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The success of an e-commerce platform is attributed to the personalized recommendations it provides to its customer. Personalization has become the key to attract and retain a loyal clientele. According to the survey by Everage.Inc., 56% of customers expressed that their return to an e-commerce site is strongly influenced by the personalized product recommendations.

With the advancement of technology, e-commerce gathered momentum spontaneously in the last decade. So has been the marketing trend, which has shifted from conventional marketing strategies to automated AI tools and data analytics. One such crucial tool that is most appreciated by the marketers is the recommendation engine for e-commerce.

Benefits of Product recommendation engine

Creating better user experience: Providing a smooth shopping experience for the user is the key to retain customers and increase e-commerce sales conversion. Providing a personalized experience has been found to have a strong impact on customer retention.

Enhanced customer engagement: Product recommendation engines provide a host of customized options for increasing user behaviour, like a personalized landing page, personalized emails with product catalogue, etc., which in turn enhance customer engagement and improve checkout conversion.

Increased traffic: The product recommendation engine helps in filtering and providing an optimized product array for each user. Improved customer experience and an engaging customer platform help to drive more traffic to the platform.

Rating-based product recommendation: In this tech-savvy world, the customer’s purchase decision heavily depends on user feedback and influencer reviews. Rating and reviews of the filtered product gain more trust and help the user to make a final purchase decision.

Best Practice tips for e-commerce product recommendation

The ‘Recommended for you’ list: It is an effective product recommendation tool to add a personal connection with the customer based on their likes

The ‘Frequently bought together’ recommendation: A suggestion to pair a similar product with a product in the cart based on user experience can increase Average Order Value(AOV).

Personalized product catalogue: Incorporating Personalized product recommendation in personalized emails improves the chance of the user reconsidering to buy a product.

The ‘Recently viewed’ list: This helps the shoppers to explore more about a casually searched product, thus improving the chances of purchase.

Highlighting popular products: Providing additional viewing opportunities for the most valued products can impact the user's purchase decision, as suggested by Pareto’s 80/20 rule of marketing.

Seasonal sales and discounts: Even if the product purchase is not a necessity of the moment, deals and offers increase the interest of the user to check out a product

Purpose of a Recommendation Engine

Personalized product recommendation is the future of e-commerce. Showcasing the best product to the right user in minimum time with a smooth user experience is the key to a successful sales conversion. Installing a product recommendation engine might sound cumbersome, but it is a must to gain visibility and popularity on the retail platform.

Datsy, a reliable and affordable AI-driven product recommendation engine, can help provide end-to-end customer engagements and personalized product recommendations to multiple platforms so that they can ensure a seamless experience for their consumers. Get in touch with us today to learn more!