A method of training a classifier to recognize vehicle vocation using a telematics system, the telematics system comprising a telematics vehicle vocation classifier and benchmarking system, a data management system, and a plurality of vehicles, each including an onboard monitoring device, the telematics vehicle vocation classifier and benchmarking system being in communication with the data management system for accessing historical vehicle data communicated thereto by the monitoring devices for each vehicle and being configured to perform the method comprising: selecting from the historical vehicle data, stored in the data management system, for each vehicle of the plurality of vehicles a series of vehicle usage values over time that correspond to vehicle usage executions, the series of vehicle usage values comprising a series of multiple associated usage values which are independent of vehicle fleet groupings, industry vehicle application groupings and vehicle type groupings, and relate to features of geolocation, two distance, routine, geo neighbourhood, stop duration and customer location, and idling duration and driving duration; organizing the series of vehicle usage values relative to each other to generate at least one vehicle operating usage pattern for each vehicle; determining if the generated at least one vehicle operating usage pattern is representative of a corresponding predominant vehicle behavioral execution pattern that recurs over a period of vehicle operation; extracting data of vehicles having the determined corresponding predominant vehicle behavioral execution pattern and assigning a label to the extracted data corresponding to the determined predominant vehicle behavioral execution pattern; generating training data from the label and the extracted data, and, using at least one machine learning technique with the training data to define a classifier for classifying at least one vehicle vocation parameter for the vehicle independent of vehicle fleet groupings, industry vehicle application groupings and vehicle type groupings. selecting from the historical vehicle data, stored in the data management system, for each vehicle of the plurality of vehicles a series of vehicle usage values over time that correspond to vehicle usage executions, the series of vehicle usage values comprising a series of multiple associated usage values which are independent of vehicle fleet groupings, industry vehicle application groupings and vehicle type groupings, and relate to features of geolocation, two distance, routine, geo neighbourhood, stop duration and customer location, and idling duration and driving duration; organizing the series of vehicle usage values relative to each other to generate at least one vehicle operating usage pattern for each vehicle; determining if the generated at least one vehicle operating usage pattern is representative of a corresponding predominant vehicle behavioral execution pattern that recurs over a period of vehicle operation; extracting data of vehicles having the determined corresponding predominant vehicle behavioral execution pattern and assigning a label to the extracted data corresponding to the determined predominant vehicle behavioral execution pattern; generating training data from the label and the extracted data, and, organizing the series of vehicle usage values relative to each other to generate at least one vehicle operating usage pattern for each vehicle; determining if the generated at least one vehicle operating usage pattern is representative of a corresponding predominant vehicle behavioral execution pattern that recurs over a period of vehicle operation; extracting data of vehicles having the determined corresponding predominant vehicle behavioral execution pattern and assigning a label to the extracted data corresponding to the determined predominant vehicle behavioral execution pattern; generating training data from the label and the extracted data, and, using at least one machine learning technique with the training data to define a classifier for classifying at least one vehicle vocation parameter for the vehicle independent of vehicle fleet groupings, industry vehicle application groupings and vehicle type groupings.