ServiceTitan‘s patent involves a method using machine learning to predict job values for tenants based on live data. The trained model generates predictions for each job request, updating based on actual outcomes. If unable to predict within a time window, statistics from other job requests are used. GlobalData’s report on ServiceTitan 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 ServiceTitan, Speech recognition techniques was a key innovation area identified from patents. ServiceTitan's grant share as of February 2024 was 67%. Grant share is based on the ratio of number of grants to total number of patents.
Predicting job value using machine learning for service technicians
A recently granted patent (Publication Number: US11900286B2) outlines a method for predicting the value of a job using machine learning models. The method involves training a machine learning model to generate job value predictions associated with a tenant. Live data related to job requests is received, preprocessed to obtain relevant features, and used to generate job value predictions. The model is updated based on actual job values, and if unable to predict a value within a time window, statistics from other job requests are used for prediction.
The system described in the patent includes processors and computer-readable storage containing instructions for receiving live data related to job requests, preprocessing the data, applying a trained machine learning model to generate job value predictions, and updating the model based on actual job values. The method involves training the model using historical datasets, generating training and testing datasets, and retraining the model regularly. Live data includes various identifiers and customer-related information, and the model can predict job values for tasks like installations or repairs. The patent also covers a non-transitory machine-readable storage medium with instructions for performing the described operations, emphasizing the importance of training and updating machine learning models for accurate job value predictions.
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