DoorDash had one patents in big data during Q2 2024. DoorDash Inc’s patents filed in Q2 2024 focus on reducing variance in target metrics by using historical data to predict future outcomes, which are then used as covariates. An automation pipeline is utilized to generate accurate and timely forecasts, and optimal coefficients for each covariate are determined using a closed form solution. GlobalData’s report on DoorDash gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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DoorDash had no grants in big data as a theme in Q2 2024.
Recent Patents
Application: Software version control using forecasts as covariate for experiment variance reduction (Patent ID: US20240211250A1)
The patent filed by DoorDash Inc. describes a method to reduce variance in a target metric by using historical pre-experiment outcomes to predict future outcomes, which are then used as covariates. The method involves providing different versions of a software application, measuring performance metrics for different client categories, predicting future performance metrics, and comparing the versions based on an auxiliary metric derived from the predicted and actual values. The process includes using time series models, data preprocessing, and regression to determine predicted values and auxiliary metrics for comparison.
The method outlined in the patent involves a systematic approach to improving software applications by predicting and comparing performance metrics across different client categories. By utilizing historical data and time series models, the method aims to reduce variance in target metrics and determine the effectiveness of software updates. The comparison process involves determining control and treatment distributions based on the auxiliary metric, ultimately leading to the deployment of the version that provides better performance. Overall, the patent presents a structured methodology for optimizing software functionality based on predictive analytics and performance comparisons.
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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.
