Public transport ridership numbers have always been a rough sketch. The real shift is happening in the background, where GPS traces from phones, smarter traffic signals and integrated mobility platforms are giving planners, banks and consumer firms a far sharper picture of how cities actually move.
The core argument is simple: traditional transport data—manual traffic counts, periodic transit surveys—is expensive, slow and leaves most cities blind to live patterns. New data sources are closing that gap, with downstream effects stretching from bus route planning to retail site selection.
The short version
- Traditional transport data is expensive and time-consuming, leaving governments blind to live movement patterns.
- Mobile and GPS data can show where people actually walk, bike, drive or commute.
- Key users include infrastructure planning firms, research organisations, banks and consumer businesses.
- The opportunity: more than 2 billion people in emerging markets depend entirely on public transport, often through informal services.
- Example: the World Bank used mobile data in Nairobi to identify crash points and prioritise road investments.
Why old transport data falls short
For decades, urban mobility was measured slowly. Someone stood at an intersection with a clicker. A transit agency ran a ridership count during a particular week. These older tools are expensive and time-consuming, which is why investors and city planners have historically made big calls on incomplete information.
Two structural problems follow. First, the data favours formal systems—buses on timetables, metros with turnstiles, taxis with meters—while skipping the minibus taxis, moto-taxis and shared vans that dominate emerging-market cities. Second, by the time a survey is published, the city has often already moved on, with new routes, new housing and new commuter patterns.
What mobile data actually changes
The new layer is behavioural rather than declared. GPS pings from phones can show where someone walked, biked, drove or boarded a bus, with far finer resolution than a survey answer. Smarter traffic signals add another stream, counting pedestrians and timing crossings. Several companies are now fusing these newer sources with traditional feeds into single citywide models.
The practical difference is that planners can finally see gaps: not just which bus route is busiest, but where people want to go and currently cannot, because the network does not reach there, the service is too slow, or the formal system does not exist. Those gaps are also where banks and consumer firms start paying attention, because unmet demand is a market signal.
Our analysis
This is one of those stories where the flashy version ("smart cities!") is less interesting than the boring one. The boring version is that lenders like the World Bank are quietly willing to pay for better data because it lowers the risk of funding a road or rail line that nobody uses. That changes who has use. Data providers, often small, can sit between multilateral lenders and ministries of transport, shaping which projects move first.
There is a real tension, though. The same data that helps a bank prioritise a safer intersection in Nairobi can, in other hands, profile individual commuters. The privacy trade-off is the part readers in this niche tend to notice first. Expect debate about retention periods, aggregation thresholds and whether data is ever tied back to a specific device.
The vendor landscape is worth watching. Integrated "city model" platforms risk consolidating into a few dominant players, which could limit competition and raise prices for cash-strapped municipalities. Regulators in emerging markets may also start requiring data-sharing arrangements as a condition of receiving infrastructure loans—a development that could either democratise access or create new bottlenecks.
Who should care
| Sector | What they get | What to watch |
|---|---|---|
| Infrastructure banks | Better risk assessment for transport investments | Whether data costs remain manageable for small projects |
| Planning firms | Origin-destination data showing where passengers actually want to go | Vendor lock-in if platforms become proprietary |
| Consumer businesses | Site selection signals from movement patterns | Privacy regulations that restrict data resale |
| Research organisations | Alternative data for economic trend analysis | Aggregation thresholds that limit granularity |
What to watch next
Bottom line: mobility data is turning urban planning from a survey-driven exercise into a near-real-time one. The biggest beneficiaries will be cities and lenders that have historically had the worst data to work with. The privacy questions are not solved, and the vendor landscape is consolidating, so keep an eye on who ends up holding the raw feeds.
Frequently asked questions
Why is traditional public transport data considered limited?
Traditional methods, including traffic counts and public transport estimates, are expensive and time-consuming, leaving governments largely blind to live movement patterns in their cities.
How do companies collect new mobility data?
Sources include GPS tracking from mobile phones, which can distinguish walking, biking, driving and commuting, as well as smarter traffic signals that count pedestrians and measure crossing times.
How is the World Bank using mobility data?
The World Bank has used mobile data to identify crash points in the Nairobi road network and prioritise investments, and has contracted data providers for public transport data across multiple African cities.
Why does mobility data matter for emerging markets?
More than 2 billion people in emerging markets rely entirely on public transport, and in most new-market cities, more than two-thirds of services still operate informally—precisely what older datasets miss.
What privacy concerns come with mobile mobility data?
The article highlights the analytical value but does not detail privacy rules. The concern is that fine-grained GPS traces can be re-identified if not properly aggregated, which is why retention periods and anonymisation standards are a key area to watch.