And at the same time, we’re driving – we’re driving the bottom line and free cash flow for investors that’s super attractive as well. That said, we are optimizing around our earners costs. So we don’t have to lean into incentives the way that we did previously. So if you look at our incentive spend for earners, it’s down about 41% on a year-on-year basis. Globally, it’s down about 50% in the US because with the liquidity of the marketplace kind of natural earnings levels are high at about $33 per utilized hour across the US. It’s $50 here in New York City per utilized hours. So earning levels were high. That allows us to take incentives down. But we’re also working on other parts of on-boarding efficiency, when we run a background check, for example, for a driver, and running it background check.
If we qualify a driver, if we know that driver is highly, highly interested running a background check, if we don’t think we can qualify, let’s say, that earner delaying the background check that again delays expenses as well. So across – across the business up bringing earners on, not just incentives, we’re looking to optimize the cost there and so far, so good. Next question. You’re welcome.
Operator: Our next question comes from Ron Josey with Citi. Your line is open.
Ron Josey: Great. Thanks for taking the question. I wanted to ask a little bit more about the non-X gross bookings now at that $9 billion run rate growing 80%. Are any of these new offerings, talk to us about how these new opportunities creating demand? And any other product specifically, seeing greater demand versus others, meaning Reserve, Comfort, Green, UberX, things along those lines? Thank you.
Dara Khosrowshahi: Yes, absolutely. So these products are definitely creating demand, and they create demand in different ways. So for example, Hailables or taxi product, if you look at the number, the percentage of new customers coming in from Hailables, it’s about twice the percentage of gross bookings that taxi represents. That’s because in a bunch of markets, actually, the only way we can penetrate into those markets is through taxi. Japan, as an example. We have a very, very small, high-end peer-to-peer business. But we’re going in partnering with taxis in Japan. We actually just joined the taxi association in Japan as well. And those taxies essentially our brand-new supply introduced us to a whole new audience in Japan.
And actually, the tourists coming into Japan as well kind of supports the local economy. So that’s an entirely new audience. That’s true in many parts of Argentina, in Turkey, where these new business models essentially are bringing new audience. The other one that I will point out to are low-cost products. So if you look at UberX Share, for example. It is taking some trips away from our UberX business do see kind of lower income move to UberX Share faster. So we think that’s providing them relief based on kind of the economic hardships and all the inflation that we’re seeing there. So we’re absolutely seeing a higher penetration of UberX Share for lower-income consumers, but it’s also introducing us to a new audience as well. Same thing in Moto.
These are two-wheelers in Latin America, and again, newer lower income audience that previously could afford Uber, now can afford Uber as well. So, all of these either drive audience or frequency or both. And obviously, they’re strategic in terms of our long-term growth formula.
Ron Josey: Great. Thank you, Dara.
Dara Khosrowshahi: You’re welcome. Next question.
Operator: Our next question comes from Doug Anmuth with JPMorgan. Please go ahead.
Doug Anmuth : Thanks for taking the question. One for Dara and one for Nelson. Dara, what do you view as some of the primary compounding advantages you’re currently achieving just across operational best practices? And where do you see the biggest opportunities going forward? And Nelson, you’ve improved profit significantly over the past year, incremental margin is now running at about 9% in 3Q. How are you thinking about key investments in hiring into 2024? Thanks.
Dara Khosrowshahi: Absolutely, Doug. So in terms of the compounding advantages, I’ll go back to what I was talking about in terms of machine learning, which is becoming a much more important part of the business. So we’re just — we have more data points in terms of opportunities to match riders to drivers or eaters to restaurants to couriers. And for example, if you take a look at our driver upfront pricing, the change that we made, it had a huge benefit for drivers, right? Drivers can see where their destination is and as a result, can accept or not accept that trip based on destination and upfront price that they see. It’s a very, very powerful driver of the business. But it also is another opportunity for us to price out that trip.
Previously, drivers are paid based on time and distance. Anyone can price based on time and distance. So the amount of data that you have doesn’t help you calculate a certain per mile rate and a certain time rate as well. So there’s zero kind of benefit to scale. Now in a world where drivers know their destination, we can price out that destination. We have more opportunities to price. We have more drivers than anyone else in the marketplace. So we’ll be able to price up that trip and match it to a particular driver based on a bigger data set than anyone else in the world that advantage compounds as our machine learning kind of platform learns more about different trips, which ones are accepted, which ones are not accepted, which ones are canceled as well.
So all of our marketplace mechanisms in terms of routing, in terms of matching, in terms of pricing, now are essentially point estimates that we can train on a larger database than anyone else. If you look at payments, for example, we announced a great new partnership with PayPal and our ability to — we’re one of the largest players out there in terms of bookings, $35 billion in bookings in a quarter, growing at a rate that most players our size aren’t growing. So on the payment side, for example, we think we can secure a lower payment cost than other players, that’s going to compound. If you look at parts of our business like detecting fraudulent activity, there are lots of rosters out there. They are being armed by machine learning, and we can detect patterns across a greater set of use cases, both in mobility and delivery so that we can identify, let’s say, the bad folks from the good folks, differentiate them and reject the bad folks and have them maybe try to steal from other platforms.
All of these different parts of the business are compounding in one way or the other. Many of them are powered by machine learning. And again, if you’ve got the most data in the world, your ML algos typically have an advantage over smaller players.
Nelson Chai: So Doug, in terms of our ability to balance growth and profitability, as you know, since we have public, Dara and I have been talking about our capital allocation process, we laid out our three-year targets last year. And if you look at the performance of the company, we’ve been in line with the top line and overachieved at the bottom every single quarter. And if you look at the guidance, again, it’s very, very, very constructive, if you think about it. You heard Dara talk a lot about where the business is going and some of the growth, our mobility business, the gross bookings were up 30% in Q3. And that’s why we’re continuing to invest in the businesses. So if you think about it, where we are today on both delivering the bottom line, but investing for the future, we’re starting to see some of these new growth initiatives scale, new mobility products, $9 billion gross bookings run rate, new verticals are at a $6 billion gross bookings run rate.
