Meteum for Ride-Hailing Services
Taxis are an integral part of any city’s transport system. Ride-hailing services powered by cutting-edge technology have become a staple all around the world, and their convenience is unmatched. However, despite the simplification and automatization of processes over the last decade, managing a successful rideshare can be a logistical nightmare.
A massive swathe of factors must be closely monitored in this industry to balance coverage and control supply. Among them is the time of day, traffic conditions, and road closures. But one factor that stands out the most is the weather: unlike the others, it has no clear oscillating pattern.
Sudden snow or rain can reduce visibility, degrade road surfaces, and increase ride-hailing demand by a magnitude, causing the system to overload. It can ruin anyone’s day: while drivers are overwhelmed with unfavorable orders, riders experience protruded wait times and severe price spikes.
To account for these factors, transportation network companies (TNCs) use big data and machine learning to predict demand and optimally distribute cars around the city. But of course, these prediction models are only as accurate as the data they use as a base. As we mentioned, weather plays a major role in demand fluctuations. Therefore, choosing a high-quality weather forecasting solution is key.
If this speaks to you, Meteum is precisely the kind of solution you’re looking for. In one of our previous posts, we described how our platform works in more detail.
Here’s a quick break-down:
- Meteum uses a multitude of raw weather data sources, from radar readings to satellite images.
- We both use ready-made forecasts from other weather models and generate our own forecasts from the ground up with an open-source meteorological model.
- We employ the most recent weather data, forecasts produced by other models, and real-time user reports to calculate the ultimate forecast with our advanced proprietary algorithm. This forecast is more accurate than what any single model could output by itself.
- Businesses can use our API to access hundreds of weather parameters and set up a customized workflow for their needs.
We have real-life data to back all of this up: in our case study, we helped a ride-hailing company decrease taxi wait times, cut operating costs, and provide a better, safer, and faster service.
The ability to predict where it’s going to be raining in the next 30–60 minutes drives better predictions of demand and improves car distribution around the city. Thanks to Meteum predicting where and when it will rain with up to 90% accuracy, a taxi service cut demand forecasting errors by 38%.
But there’s more: the average wait time dropped by 18% since drivers were able to position themselves in anticipation of demand spikes. The company’s driver loyalty index also jumped by 11% after Meteum made life easier for them. During inclement weather, incremental GMV was up 28%.
This expericence demonstrates that weather significantly influences ridership, especially when the conditions are severe. Riders expect taxis to work like clockwork, and we at Meteum believe this goal is perfectly achievable if you approach it the right way.
Visit meteum.io to explore our out-of-box solutions or grab your free API key to boost the efficiency of your ride-hailing business with our top-of-the-line weather forecasting platform.
