Have you ever wanted to push your favorite items from the cart to “Buy now” during festive sales when great deals are offered? But have you ever stopped to think how much of that excitement was truly yours, and how much was subtly crafted by marketing strategies or even AI-driven algorithms? Shiprocket, one of India’s top eCommerce enablement platforms, recently shared insights on e-commerce growth during the festive season, highlighting the role of AI-driven recommendations and social media influencers. According to the report, 84% of consumers in the fashion and beauty categories made purchases influenced by promotions or influencer suggestions. In an exclusive conversation with Praful Poddar, the chief product officer at Shiprocket, we discussed how AI has evolved in shaping purchasing decisions. Poddar noted that while in 2010, online shopping platforms used simple logic to show “similar products,” this approach has advanced over the years. Initially, product recommendations were generated through basic rules and Excel sheet-based logic, where items were mapped based on historical data. Today, machine learning algorithms consider multiple parameters, offering more personalized suggestions. In recent years, machine learning has become mainstream, allowing platforms to analyze vast amounts of data in real-time. Poddar explained that generative AI has further transformed the process by predicting user behavior without the need for manually inputting parameters. Aakash Anand, the co-founder of Unikon.ai, shared that their AI/ML-based peer-to-peer networking platform is leveraging recommendation algorithms to personalize users’ journeys on the platform. They have also integrated semantic search, which understands the context of the query and responds accordingly. For sellers, Shiprocket focuses on two main areas when it comes to using AI in their platform: enhancing the buyer experience and helping small and medium businesses (SMBs) operate more efficiently. They use data from event streams, such as browsing behavior, filters used, and items added to carts, to create buyer personas and improve personalization. The platform’s network effect also helps create larger buyer cohorts, enabling more targeted recommendations across its 2,000 websites. On the buyer-facing side, the company uses AI to enhance the experience on its tracking page and MyShipRocket app, offering more personalized information than standard courier tracking services. This improves the overall user experience, making the process more tailored to individual preferences. In the broader e-commerce industry, AI and ML are integrated into multiple areas, enhancing both operational efficiency and customer experience. Major players have leveraged AI to optimize cross-category searches, boost impulse purchases, and improve profitability. For example, Wayfair, a Boston-based e-commerce company, uses AI to personalize product recommendations and optimize pricing strategies. As AI continues to evolve and become more mainstream, it will play a crucial role in shaping the future of e-commerce, making the shopping experience more personalized and efficient for both buyers and sellers.
