US transit agency Southeastern Pennsylvania Transportation Authority (SEPTA) recently published its September ridership figures. Total ridership increased by 8% compared with September last year, with average daily ridership reaching its highest level since February 2020.

The differences across the network make the figures particularly interesting:

🚌 Bus ridership increased by 14%.
🌙 Between 6 PM and midnight, bus ridership grew by 22%.
🚇 Metro ridership rose by 4%, while weekend ridership declined.
🚆 Regional Rail ridership was 4% lower than a year earlier.

One service can gain passengers while another loses them. Growth in the evening may create different capacity needs from growth during the morning peak.

SEPTA also puts these changes into context, discussing construction work, station closures, events and weather conditions.

For operators and public transport authorities, this is where the conversation about service adjustments begins. Which routes and time periods are seeing growth? What does this mean for occupancy? How are fare revenues developing relative to operating costs? And does the service still match the journeys people want to make?

At Zight, we bring passenger data, timetables and operational performance together. This helps operators and authorities explore trends at the level where decisions are made: by route, stop, direction and time of day.

But what if your ticketing data only tells you where passengers board?

In check-in-only networks, the alighting stop remains unknown. This makes it harder to understand complete passenger journeys and how occupancy changes along a route.

Our AI-powered OD Generator estimates an alighting stop for each check-in. It combines boarding data with information about the transport network and the areas surrounding stops, enriching your existing records with estimated destinations.

This helps operators analyse origin–destination flows, transfers, vehicle occupancy and passenger miles, and better understand where service and demand may be out of balance.

How does it work? You send us your check-in-only transaction data. Within a few days, we return the dataset enriched with estimated alighting stops. You can use it directly in your own analyses or explore the results in the interactive dashboard included.

Together, these insights help identify where additional capacity may be needed, where timetables need attention, and what subsequent changes actually deliver.

Curious what our OD Generator could do for your network? Comment ‘OD’ below and we’ll tell you more!