Powering On-Demand Forecasting with a Weather API
Figuring out how much supply you need for a fluctuating, need-it-now on-demand market can be like one of those dreaded SAT problems in math class. Train A leaves Kansas City traveling 60 mph, and Train B leaves Chicago traveling 40 mph…except you don’t know how half of the factors to solve the equation.
Unlike a theoretical problem in your high school algebra class, this kind of math determines the success of your business. If you don’t understand what drives demand for your services – whether it’s delivering dinner or an on-demand ride – it’s impossible to offer your customers great service. You need to know the exact factors that can influence their orders, such as the weather, and prepare in advance.
What if you could accurately predict spikes and valleys in your on-demand business? Here are three ways incorporating weather into your on-demand forecasting improves your performance.
1. Increase Profit Margins
Profit margins for on-demand companies are notoriously thin — 6% or less per order. Even delivery market leader DoorDash didn’t post a profit (a cool $23 million) until Q2 2020, driven by in-person restaurant closures. Competitor GrubHub continues to post losses well into the pandemic, losing about 15 cents per order.
Increasing the accuracy of your on-demand forecasting helps both sides of the profit equation, boosting revenue by providing a better customer experience and decreasing expenses with more streamlined operations.
“An unexpected rainstorm can significantly delay deliveries resulting in poor customer experiences, increased operational costs, and inefficient delivery teams. Swiggy makes thousands of deliveries across the country every hour and ClimaCell’s predictive weather impact helps our team make confident decisions in advance- down to the street level and more importantly automate and operationalize these insights.” – Ashish Chatterjee, VP – Product Operations, Swiggy
For example, incoming rain or snow often correlates with an increase in food delivery orders. In fact, 49% of people are more likely to order pizza delivery during bad weather, and 56% want to pre-schedule food delivery via cell phone notifications before a storm impacts them. Using predictive weather impact data for on-demand operations opens up a number of exciting growth opportunities, but it all starts with having access to the right data via a weather API or predictive software.
2. Optimize Operations
Take an on-demand scooter company, for example. Of course, you might know that January in Boston might not be the best time to ride a bike. But what about during a sunny Boston Marathon in April? On-demand forecasting helps businesses determine the placement of assets and how to price them. With more detailed on-demand forecasting from analytics powerhouse Zoba, a scooter company can increase per asset utilization by 10-50%.
Factoring weather into your forecasting adds that much more accuracy, so you’ll know exactly how many scooters need to be available, and where they’ll be needed. Rather than play a guessing game, you can fill demand needs as they arise. Zoba sees increases in contribution margins that tripled the speed at which on-demand mobility companies can pay back their vehicles.
“Demand is impacted directly by weather,” said Daniel Brennan, Cofounder of Zoba. “Understanding weather at the hyperlocal level allows you to better forecast demand. It could be raining on one side of the city and not on the other side. Being able to accurately predict and understand market conditions at the city block level is huge for on-demand companies.”
Not only does this make it easier to supply the right amount of scooters, cars, or bikes at the right time, it also keeps your employees safer. Existing map data can tell you real-time weather, but knowing a storm is coming through in the Northwest part of the city helps your team navigate through treacherous driving conditions, re-routing if needed or predicting increased demand for services so you can offer incentives to ensure you have enough couriers on the road to meet demand and offer timely ETAs.
3. Improve the Customer Experience
With the right weather intelligence, on-demand companies can predict demand surges or dips, allowing them to proactively optimize routes and staffing for maximum efficiency. This ultimately translates into a better customer experience, driving increased loyalty.
How do you translate “customer experience” into a meaningful metric? NPS and C-SAT scores paint some of the picture, but for on-demand companies, ETAs represent a leading indicator you can drastically improve with predictive weather analytics.
When it comes to food delivery, 92% of people say expected delivery time matters, with 69% of people saying they’d consider a different restaurant the next time they order if their actual delivery time differs from the expected delivery time.
Take UberEats, for example. Weather intelligence gives Uber the ability to pinpoint demand surges and improve customer ETAs by 25% during specific weather events.
“With ClimaCell, we’re providing even more accurate ETAs based on insights from their on-demand forecasts.” – Nick Johnson, Maps and Technology Partnerships at Uber
ClimaCell allows Uber to make decisions in advance and in real-time. The software and API offerings allow teams to automate workflows and make business decisions seamlessly instead of worrying about the forecast.
Forget about anxiety-inducing story problems. Powerful on-demand forecasting — with help from ClimaCell’s weather intelligence — gives you the data you need to increase profit, optimize your operations, and improve the customer experience.