By Team WMB, 23 November 2018
The personalized product recommendation is an issue that awakens the minds of e-merchants by placing the visitor in a central position. The goal is to generate more customer satisfaction and ensure customer loyalty over the long term to improve the profitability of marketing actions.
However, too many brands and e-merchants only partially use the potential of the product listings pages and view them simply as a product aggregate that follows the tree. from the menu by clicking on a category or sub-category.
This article aims to help you better understand and master the mechanisms of recommendation engines. Happy reading!
To date, many online stores are equipped with product recommendation engines using or not using a alogrithm to recommend content in a dedicated location (products, articles, videos or other ... ) and a given context (visitor, type of page, session ...).
For simplicity, it's as if a seller was present in your e-commerce site and allowed you to offer each visitor on each page a bespoke selection of recommendations, such as would do a physical shop seller.
The typology of the products sold on your e-commerce site and your audience strongly determines how the recommendations should be used, whether for the applied merchandising rules or for pre-defined algorithms provided (for example: "Popular products", "Customers who bought also bought", etc.).
Why are recommendations needed for merchant sites?
Because facilitating Internet users' purchases by immersing them in a corresponding product universe significantly improves the customer experience ... and the fundamentals of the site. Indeed:
For simplicity, the technique most used to successfully set up these different functions is called collaborative filtering that uses actions (purchases, cart additions, clicks, navigations, historical ...) users to predict what another user will like. Semantics (content, description ...) can also be included in the recommendation.
To summarize, we have so [shoes, not skirts] then [accessories soles].
Recommendation engines play multiple roles on the pages of an e-commerce site. It is up to the e-merchant to define the most appropriate type of recommendations based on their audience and their clients' journey to optimize the conversion tunnel of their site. Thus the recommended products can fulfill several functions such as:
All pages can accommodate a product recommendation insert with different functions.
Displaying the products produced in your site's recommendations plays a major role in the user experience and has a direct impact on turnover, inventory turnover and the profits you can generate.
As a conscientious e-merchant, you are doing your best to improve the customer experience on your e-commerce site. However, a problem often reappears: how to promote the product discovery?
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