'Improving eCommerce Product Discovery with Recommendation Engines' personalization ecommerce
Recommendation engines can be used to get customers hooked to your platform through a hyper-personalized shopping experience. Around 35% of what consumers purchase on Amazon and 75% what they watch on Netflix come from product recommendations. In this blog, we will deep-dive to understand how recommendation engines can improve product discovery by looking at real-world examples and applications.
Another way of recommending contextual items is by showcasing 'Frequently bought together' items as Amazon demonstrates below: Think of the search icon on your website as an intelligent albeit virtual sales agent--continually suggesting relevant products to customers based on historical browsing, past purchases, and product attributes. Recommendation engines can analyze and record user activity--from understanding product views and previous purchases to adding items to the cart and clicking on bestsellers. The engine recognizes trends across said attributes to deliver a hyper-personalized search experience for the user.
The personalized search functionality boosts user engagement, saves your customer's valuable time, improves user satisfaction, and boosts brand loyalty.Another tried-and-tested strategy to boost product awareness is by rolling out personalized push notifications that encourage users to take the desired course of action:
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