Searched for a veterinarian in your area and now your social feed has been taken over by ads for pet products? Through machine learning, etailers can discover dynamic patterns in customer habits and provide bespoke shopping experiences. With the power of Machine Learning, etailers can now even predict customer choices even before the customer knows about their requirement. This article in Rudradeb Mitra covers in detail how Machine Learning can be used in predicting buyer behaviour (link). Thinking about buying pet food and suddenly pet food advertisements are all around you? -- well, it's not sorcery.

What will AI's role be during this busiest of all seasons? The holiday season means many things to many people; to retailers and e-tailers, it means things are about to get crazy busy. This is true no matter when the shopping season begins. In the US for example, it traditionally stretches from Thanksgiving to just after the New Year; in India, it runs from mid-August to January. Retailers of all sorts are already adapting their approach by timing sales and tying them into holidays or other festive events.

NEW DELHI: Startups like SnapShopr, Staqu Technologies, Wazzat Labs, MadStreetDen and iLenze are experimenting with deep learning and image search technologies focused on powering fashion e-tailers to simplify catalogue search, drive customer engagement and get higher conversions. "Two big trends prompted us to start-up -increasing number of smartphones has eased access to smart cameras, which has triggered increased image-based content on the internet. Secondly, we realised that businesses would increasingly need deep learning technologies to understand and analyse visual content to gain valuable insights - which can be the difference between success and failure now," said Ankit Sachan, cofounder of iLenze, which raised 500,000 from Singapore based Mercatus Capital. The technology is inbuilt within the etailer's application and helps connect product discovery in the offline world like reading a magazine or on the street to online searches of similar products on ecommerce websites. By making it easier and more efficient for consumers to scan the etailer's catalogue, the tech increases engagement and thus higher conversion rates and transactions.