Lyft Price Quotes

Summers also claimed that technology was reducing the demand for capital. Digital businesses, such as Facebook and Google, had established dominant global franchises with relatively little invested capital and small workforces. In his book The Zero Marginal Cost Society (2014), the social theorist Jeremy Rifkin heralded the passing of traditional capitalism.16 If the Old Economy was marked by scarcity and declining marginal returns, Rikfin argued that the New Economy was characterized by zero marginal costs, increasing returns to scale and capital-lite ‘sharing’ apps (such as Uber, Lyft, Airbnb, etc.). The demand for capital and interest rates, he said, were set to fall in this ‘economy of abundance’. There was some evidence to support Rifkin’s claims. The balance sheets of US companies showed they were using fewer fixed assets (factories, plant, equipment, etc.) and reporting more ‘intangibles’ – namely, assets derived from patents, intellectual property and merger premiums. In much of the rest of the world, however, the demand for old-fashioned capital remained as strong as ever. After the turn of the century, the developing world exhibited a voracious appetite for industrial commodities that required massive mining investment. China embarked on what was probably the greatest investment boom in history. Before and after 2008, global energy consumption rose steadily. The world’s total investment (relative to GDP) remained in line with its historical average.17 Rifkin’s ‘economy of abundance’ remained a tantalizing speculation.

Up-front investment to try to professionalize the supply side early on in a network’s development inevitably comes with risk. In a well-publicized misstep for Uber, the company sought to expand its supply side by financing vehicles to provide cars to potential drivers who didn’t own vehicles, a program called XChange Leasing. The hypothesis was that this should push these drivers into power-driver territory quickly. Payments could be automatically deducted from their Uber earnings, and their driver ratings and trip data could be used to underwrite the loans. XChange Leasing unfortunately lost $525 million and failed to professionalize the driver side of the market. The problem was, it attracted drivers highly motivated by money—usually a positive—but who didn’t have high credit scores for good reason. They often failed to make payments, using their Uber-provided car to drive for competitors and avoid the automatic deductions. They would steal the cars and sell them for, say, half price. They would drive for Lyft instead of Uber, as a way to avoid the automatic payment deductions—they would try to have their cake and eat it, too. Uber needed to organize a massive repossession effort to get the cars back, but it was too late—many had been sold illegally, some finding themselves as far away as Iraq and Afghanistan, GPS devices still attached and running. This is a colorful example of how scaling the supply side, when a lot of capital is involved, can be tricky.

Finding the Competitive Levers When there’s a battle between two networks, there are competitive levers that shift users from one into the other—what are they? The best place to focus in the rideshare market was the hard side of the network: drivers. More drivers meant that prices would be lower, attracting valuable high-frequency riders that often comparison shop for fares. Attract more riders, and it more efficiently fills the time of drivers, and vice versa. There was a double benefit to moving drivers from a competitor’s network to yours—it would push their network into surging prices while yours would lower in price. Uber’s competitive levers would combine financial incentives—paying up for more sign-ups, more hours—with product improvements to improve Acquisition, Engagement, and Economic forces. Drawing in more drivers through product improvements is straightforward—the better the experience of picking up riders and routing the car to their destination, the more the app would be used. Building a better product is one of the classic levers in the tech industry, but Uber focused much of its effort on targeted bonuses for drivers. Why bonuses? Because for drivers, that was their primary motivation for using the app, and improving their earnings would make them sticky. But these bonuses weren’t just any bonuses—they were targeted at quickly flipping over the most valuable drivers in the networks of Uber’s rivals, targeting so-called dual apping drivers that were active on multiple networks. They were given large, special bonuses that compelled them to stick to Uber, and every hour they drove was an hour that the other networks couldn’t utilize. There was a sophisticated effort to tag drivers as dual appers. Some of these efforts were just manual—Uber employees who took trips would just ask if the drivers drove for other services, and they could mark them manually in a special UI within the app. There were also behavioral signals when drivers were running two apps—they would often pause their Uber session for a few minutes while they drove for another company, then unpause it. On Android, there were direct APIs that could tell if someone was running Uber and Lyft at the same time. Eventually a large number of these signals were fed into a machine learning model where each driver would receive a score based on how likely they were to be a dual apper. It didn’t have to be perfect, just good enough to aid the targeting.

registered email address and went global in 2007. Twitter split off onto its own platform and went global in 2007. Airbnb was born in 2007. In 2007, VMware—the technology that enabled any operating system to work on any computer, which enabled cloud computing—went public, which is why the cloud really only took off in 2007. Hadoop software—which enabled a million computers to work together as if they were one, giving us “Big Data”—was launched in 2007. Amazon launched the Kindle e-book reader in 2007. IBM launched Watson, the world's first cognitive computer, in 2007. The essay launching Bitcoin was written in 2006. Netflix streamed its first video in 2007. IBM introduced nonsilicon materials into its microchips to extend Moore's Law in 2007. The Internet crossed one billion users in late 2006, which seems to have been a tipping point. The price of sequencing a human genome collapsed in 2007. Solar energy took off in 2007, as did a process for extracting natural gas from tight shale, called fracking. Github, the world's largest repository of open source software, was launched in 2007. Lyft, the first ride-sharing site, delivered its first passenger in 2007. Michael Dell, the founder of Dell, retired in 2005. In 2007, he decided he'd better come back to work—because in 2007, the world started to get really fast. It was a real turning point. Today, we have taken another

Commoditized services marketplaces should be responsible for setting prices to ensure its users receive the optimal price. If you look at other commoditized services platforms, such as Handy, Lyft, and Glamsquad (an Applico client), consistent and transparent pricing is a core part of their ability to deliver seamless matching.

Thiel wrote in his 2014 book, Zero to One: Great companies can be built on open but unsuspected secrets about how the world works. Consider the Silicon Valley startups that have harnessed the spare capacity that is all around us but often ignored. Before Airbnb, travelers had little choice but to pay high prices for a hotel room, and property owners couldn’t easily and reliably rent out their unoccupied space. Airbnb saw untapped supply and unaddressed demand where others saw nothing at all. The same is true of private car services Lyft and Uber.