You can export Insights into your favorite BI tool.
The “Export” button at the top right corner of the Insights page produces a CSV file, created in response to the selection of App Users, Trips, Geofences, Geotags, region, or device metadata. Learn more about working with device and profile metadata.
Location and marker data
The Insights view allows operations teams to download a CSV file and share across your organization. While this allows the ops team to use location data without engineering help, some use cases need more detailed data.
HyperTrack’s data export API gives you all the insights data plus the data the insights view is based on—locations and marker data for geotags, trips, geofences, and device status (activity and outages)—to be consumed by data and engineering teams.
To get the data, call our history API:
The API call returns a pre-signed URL that you can easily download. Here is a full shell example using jq:
Note the link is pre-signed and will expire after 60min. Once you downloaded the file, use your favorite gzip tool (e.g., gunzip) or library (e.g., python gzip) to decompress to get the full json file.
The returned json file contains an array of devices, which each entry given you details about the device. Here is a sample in pseudo json (with comments added for clarity):
The json file contains a json array, with each item representing one user in the insights view. Each user contains the following fields:
|rating||Overall tracking score of this app user. This is computed using tracking percentage, and behavior for trips, geotags and geofences. A 5-star rating means the user performed perfectly as expected. Use this to measure productivity and reward top performers.|
|device_name||App user name|
|device_id||Device Identifier that uniquely identifies a device within HyperTrack|
|tracking_percentage||Percentage of the time when device was tracked, relative to the time you intended to track the device that day. Disabling permissions for example would reduce the percentage. Use this to review devices that did not track as intended, understand the reasons why, and take corrective action.|
|custom custom_marker_count||Number of app events resulting in geotags. The number of markers typically correspond to your orders, and depends on your use case and implementation. Use this to review how much work was done by each user.|
|custom_marker_mean_distance||Arithmetic mean of distance between geotags. A higher number means there was a larger average distance covered from marker to marker. This indicates lower efficiency where more work needs to happen per unit distance, and higher efficiency where more distance implies more work done. Use this to measure route efficiency.|
|trip_count||Number of trips. The number of trips typically corresponds to your orders, routes or work days, depending on your use case and implementation. Use this to review how much work was done by each user.|
|arrival_percentage||Percentage of trips that arrived at the destination. A high arrival percentage indicates that the app user made it to the destination more often. Use this to measure address accuracy and user behavior.|
|on_time_percentage||Percentage of trips that arrived on time. A high on-time percentage indicates that the app user arrived at the destination on or before the scheduled time. Use this to measure punctuality.|
|drive_distance||Total distance driven by the app user on this day. Use this to review expenses, payouts and reimbursements related to distance driven.|
|stop_duration||Total stop duration by the app user on this day. Use this to review time spent at work or customer locations.|
|steps||Total steps walks by the app user on this day. Use this to review the amount of movement at work or customer locations.|
|locations||Object representing the location time series of the trips. Follows GeoJSON geometry of type LineString|
|markers||Array of markers. The markers show you visited geofences, geotags as well as details about the device status.|
|trips||Array of trips per device|
For every visit to one of your geofences, we add a marker to the markers array. The geofence marker gives you detailed data about the geofence arrival, exit, time spent inside and how the user got to this geofence. Here is an example:
Geotags let you geotag import app events. The geotag markers provide detailed data such as location and metadata provided:
Device status markers
The device status markers explains what the device was doing at a given time. It gives details about
the tracking status (
active when the device is tracking properly,
inactive when the device can't be tracked or
disconnected when HyperTrack lost device-server communications). For active devices, we furthermore split the
markers into activities like
For urgent needs to help you get your data, or for questions or comments on this topic, please do not hesitate to contact us.