eBay had 105 patents in ecommerce during Q4 2023. eBay Inc filed patents in Q4 2023 for technologies such as using machine learning to improve transaction conversion probabilities, distributing information at variable rates, controlling feature testing through experimentation platforms, identifying products in an electronic marketplace through visual comparison, and implementing a trusted fulfillment agent network system for online marketplace transactions. GlobalData’s report on eBay gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
eBay grant share with ecommerce as a theme is 54% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Dynamic transaction system using counterfactual machine-learning analysis (Patent ID: US20230419396A1)
The patent filed by eBay Inc. describes systems and methods that utilize counterfactual machine-learning analysis to enhance the probability of transaction conversion. The system trains a model using data from previous transactions to determine the likelihood of transaction conversion based on user account behavior. By monitoring user actions related to a potential purchase, such as interactions with a listing, user and item attributes are identified to calculate the conversion probability. If the probability falls below a set threshold, counterfactual analysis is conducted to pinpoint changes to the item that would increase the probability, which can then be automatically implemented without human intervention.
The method outlined in the patent involves tracking user behavior, determining probabilities for transaction conversion, and performing counterfactual analysis to optimize the likelihood of conversion. By adjusting attributes associated with the item based on user actions, such as displaying a cart interface or offering discounts, the system aims to increase the chances of completing a transaction. Additionally, the patent covers scenarios where adjustments are made dynamically, such as altering costs, providing incentives, or displaying upgraded options, all with the goal of improving the conversion rate. The system also includes provisions for retraining the model with new transaction data and utilizes a long short-term memory model to incorporate user behavior leading up to the current action.
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