Important Note: All of the information below applies to partner users only - not general/public Busby users.
Enterprise partners looking to onboard employees or stakeholders have access to powerful analytic capabilities provided by Busby Insights.
How is data collected?
Data is either live-streamed or batch uploaded (depending on your rider use cases and preferences) to your analytics dashboards. Your users explicitly grant consent for their data to be collected as part of the custom onboarding process
Whos data is collected?
You are only able to view and query your own rider data.
What data is collected?
The following data insights are available out of the box:
Cyclist Locations (real-time)
Quickly view your cyclist density and locations in real-time, with less than 100ms latencies allowing superior fleet management and logistics management
Both real-time and historical (any time period) to allow you to view the heatmaps of your users at any location at a glance.
Quickly identify high-risk areas for your users (and also the general public) in order to safeguard your staff/users and pro-actively avoid incident hotspots.
Whilst incident hot-spots are useful for viewing historical incident data, near-miss hotspots are much more proactive and allow you to make recommendations to your users to avoid potential areas or situations where an incident is highly likely.
How do I view my data?
You and your team are provided with secure access credentials to your user dashboards, including visualisations, mapping, metrics tiles, graphs and more.
Can I run custom queries?
Yes, custom queries can be run against your user data.
What is the recommended ingest period/amount for the analytics platform?
This varies on the metrics described above, some metrics such as rider locations are instantly useful to the organisation, whilst others like near-miss hotspots and incident hot-spots typically return value back to an organisation once a period of 30 days of data has been collected. Increasing the number of riders can shorten this period (i.e. 100k riders in a region will produce more data than 1k riders over the same duration).