Every time you click to book a ride on the Grab app, the machinery that clicks in the background crunches some serious numbers to pair you with a driver.
It's "staggeringly complex," as Grab's director of engineering, Ditesh Gathani, put it in an interview with Mashable.
SEE ALSO:Uber's ambitious mapping project kicks off in AsiaUnderneath the seemingly simple process of booking, the system has to achieve a few goals, such as: providing the passenger with a driver, at reasonable cost within minutes; and to do this with as few buttons to press, and fields to fill in as possible.
It also runs predictive analytics in real-time to figure out where demand will be, so the app can tell drivers where to go in the next few hours. Add that to machine-learning, with the system figuring out your routine and filling in where you want to go on some days.
And it balances live demand and supply against pricing algorithms so an attractive fare (to both driver and rider) can be recommended.
"All that, in the order of milliseconds," Gathani said, taking a breath.
The ride-sharing app is Uber's biggest competition in Southeast Asia, handling well over 1.5 million bookings a day across Singapore, Malaysia, Indonesia, Thailand, Vietnam and the Philippines.
Its driver network has crossed 630,000 across the region, which has stretched beyond private cars and taxis to include motorcycles and, just recently, private shuttle buses and coaches for hire.
View this post on Instagram
Gathani himself has seen the engineering team grow from 10 to its current size of several hundred, across three offices in Singapore, Seattle and Beijing.
Most of the software engineers focus on features and building out Grab's advanced machine learning engines, while the backend is offloaded onto Amazon Web Services, so there are fewer needed to tend to server room stuff, he said.
The team rolls out an estimated 100 upgrades to the system per week in the background, without users noticing.
Grab has a dedicated team of economists that determine what fare you pay.
The specialists Grab has hired now also include a team of economists, chiefly responsible for the fare you pay.
"From an engineering perspective, dynamic pricing systems are so complicated," Gathani said.
To arrive at a single fare at a given time, the system works through several economic models, and takes into account real-time demand and supply.
Coupon codes also affect rider behaviour significantly, and the system needs to be smart enough to hand out monetary incentives to drivers, to attract more to high-demand areas if it detects a surge.
View this post on Instagram
When Grab started in Malaysia as MyTeksi several years ago, the model was far less sophisticated, he noted. "We had a naive approach to pricing. We'd have a [pre-set fare] and let people offer tips to drivers to pick up their requests -- and drivers knew. So [drivers] would wait and not accept rides until tips started coming.
"It made passengers furious," he said.
Grab -- and other companies like it -- have become so reliant on data.
Today, the system is a lot smarter. It's mapped each driver on its network, and is able to measure how likely someone will accept a job. The model is self-learning, so it refines itself over time based on how people behave on the app, and autonomously figures out who to send jobs to, and when.
"We're able to tailor jobs to drivers, right down to the individual," said Gathani.
Grab -- and other companies like it -- have become so reliant on data that nearly every department works through obsessive tracking information for daily operations.
The marketing team, for example, combs through terabytes of data with analysts to measure how well promo codes work, he said.
And is it true that people who cancel rides get penalised?
"Yep," he nodded. "Cancelling has a tremendously negative effect on the ecosystem."
The system learns to sift out serial cancellers and penalises them by lowering the chance of them getting a ride.
Only about 5 percent of Grab's users are classified as serial offenders. If you're among their ranks, you can still train the machine to lift you out of the red zone by behaving a little more responsibly.
TopicsUber
(责任编辑：時尚)
Airbnb activates disaster response site for Louisiana flooding
Lil Nas X's 'Satan Shoes' will be recalled in settled lawsuit with Nike
The free cookbook designed for people with taste and smell loss from long COVID
Brendan Fraser's top hits as told by Twitter, and where to stream themThe Weeknd teases new music in Instagram postTesla's rumored P100D could make Ludicrous mode even more Ludicrous
A Tesla Model S P100D begs the question: What's more Ludicrous than Ludicrous?Right now, the biggest
...[详细]Tinder releases 'Are You Sure?' feature to stop harmful messages before they happen
Over the past few years, Tinder has stepped up its safety features — with good reason. The app
...[详细]Researcher claims to hack AirTag so it points to wrong website when scanned
That didn't take very long. A German researcher claims to have hacked Apple's new item tracker, the
...[详细]Is Apple planning a spring event to introduce new iPads and AirPods?
Apple might have a product announcement event in just a few days. But then again, it also might not.
...[详细]These glasses hide a fitness tracker on your face
The last time a company tried popularizing wearable tech embedded in glasses, most notably with Goog
...[详细]Twitter refines its scolding prompts in ongoing effort to make users nicer
If at first you don't succeed... Twitter announced Wednesday an update to its ongoing effort to pare
...[详细]
The electric Audi keeps evolving. Back in 2018 Audi unveiled its first all-electric SUV, the e-tron.
...[详细]Apple knows AirTags can be abused and is trying to get ahead of it
Sometimes, you don't want things to "just work" for everyone. On Tuesday, Apple announced a slew of
...[详细]Uber's $100M settlement over drivers as contractors may not be enough
UPDATE: Sept. 7, 2016, 4:41 p.m. EDT 。 A ruling in a different case on Wednesday, Sept. 7 may have ch
...[详细]
The pandemic still rages across the world. A hard-hitting second wave of coronavirus has reached Ind
...[详细]
