a company with its consumers touch upon personalisation. For instance, we’re one of the largest loyalty services providers globally. It includes marketing services, where we help our customers acquire consumers, develop them and drive engagement with them. It includes insights businesses, where we derive insights that the customers can use to make decisions. One of our key solutions is Dynamic Yield, a state-of-the-art personalisation platform and decision engine company.
Dynamic Yield supports our customers in achieving numerous benefits, including elevated customer lifetime value, heightened engagement, enhanced customer loyalty, reduced acquisition costs, improved return on investment (ROI), enriched customer onboarding experiences and usage, as well as amplified cross-selling of new products and services. In India, we have been able to create a significant impact for Shoppers Stop through Dynamic Yield.
Can AI guarantee accuracy of data-driven insights?
Absolutely. Our research shows that in 70% of the cases, when consumers buy something, they use an offer from a merchant. In 50% of the cases, they make that buying decision based on the offer that they see. Therefore, merchant offers are very important. But the offers that can be targetted and personalised using AI and data analytics are even more powerful. Since it’s linked to the card, you, as a cardholder, might get a personalised offer based on your spending pattern. In the case of Dynamic Yield, AI and ML are embedded into the platform to improve the accuracy of data-driven insights.
In what ways has Mastercard adopted GenAI to improve customer experience?
At Mastercard, AI is integrated into nearly every aspect of our operations. GenAI is the next evolution and some of our products and solutions, such as Shopping Muse are already in the market, while others are still in the works. Dynamic Yield has lots of deep learning and AI capabilities to test and learn. In October 2023, Mastercard announced the expansion of its consulting business with the launch of new practices dedicated to AI and economics, to help customers across industries rapidly and responsibly advance their use of AI.
What exactly does Shopping Muse bring to the table?
Shopping Muse was introduced in late November 2023. This generative AI tool transforms the way consumers navigate and explore products within a retailer’s digital catalog. Shopping Muse recreates the in-store human experience by translating consumers’ colloquial language into tailored product recommendations, complete with suggestions for coordinating products and accessories. Powered by AI interfaces such as GenAI and visual AI, Shopping Muse acts as a refined digital personal shopper, extending a curated shopping experience to anyone engaging with the retailer
on a website.
How do you see the year ahead panning out?
One of the reasons why Mastercard is in this business is because data and services differentiates payments for us, helping our issuer and merchant partners do more with payments — market, target, innovate. We will continue doing that, leading to diversifying into doing more in retail, commerce, tourism and transit.
