Online shopping is clearly not a just fad, and this has been proven amply during the covid pandemic. This phenomenon has revolutionised how people buy everything, from daily use products to foods to even services. It is inevitable to engage in comparisons of the online experience to the traditional shopping experience, and quite frankly, the latter would have managed to trump the former in terms of features, if not for artificial intelligence.

With its potent capabilities, AI makes the online retail experience extremely smooth for the customers. In fact, AI not only makes online shopping as good as offline, it even adds features such as hyper-personalisation that the latter does not afford to its customers. Read on to find out more about how AI is helping online retail.

• Recommendation engine: Online retailers have one distinct advantage over their offline counterparts: they collect numerous data points which can help track shopping behaviour. This perk can be exploited to hyper-personalise the shopping experience by recommending the right products, and therefore, increase the conversion rate. Outfitter is an AI-powered recommendation engine which has helped abof (all about fashion) drive up sales significantly.
• Virtual styling: One common issue with buying fashion items online is inability to try them on and see how they look. This also leads to heavy returns and exchanges. Computer vision and ML. combined, can help simulate the trying room experience virtually. In fact, Bangalore-based retail startup Kiksar Technologies, with the help of AI and AR, provide a 'Virtual Try On' experience for customers beforehand, attempting to hyper personalise shopping and mitigate the scope of returning products.
• Customer support chatbots: AI-enabled chatbots are a vital tool for enhancing the online shopping experience for customers. These chatbots are programmed to fill in for the absence of an actual salesperson by answering customer queries, taking complaints, suggesting products etc.
• Price adjustments: AI-enabled predictive analytics can help the online retailers identify the best time to start decreasing or increasing prices. By monitoring factors such as competitor prices and inventory levels, AI can compare demands to calculate prices. Further, by tracking an individual’s shopping behaviour, it is possible to offer personalised discounts and offers to customers.
• Intelligent search: AI makes it seamless for the online customer to navigate a website and search through product catalogues. Speech recognition enables voice search for e-shopping. Additionally, AI also classifies the products on the website, giving a neat path to the customer to quickly find what they are looking for.

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