Overstock has been granted a patent for a system that provides personalized product recommendations to online visitors of an e-commerce website. The system uses a processor to sort a list of products based on a comparison of a user’s interactions with the website and previous user interactions. The system also tracks user interactions, generates a list of interactions specific to the target user, compares it with previous users’ interactions, and re-orders the search results list to provide personalized recommendations. GlobalData’s report on Overstock gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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According to GlobalData’s company profile on Overstock, personalized content delivery was a key innovation area identified from patents. Overstock's grant share as of June 2023 was 1%. Grant share is based on the ratio of number of grants to total number of patents.

Personalized product recommendations for e-commerce websites

Source: United States Patent and Trademark Office (USPTO). Credit: Overstock.com Inc

A recently granted patent (Publication Number: US11676192B1) describes a system and method for personalizing search results on an e-commerce website to provide targeted product recommendations to users. The system includes a processor, memory, and user devices connected to a server through an electronic communication network. The server tracks user interactions with the e-commerce website, storing information about user actions such as product refinements, related products viewed, navigation paths, previous promotions, product attributes, profile information, purchases, and pricing.

The system generates a list of interactions specific to a target user by using the stored information about the user. It then compares the target user's interactions with those of previous users to determine a subset of previous users with similar interactions. The server receives an ordered list of products from a search engine in response to a search query by the target user. The target user's interactions are matched with the subset of previous users' interactions to generate a subset of matched interactions, which are used to reorder the list of products based on their rank among the matched interactions. The sorted product list, specific to the target user and based on the matched previous user interactions, is then displayed on the user's device instead of the original ordered list.

The method described in the patent involves presenting an interface generated by the e-commerce website on user devices, tracking user interactions with the website, generating a list of target user interactions, comparing them with previous users' interactions, receiving an ordered list of products from a search engine, matching the target user's interactions with the subset of previous users' interactions, reordering the list of products based on the matched interactions, and displaying the sorted product list on the user's device.

Overall, this patent aims to improve the personalization of search results on e-commerce websites by leveraging user interactions and matching them with similar previous interactions to provide targeted product recommendations. By reordering the search results based on these matched interactions, the system aims to enhance the user experience and increase the likelihood of finding relevant products.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.