With millions of listings uploaded daily, manually tagging, classifying, and updating product information has become an operational bottleneck, writes Sameer Kanodia, Managing Director and CEO, Lumina Datamatics Limited, & Vice Chairman & CEO, TNQ Tech
Every day, over 270 million Indians shop online, making the country the second-largest e-retail market globally with a GMV of nearly $60 billion in 2024. Yet, despite this vast scale, many consumers abandon their searches due to cluttered interfaces, irrelevant recommendations, or difficulty in finding the right product. Bounce rates in high-SKU categories often exceed 40%, highlighting a pressing challenge for retailers of how to match the right product with the right customer at the right time.[1] Increasingly, the answer lies in Artificial Intelligence, which is transforming product discovery in Indian e-commerce.
AI-driven catalog management tools are at the forefront of this transformation. With millions of listings uploaded daily, manually tagging, classifying, and updating product information has become an operational bottleneck. Intelligent auto-classification systems now analyse product attributes and automatically categorize items based on specifications, features, and intended usage. This not only reduces the risk of human error but also ensures that products appear in the right search results and category listings, streamlining the shopper’s journey from discovery to purchase.
Complementing auto-classification, advanced image tagging technologies are enabling retailers to leverage visual data more effectively. Every product image uploaded to a platform can be analyzed by AI to detect colors, patterns, textures, and even contextual details such as environment or usage. This metadata is then used to enhance search functionality, allowing consumers to search visually or receive recommendations based on visual similarity. For example, a customer seeking a mustard-colored shirt or a compact kitchen mixer can be guided to the most relevant products without relying solely on keyword searches, improving both precision and speed in product discovery.
Smart metadata generation is another game-changer in this scenario. AI algorithms examine product descriptions, specifications, and user-generated content such as reviews to generate additional metadata that enriches each listing. This allows products to surface in unexpected but relevant search contexts, improving discoverability across diverse customer segments. For instance, a multipurpose fitness tracker may appear not only under electronics but also under health, sports, or lifestyle searches, thereby widening its reach without additional manual effort.
The benefits of AI-led product discovery extend beyond search accuracy. Retailers utilizing these technologies report measurable improvements in user engagement and conversion rates. Enhanced search results reduce bounce rates, as customers are more likely to find what they are looking for on the first attempt. Personalization engines, fueled by AI, can also prioritize listings based on a shopper’s browsing history, past purchases, and demographic insights, ensuring that every interaction feels tailored and relevant. In a market as diverse as India, where consumer preferences vary widely across regions, this level of personalization is critical for driving loyalty and repeat purchases.
Moreover, AI-driven systems simplify large-scale catalog management, which is essential for retailers managing tens of thousands of SKUs across multiple categories. Automated processes reduce operational overhead, allowing merchandising teams to focus on strategic decisions rather than manual data entry. Real-time updates ensure that products with stock changes, pricing adjustments, or promotional offers are immediately reflected on digital storefronts, maintaining a seamless shopping experience. This agility is particularly valuable during peak seasons or festive sales, when product volumes spike and consumer expectations for accuracy and convenience are at their highest.
The integration of AI into product discovery is also opening doors for more immersive shopping experiences. Conversational AI and intelligent virtual assistants can guide customers through complex choices, asking targeted questions to refine search results and recommend complementary items. Visual search features enable users to upload images and find similar products in seconds, bridging the gap between offline inspiration and online fulfillment. These capabilities not only enhance user satisfaction but also strengthen the retailer’s brand as a technologically advanced and consumer-centric player.
Looking ahead, the evolution of AI in product discovery is set to accelerate with innovations like multimodal search, where text, image, and voice queries seamlessly converge, and predictive algorithms anticipate consumer needs based on patterns, seasonality, and lifestyle trends. In India’s rapidly expanding e-commerce ecosystem, where digital literacy and smartphone penetration continue to rise, these advancements will play a defining role in shaping retail engagement.
For retailers, the focus goes beyond operational efficiency to building more spontaneous, responsive, and personalized shopping voyages. Reducing bounce rates, improving search accuracy, and simplifying catalog management are only the starting points; the true objective is to inspire consumers to discover products effortlessly, enjoy smooth interactions, and make confident purchasing decisions. By harnessing AI in product discovery, Indian retailers are not only streamlining digital storefronts but also setting a new benchmark for customer experience in an intensely competitive market.
“As the e-retail landscape evolves, AI will be the catalyst that empowers retailers to move from transactions to true connections with consumers.”
