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sharminaktersss3435
Apr 09, 2022
In Development Forum
In this article, we take a look at how recommender systems can provide a more personalized and powerful e-commerce experience for your website users. Users love it when companies can re-guess their minds. In an ideal world, our favorite food chains would create weekly shopping lists for us. A fashion brand sent us a curated list of new clothing items to complement our current wardrobe. We don't need to expend much effort to get the necessities we need. Brands use machine learning (ML) and AI to do most of the work for us. While we are not yet at this stage of the predictive shopping experience, machine learning techniques have become increasingly accessible—whether as plug-in solutions or custom algorithms. Recommender systems are the new favorites of e-commerce companies in particular. Why? As the next four use cases demonstrate, the post-adoption benefits are enormous. 1. Personalized Marketing Pressed for time and always on the go, modern consumers do a lot of industry mailing list across multiple devices, rather than taking the time to run an outright shopping marathon (unless, of course, it's the holidays!). Brands that offer fast, immediate delivery reap the most benefit. According to a personalized consumer survey conducted by MyBuys, 48% of consumers spend more on e-commerce companies that offer a personalized shopping experience. ML systems allow you to capture data from past and current shopping sessions and convert it into dynamic offers. For example, you can present unique versions of your store's homepage to different groups of customers. New visitors can see your bestsellers first. Regular shoppers can be directed to new offers or personalized discounts. You can showcase better cross-sell and upsell offers at different stages of a user’s buying journey to increase average basket size and increase conversions. On average, intelligent recommendation systems can increase the conversion rate of online products by 22.66%. Additionally, ML can determine which inventory to display (other than the best-selling ones). Smart recommendation systems can scan your entire product catalog and rank the best products for individual buyers. You can go a step further and display the nearest store locations that offer the collection. Or capture browsing data and target potential customers with local inventory ads later in the day.
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