AI in Retail – Techstrong AI Podcast EP40

Hello and welcome to the Techstrong AI Podcast. I'm Amanda Ani, and with me today is Serena Rajani. He is the Senior Vice President and sector head of Consumer and life Sciences at Wipro.

How are you doing? Delighted to be here. Hi Amanda.

How are you? Glad you're here. Doing well.

So can you share a little bit about Wipro? What services do you provide? Certainly.

8 billion New York stock exchange listed company with a suite of services that extends across applications, artificial intelligence, business processes, cloud consulting, cybersecurity, data analytics, digital experiences, engineering and sustainability. Wonderful. Well, we have our topic of the day, which is AI in retail.

So I wanna get down to it. Um, I know unstructured data is a real difficult issue amongst companies, how to harness all that data, especially in real time. So can you share from your experience, what are you hearing from business leaders as far as their struggles with this?

Great question, Amanda. What we are observing is the consumer expectations are evolving from nice to have demands to essential experiences, omnichannel, conveniences, personalizations, any positive in-store experience, uh, which is not no longer just a nice to have, it's a must have. And consumer retention rates are as high as 89% for those retailers with strong omnichannel strategies.

63% of consumers say that a positive in-store experience will make them more likely to buy from them online, and 80% look for tailored experiences. So clearly for a lot of consumers having to make sense of this data that they actually share, uh, with a lot of the retailers and the retailers actually making sense of it and having customized experiences, those are becoming very critical. A lot of it is unstructured, and the quicker that we can actually bring it all together makes for a more meaningful relationship between the retailer and its consumer.

So what makes it so hard to, to harness that unstructured data specifically, and what advice do you have for company leaders? A lot of this unstructured data is actually stored in different places in different formats. Uh, there are certain rules and regulations about using some of these things.

What do we do to bring in actually a unified approach to bring this all together? That's the critical angle, right? Uh, whether it's around range of products, assortment of products, pricing of products, campaigns.

Can you do a seamless product discovery for the client? Can you do a 360 degree personalization for the client based on the data that you have? And they allow you to use smart returns, post-purchase insights.

These are all meaningful experiences that could be created, but it's not that easy because you gotta bring a lot of this together and actually make sense out of it. And that's the critical angle here. So we're hearing a lot about ai, it's advancing rapidly over the last two years.

AI promises to solve so many issues. How can AI be harnessed in this instance? That's a very good question.

In fact, AI could be used for a variety of parts of the retail experience and the store experience. And what we have observed is it could start with something as simple as, say a self-checkout, a kiosk customer assistant to interact with a customers in a spoken language. Suppose they're traveling to an airport where they don't understand a local language.

Could I use AI for that? And it could actually reduce the in-person interaction on product information answer related to any questions, issue resolution, uh, empathetic query resolution for the stressed consumers of today, or it could be a quicker way in which they check out from the store. In fact, one of the things that we have also observed is consumer behavior insights and providing, uh, actually reducing customer churn because of this, providing best offer analytics, uh, these are all reducing to, you know, the customer churn.

Uh, we are also providing, in fact, what we are observing is experience design, advisory implementation, managed services to help retailers enable a seamless omni-channel personalized customer experience by blending capabilities across marketing, commerce, and customer experience. And so AI definitely helps with that customer experience. Is there a way to use AI to help with harnessing and capturing all the data and sorting through it?

Absolutely. In fact, a lot of that data right now resides in different places. But if I could bring them all together and, and I'll give you some examples.

Uh, we have actually designed a unified customer intelligence and contextual experience that integrates customer data silos from multiple touchpoint. And it could be first party data, third party data. Can you derive an insight of shopping preference and build customer intelligence and deliver, I would almost say a hyper contextualized experience to lift your conversion rates and to drive loyalty?

These are two important things on which a lot of retailers actually scale, which is can I convert them quickly, uh, rather than have shopping carts that are left abandoned? Can I drive loyalty? Can I bring them back to my store or my website on a consistent basis?

And these are some of the things that we're observing are some of the outcomes that are being driven through ai. We hear a lot about intelligent AI chat bots helping with customer issues. How close are we to just letting those chat bots run free and um, not needing any oversight?

That's a very good question. Uh, I would say we made progress, but we are not at the perfect stage where a chat bot can actually be running on itself. This definitely human oversight involved here.

Uh, we have seen, for example, can I do a customer data platform and provide a fairly rich interaction with a client over a chat bot? Can I have the chat bot measure and manage these relationships? And they may be able to answer some standard questions, but sometimes I'm also observing some of the questions might be non-standard.

Some of them questions might be related to inventory that you may or may not have. So how do I connect a lot of these systems and are able to provide information As long as the chatbot is able to provide an empathetic, uh, back and forth with that client where they feel like they've been listened to and uh, they're getting what they're asking for, they're more likely to come back. But I don't think we are full.

I think the utopian concept of a chatbot actually replacing a, a human being fully, I don't think they're there yet. So when it comes to implementing new AI technologies in a company, what are some of the struggles that companies have and what advice do you have for them? So one thing that we are observing, for example, in gene ai, uh, can you use gene AI to enrich a product attribute?

And can you generate a smarter product description from external sources? And it could be from a marketplace, it could be from social media. And can you enable a single view of the product across the enterprise that can power a consistent and impactful product and content experience across all digital touchpoints?

Easier said than done. We have seen in some places this also leads to a higher conversion. The other one is commerce modernization.

Um, can a retail retailer modernize their legacy commerce solution via a microservice or a cloud enablement? That's another thing that we are seeing If that can scale, that's another thing which I believe is clearly the future that a lot of companies are looking at. Uh, we are working with actually a, a retail, a US electronics retailer.

And this has actually powered their digital revenue growth. But I think there's a lot of headroom for growth here. So this may be really far out in the future, but I envision a a time where we can go online and we can have an AI shopping assistant that's helping us pick out things and we can just use our voices to talk to this AI assistant and say, do you have it in red?

Do you have it in green? Okay, put that in the cart in this size. Do you think, how far out do you think something like that is?

And are retailers looking at that type of technology? Actually they are. Amanda, that's a really good insight.

You will actually observe that it's not that far away. We actually have retailers that might have customers walk into their showrooms and experience their clothes real time. Could be, for example, have them turn the, you know, put these clothes on through a virtual virtual, try-on and decide that, you know what, instead of the blue top, can I do it in a rec top?

How does that look for me for a party that I have this evening? And the mirror gives you the information that you need via your phone or any way you're interacting with it. And that's ai ML accelerators that we are seeing.

And these are committed investments that we can see companies making. We are working with some of our clients on some of these things, and these are, if you ask me, these are retail solutions that drive a higher conversion. They also bring in a higher lifetime value through enhanced experiences.

And there are also cost advantages to this because, uh, it's smart, it's responsive, and these virtual assistants actually help you deliver or discover chic uh, trends, uh, that store associates can actually, you know, work with them to take it to the next level. It can help you from a smart store sourcing standpoint. So for example, if a store is selling goods of a certain type size, uh, color or variety, they can actually order those rather than have goods that are sitting on the store shelf and getting wasted.

So there are a lot of AI ML accelerators that we use, um, which are actually powered through any of the new technologies that we have through ar vr, to, to make this, uh, real for our clients and, and not that far in the future. That's really cool. All right, well if there was one key takeaway you could leave our audience with today, what would that be?

I think the future is here. Um, we are looking at autonomous checkout experiences where you, where you are working with a retail store assistant is actually your checkout point and you actually already see this in some stores. Can I step in and step out of the store without having to interact with a, an a buyer assistant?

Can I for example, have equal experiences online store experiences? And there's actually a connect between made between both those visits by the retailer. Uh, these are all stuff that we are seeing from a AI infused strategy.

Uh, this is leading to business transformation and we are seeing that AI is actually unlocking a huge amount of business value across the retail value chain. Uh, and it could be, it could lead to revenue uplifts across online and stores. It could improve, uh, customer loyalty and most importantly, it'll also lead to an efficient retail operation, uh, thereby reducing the cost to serve.

So, so clearly we are seeing a whole lot of these things happening in fairly short order and we are seeing this globally, so it's not just stateside or in Europe, you're actually seeing this in Asia. So you're actually seeing a consistent experience across brands across different countries. So, which is pretty unique.

Uh, earlier it used to have these disjointed experience across stores in different locations. Now you're actually seeing a consistent experience that's coming across. That's amazing.

Alright, well thank you so much for coming on our show and sharing your insights with us today. It's a pleasure to be with you, man. Thank you so much.

Thank you. And thank you to our audience. Stay tuned.

There's more.