Many of the eCommerce players such as Macy's, Amazon and Flipkart compete with each other, establishing niche technologies and customizing every nuance of the customer experience to improve revenue generation and stay ahead of other players in the market. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original Essay Machine learning, an application of artificial intelligence, is a technique recently adopted by e-commerce operators, to help improve customers' shopping experience and make it more efficient and engaging. Below are some of the areas where ML can help improve revenue for eCommerce operators. ML helps define pricing policies based on customer price sensitivity and product demand. In detail, ML tracks every movement of the entire customer experience: what the customer searches for, the frequency of their visits, purchasing patterns, browsing pages, cart items, recent purchases, geography of the customer, etc. and provides insights into price position, cart abandonment rate, competitor data, historical pricing, revenue generated, etc. This analysis can help companies reposition their pricing policies, recover lost sales, increase conversions and generate high profits. MI uses techniques such as marketing mix, share of wallet (amount of business a company gets from specific customers), bundling (offering two or more complementary goods as a bundle), etc. to identify potential customers and increase the value of the product. acquire. These techniques allow companies to suggest purchasing recommendations for online shoppers, personalize promotions for repeat customers, and enable seasonal demand offers and cross-selling to targeted audiences. Companies use promotions, offers and deals to achieve the right balance between sales volume and profit percentage. Optimal inventory management is one of the key factors in managing revenue effectively. Based on past customer transactions, ML can identify on-demand products and supply chain processes. When the entire supply chain is accurately tracked from order to delivery, ML can suggest optimal sourcing policies to stock profitable, high-performing products and avoid stockpiling low-value products. ML also suggests assorted products (mix of merchandise suited to customers), alerts on replenishment status (to avoid out-of-stock conditions) and helps deal with cancellation tasks. Please note: this is just an example. Get a custom paper from our expert writers now. Get a Custom Essay For successful product launches, it is essential for businesses to understand their market segments and target audiences. ML offers 360-degree analysis of market size, product reach within the segment, customer accessibility, homogeneity in terms of preferences and characteristics, quantified results for product launches within the segment in recent times. This in-depth research adds value to decisions along with insights from competitive analysis, proprietary analytics, promotion channels and niche audiences.