Does your favourite brand know who you are? The role of AI in offline retail

I was talking to an ex-client a few weeks ago who launched and scaled one of the biggest and most influential fashion brands in India over the last 15 years. I was curious after so many years, what had really changed in the fashion retail space and what he saw as the major challenges facing fashion brands in the offline space. What he told me was fascinating because in spite of the advance in technology over the last 10-15 years, the problems remain the same.

We still don’t really know who our customer at the retail store is. It’s much easier to track pixels, mobile numbers and cookies online to create a profile for targeting, but if the same person walks into our store, we don’t know it’s him/her.

That got me thinking about my own experiences as a consumer. One of my favorite brands has a dominant on-ground presence in the best commercial shopping areas across India. I realized that despite shopping from the same store several times, the staff didn’t know me at all.  And the staff also kept changing. This is the other problem he mentioned. Indian retail staff is not adequately trained, and they change jobs often. Ergo, I am a stranger to my favourite brand. I know it very intimately, but it doesn’t know me at all.

That got me thinking, can AI make a difference? I spoke to a bunch of tech companies and technologists, and this is what AI can do for offline retail today because while this technology already exists, no one is looking at it seriously.

AI-Powered Customer Identification: The New Frontier

Customer Identification & Real Time Analytics

AI camera-powered screens with built-in analytics engines can scan every customer walking in and identify by gait recognition, body composition, height and weight the demographic of this customer. Male/Female, approximate age, etc, it can even identify the clothes the customer is wearing and the AI-powered engine can then display clothing that is relevant to this customer.

When you combine this with existing in-app loyalty programs, a simple tap on the screen by the customer gives the AI engine permission to recommend even more relevant clothing and accessories based on previous purchases.

Because the system is location and weather aware, it can suggest season appropriate merchandise.

These systems can connect in-store visits to customer profiles, reward loyal patrons, and detect shoplifting or suspicious behaviour. In privacy-conscious India, such solutions are deployed with consent or in combination with opt-in loyalty programs. And most of these are fully GDPR compliant.

Unified Customer Profiles: AI platforms now integrate data from multiple touchpoints - including mobile apps, SMS, loyalty cards, and Point-of-Sale (POS) systems. This unified approach lets brands identify customers across channels, even if the initial interaction was offline. Large retail chains are already leveraging these unified profiles to serve targeted recommendations, regardless of whether customers are in-store or browsing online. If this can be overlaid with media and POS data, this could be a game changer to create a truly unified customer profile.

AI-Enhanced Loyalty and Rewards Programs: Instead of one-size-fits-all discounts, AI can segment customers based on purchase history, visit frequency, and style preferences. The brand can then send personalized offers via WhatsApp or SMS to create a sale when the customer is not even looking to buy. After all, most people find a customized offer very irresistible.

Driving Larger Ticket Sizes: From Personalisation to Impulse

Hyper-Personalized Recommendations: Indian platforms like Myntra and Reliance Retail use AI algorithms to recommend ensemble suggestions, cross-sell accessories, and suggest bundling offers—mirroring the ‘frequently bought together’ experience of online fashion. These tactics encourage customers to try and buy more during a single visit.

Dynamic Pricing and Offers: AI enables real-time pricing tweaks based on demand, inventory, and individual shopping behaviour. For instance, a loyal shopper might receive an exclusive in-store discount on a high-margin item if their profile and purchase history suggest potential for higher spend. Combine this with dynamic DOH on the store front or in high traffic areas and this could lead to incremental sales.

This might mean featuring a trending kurta style in Mumbai and fusion wear in Bengaluru, based on regional AI-powered demand forecasting. Localised assortments and smart curation can lead to higher conversion rates and larger transactions.

Looking Ahead

As AI becomes embedded in every aspect of Indian fashion retail, the line between online and offline will continue to blur. The future belongs to those retailers who can use AI to not only identify their customers but also anticipate their needs and delight them, often before they even realize what they want.

AI isn’t just about technology, it’s about reimagining the entire customer journey, building deeper relationships, and creating experiences that naturally drive higher basket sizes and enduring loyalty. The revolution is happening now, and the smartest retailers are not waiting on the sidelines.

Disclaimer: The views expressed here are solely those of the author and do not in any way represent the views of exchange4media.com.