Walmart has patented a system that uses offline transaction data to improve online search results. The system links user’s in-store purchases with online search queries to provide more accurate results. This innovation aims to enhance the online shopping experience for users. GlobalData’s report on Walmart 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 Walmart, Transaction splitting was a key innovation area identified from patents. Walmart's grant share as of February 2024 was 43%. Grant share is based on the ratio of number of grants to total number of patents.
Online search based on offline transaction data
The granted patent (Publication Number: US11928723B2) describes a system that includes a computing device capable of obtaining historical search data and in-store purchase data from different databases. The historical search data consists of search results, associated queries, and users, while the in-store purchase data includes offline transactions associated with the users from the historical search results. The system generates order feedback signals for each offline transaction and trains a search model using a training dataset based on historical search results and order feedback signals. When a query is received, the system implements the search model to generate an online search result, potentially including location information within a physical retail store for relevant items.
Furthermore, the system allows for the association of historical search results and in-store purchase data based on user IDs and item IDs. The user ID can be determined through various means such as a saved credit card or payment app used for offline transactions. The system also considers the time period between the query and offline transaction, with the training dataset including data related to the most recent associated query. Additionally, the system can generate additional online search results based on new queries and update the search model using offline order through rate (OTR) data calculated at the query-item level. The system continuously refines the search model based on updated data and human inputs to improve the accuracy of online search results.
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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.
