How Can AI Help E-Commerce In The Festive Season?
The biggest shopping season of the year is around the corner. The festive season, beginning in mid-August with Independence Day and ending in January with some harvest, is a period that usually sees higher sales of all types of goods. E-commerce sites typically see sales figures almost doubling up in this period (According to a recent report, Flipkart is targeting four times the sale of competition and Amazon is aiming to cross 100% annual growth rate from the India sales). With a string of festivals lined up, this period is often considered auspicious for making purchases. The festive season sales are more like the moments of reckoning for India’s online shopping websites. In last few years, e-commerce players such as Amazon, Flipkart, Snapdeal, Shopclues, Paytm etc have taken the idea of shopping around festivals to a new level. They organize large-scale sales that attract consumers from every part of the country (like the Big Billion Days, The Great Indian Shopping festival, Maha Bharath Diwali Sale etc) Brands across categories partner with these e-commerce players and offer deals to the consumers making the extravaganza even bigger. In a fight to steer ahead in the race, how nice it would be for the e-tailers to have technology as their biggest advantage? Artificial Intelligence has the power to change the entire ballgame and we know it. Behind the scenes, from the warehouses to the websites, AI can play a huge role in automating processes. Understand and process voice queries, recommend products based on a person’s buying history, or forecast demand- AI could do it all. And that’s not all, AI could do even more: Product identification and search: AI programs can be used for image search or video search which enables the engine to study a particular image (say, a man wearing a turtleneck linen pink shirt) and offer a recommendation for similar products (shirts). The scope of the visual search can be expanded and complemented with suggestive and voice-activated shopping. Eventually, this mechanism will lead to customization of shopping experience such that the AI program will start identifying the products kept in cart and process page/sections browsing based on customers’ past shopping data and other data from various sources, making the suggestions more accurate with time. Personalization: AI systems allow deep dive into customer preferences and sentiments, understanding their spending patterns and recommend products they are likely to purchase. This works very well for personalization, personalize the offers and products to match customer preferences and filters, make it more in numbers and value. This ultimately ensures customer satisfaction and achieving sales targets. Customer service: E-commerce brands can take in AI advancements such as Virtual Personal Assistants or chatbots for enhancing customer-brand interactions. Technology giants like Google and Amazon are doing extensive research on artificial intelligence and exploring the possibilities of conversational bots. They are trying to chalk out a mechanism where a machine can learn from the conversation between a customer and customer care executives. And the responses get evolved and personalized for each query, complaints, product information etc. For example, the Indian e-commerce company Flipkart is working on AI algorithms that will create a more personal, conversation-based shopping experience for their customers. Fashion assistant: The next stage for AI and ML could be when a customer wants to go on a trip or holiday, the smart chatbot would suggest a list of the things to take along. Or maybe a customer is not able to choose the right clothes to wear on any occasion. The chatbot can suggest the right dress and complement it with footwear and accessories like a fashion assistant/advisor. Let, for example, a customer can be offered virtual trial, say a customer tries an outfit virtually and the chatbot may suggest buying that product, like a friend (as an influencer). Demand forecasting: AI will also help to improve the overall sales performance, Amazon used predictive analytics to know beforehand and estimate for the products in high demand (based on preferences) and keep it in stock (avoid stock out situation) and plan for inventory accordingly during its Prime day. This application can be picked up by the other Etailers for forecasting future product demand and managing warehouse stock levels. Automating operations: AI can be used anywhere to automate operations like order receiving and processing without any human intervention. Amazon is automating wherever it can, right from the point of using robots for warehouse management to delivery at doorsteps through drones. Flipkart is also using AI to predict sales and streamline the ordering and delivery process. Without a doubt, AI is changing the face of e-commerce for the better through its intelligent systems. The customers would be offered tailored solutions. With adopting to these systems at the right time and right skills, infrastructure and investments, AI is poised to offer benefits to e-tailers like revenue enhancement, increased margins and sales success.
The biggest shopping season of the year is around the corner. The festive season, beginning in mid-August with Independence Day and ending in January with some harvest, is a period that usually sees higher sales of all types of goods. E-commerce sites typically see sales figures almost doubling up in this period (According to a […]
In a fight to steer ahead in the race, how nice it would be for the e-tailers to have technology as their biggest advantage?
["AI (Artificial Intelligence)", "Amazon", "ecommerce", "Flipkart", "Online shopping"]
["Go", "artificial intelligence", "AI", "chatbots", "R", "ML", "Flipkart", "Amazon", "Online shopping", "Aim", "ecommerce", "analytics", "GAN", "predictive analytics", "AI (Artificial Intelligence)"]
["AI", "artificial intelligence", "ML", "analytics", "Aim", "chatbots", "predictive analytics", "R", "Go", "GAN"]
Suhale Kapoor is the Co-founder and Executive Vice-President of Absolutdata Analtyics. He is currently involved across functions at Absolutdata including Finance, Technology and Business Development. He has about 17 years of experience in operations, marketing, logistics and information management systems.