Big Data Analytics Improve Transit Operations at Blacksburg Transit

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Big Data Analytics Improve Transit Operations at Blacksburg Transit

Case study shows how granular data collection and custom reporting from TripSpark Streets enabled 22% ridership growth and 90% on-time performance at Blacksburg Transit.

Published

June 4, 2026

Read time

3 min read

Source

Blacksburg Transit collects 11,000 data points daily across fixed route, paratransit, and commuter services. Access to raw stop-level data allowed the agency to analyze schedule adherence, passenger loads, boarding/alighting patterns, and fare types. This supported weekly service adjustments for university schedules, eliminated low-performing stops, and provided evidence-based responses to customer complaints. The approach contributed to an APTA Outstanding Transit System award in 2019.

Key takeaways

Granular data access enabled stop-level ridership and schedule adherence analysis beyond canned reports

22% increase in ridership and revenue service hours achieved from 2016-2018 through data-driven planning

90% on-time performance maintained with 43 passengers per revenue hour, nearly triple the national average

Daily collection of 11,000 data points supports trend detection and answers to previously unasked questions

Real-time passenger information via app and SMS replaced printed timetables, handling 2,500 text inquiries daily

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