Gusto‘s patented central database system utilizes machine learning and clustering to predict a user’s next web page visit based on past behavior. By tracking user activity and characteristics, the system guides users to recommended pages, enhancing web navigation experience. GlobalData’s report on Gusto gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Gusto, Social media analytics was a key innovation area identified from patents. Gusto's grant share as of January 2024 was 68%. Grant share is based on the ratio of number of grants to total number of patents.

Predictive web navigation using machine learning and clustering

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

A recently granted patent (Publication Number: US11863641B1) outlines a method involving a central database system tracking the number and order of web pages viewed by multiple users within a domain. The system then generates a training data set based on this information and user characteristics, subsequently training a machine-learned model to predict the next web page a user is likely to view. By identifying characteristics of a target user and their browsing history, the system can accurately predict the next web page the user will visit by applying the machine-learned model.

Furthermore, the patent details the process of generating feature vectors, labeling them with next web pages in the order of user visits, and utilizing session context data and web markup to enhance the training data set. The system also incorporates a mechanism to track user behavior, adjust predictions based on observed outcomes, and strengthen or weaken associations between web pages viewed and predicted next pages. Additionally, the patent includes provisions for determining transitions between web pages viewed by a target user and assigning weights to different subsets of web pages based on keyword presence and user engagement metrics, ultimately improving the accuracy of predictions made by the machine-learned model.

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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.