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Hetaxi
Jun 18, 2024
  332
(4 votes)

Enhancing online shopping through Optimizely's personalized product recommendations

In this blog, I have summarized my experience of using and learning product recommendation feature of Optimizely Personalization Artificial Intelligence Services. The product recommendations are configured under a campaign for different products to display to users. The product recommendation feature is designed to enhance the customer’s online shopping experience for returning visitors by utilizing a new algorithm set by Optimizley. This algorithm intelligently suggest products based on upsell or cross-sells related to previous interactions, popular and new items from favored categories, best sellers, the user’s viewing history, and items linked to past activity. The goal is to provide a personalized and engaging shopping journey, ensuring each recommendation is unique and relevant to the user’s preferences. Product recommendations use machine learning and behavioral data and suggest products according to users likely to be interested in based on earlier page visits, purchases or any other interactions. Below are some key elements of product recommendations block:

  • Personalization - customizing the content and product suggestion based on individual user's preferences and site behaviors to offer engaging experiences.
  • Machine Learning - using advanced algorithms to analyze user's data to display similar product suggestions.
  • Segmentation - classifying and grouping users based on common interests or behaviors to offer similar content and product suggestion.
  • A/B Testing: experimenting different variations of a webpage to decide which page is performing better and can be optimized.
  • Analytics and Reporting: offering detailed insights of user interactions and performance if recommendations of recommendations to retrieve to data-driven decision-making.

Optimizely provides a default "Product recommendation" block as part of the product recommendation package. The developer can customize this block to add required properties, and customize the UI accordingly to match the implementation need. The “Carousel Items” is one of the propety we tailored for one of our client's work. It accept any web products with a maximum limit of three products to maintain a focused display. to add product manually or simply by drag and drop. The added products will be positioned before AI-recommended products, giving content creators control over the product sequence. The manually added products in the product recommendation block are designed to take precedence over AI recommendations, ensuring that they are displayed first and not repeated within the same block. This block is versatile and can be integrated into various pages of a website such as Homepage, Empty Cart Page, Search Results Page, Category Page, and Collections pages.  The  recommendations are based on the widget type selected within the Personalization portal, ensuring that the products displayed are relevant and likely to engage customers. The widget type can be homepage, cart page, search result page, wishlist page etc. 

Optimizley CMS - Personalization Block (Source : internal stag environment)

Homepage of a website - Personalization Block (Source : internal stag environment)

Optimizely's product recommendation is a dynamic and innovative feature designed to enhance the user experience on e-commerce platforms and support business to improve customer engagement, sales, prompt suggestions, and help them complete the purchase. These features work in concert to not only improve customer experience but also to offer valuable data insights for business to take business decision.

With decade of experience in QA profession, I stand at the forefront of software quality assurance. Working at Thinkmax Inc., (Partners with Optimizely) has honed my skills across Optimizley platform to website to ERP system. I bring wealth of experience in QA process improvement related initiatives and implementation, performing test management activities in scrum and hybrid framework. I'd like to invite you to connect with me - Hetaxi Morker in elevating the quality of your upcoming project to new heights of quality excellence.

 

 

 

Jun 18, 2024

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