We've taken a deeper look at privately held Uber, the ridesharing service provider that sits at the number-two spot in the world and is attempting to gain traction in what we estimate will be a $630 billion market by 2022.
In our view, Uber's core business, the ridesharing platform, would warrant a narrow economic moat rating as it has displayed some moat sources such as network effects and intangible assets, which could position the company to become profitable and generate excess returns on invested capital in the future.
Based on our analysis and using publicly available data on Uber's financials from The Wall Street Journal as a starting point, we value Uber at a $110 billion market capitalisation.
We project that Uber's net revenue will grow at a 27% average annual pace over the next 10 years to $82.4 billion. We foresee Uber continuing to spend on expansion and research and development but think it will become profitable by 2022. The company is likely to go public during the second half of 2019, and considering its success at raising capital, we expect the initial public offering price to value Uber between $100 billion and $110 billion.
Looking ahead, Uber may leverage its ridesharing business and tap into other growth opportunities, including bikesharing, meal takeout and delivery, freight brokerage, and ridesharing via autonomous vehicles.
In our view, autonomy is the most transformative technology set to affect the world of ridesharing; we see powerful economic forces driving autonomous vehicle adoption in the ridesharing industry, from which Uber may benefit. On the other hand, risks remain, such as increased competition and the company's legal issues.
How Big is Uber’s Market?
An Uber ride can be ordered in 65 countries and more than 700 cities. Based on data from Uber and eMarketer as quoted in Reuters, Uber has U.S. ridership of over 40 million people and global ridership of 75 million. EMarketer projects U.S. ridership to increase to 64 million by 2022.
Riders depend on approximately three million active drivers globally, with "drivers" defined as those providing more than four rides per month. Uber says it completed four billion trips in 2017, resulting in $36.2 billion in gross bookings and $7.8 billion in net revenue. Its largest territory is North America, while the company is also present in Central and South America, with the ridesharing app available in over 300 and 175 cities, respectively.
Uber's scale is not derived only from ridesharing, however. According to Eater and Uber, Uber Eats – the food delivery service – has eight million monthly active users in over 250 cities globally, with over 60,000 participating restaurants.
This compares with current market leader Grubhub's GRUB 15 million users and over 80,000 restaurants. Uber Eats has expanded rapidly, with the number of drivers growing 24% between March 2016 and March 2017, according to The New York Times. Although its drivers are considered contractors, Uber also has nearly 16,000 employees.
We believe that Uber's market potential expands far beyond the one-off need for a ride from the car dealer or airport, and even the total taxi market. Uber leverages its network of drivers and users for logistics of transporting people, food, and cargo to create a compelling substitute for traditional means of transportation.
For these reasons, we believe Uber's total addressable market is the aggregate of the global addressable markets for the taxi, rideshare, and food delivery industries along with the U.S. addressable markets for freight brokerage and the share we believe rideshare companies can take from global public transport and U.S. bikeshare. Taking these submarkets into account and adjusting for Uber's lost stake in China, we estimate Uber's total addressable market to be $630 billion by 2022, with a 26% compound annual growth rate from 2017 to 2022.
We View Uber as a Narrow-Moat Business
In our view, Uber's core business, the ridesharing platform, has displayed some moat sources such as network effects and intangible assets, which could position the company to become profitable and generate excess returns on invested capital in the future. For this reason, we assign Uber a narrow moat rating, meaning we believe it has a small competitive advantage over its peers.
Uber's network effects benefit drivers as well as riders, creating a continuous virtuous cycle. Drivers and riders make up the supply and demand in ridesharing, respectively. As a first-mover in this market, where requests for rides from anywhere could be made in real time via a simple-to-use mobile app, Uber began to attract riders mainly via word-of-mouth marketing.
Growth in demand and further word-of-mouth marketing attracted more drivers, increasing the supply of Uber vehicles. As the number of drivers increased, the timeliness and reliability of the service improved, which drove the number of users or riders higher, which attracted more drivers, all of which we believe is indicative of the network effect.
Growth in demand is driven not only by more users, but also likely by more rides per user. Increasing supply is based on more drivers and further capacity utilisation of each driver and vehicle. Therefore, what we view as Uber's network effect increases the benefits from and value of Uber's network for new and existing riders and drivers.
A figure that we believe supports this and demonstrates increase in vehicle capacity utilisation is growth in average number of rides dispatched per unique Uber vehicle, which has been increasing gradually from 2015 through 2018.
While we think Uber has benefited nicely from network effects in recent years, we don't believe it benefits from customer switching costs. In our view, the ridesharing industry currently lacks barriers to entry or exit for customers and drivers. Both customers and drivers can easily switch to Lyft, while customers have other transportation options like taxis and public transit.
In early 2017, Uber faced much criticism for appearing to support an immigration order signed by President Donald Trump and attempting to profit from protests related to that event in New York City, both of which led to the #deleteUber campaign launched on Twitter.
Also, then-CEO Travis Kalanick was appointed to Trump's economic advisory council, to which some employees at Uber objected. Lack of barriers to exit or switching costs for riders and drivers was on display, as during the same period, other ridesharing providers such as Lyft made headway in New York City and experienced faster growth in trips as riders easily downloaded and used Lyft and other apps for ridesharing services.
In our view, Uber's ridesharing network effect can help the company tap into other markets and generate additional revenue streams. An example is the meal takeout and delivery market. According to Recode, Uber Eats has grabbed share from Grubhub and currently has about 21% of the U.S. market. The same can be said about Uber's plan to extend its reach into the bikesharing and freight brokerage markets.
There are concerns about whether Uber's network effects can remain an economic moat source if the company is forced to incur additional costs imposed through regulations at the municipal, state, and/or federal levels. Additional worries surrounding Uber's network effect moat source include the potential impact of autonomous vehicle adoption on car ownership. Some believe autonomous vehicles could attract more car buyers and increase car ownership, thereby possibly lowering demand for ridesharing services, as self-driving cars may diminish annoyances and other costs currently associated with driving in traffic and/or driving long distances.
We disagree, as we think the availability of autonomous vehicles on ridesharing platforms will significantly reduce the necessity of car ownership, which also lowers the return on the much higher car ownership costs.
As Uber benefits from its network effect, we think it gains access to valuable intangible assets in the form of data on riders and drivers, which we suspect helps the company improve its services and increase its vehicles' capacity utilisation.
In turn, Uber's service may become more effective over time as the company further monetises its riders via real-time supply and demand-driven pricing. Uber may also use this extensive data and knowledge to tap into other markets. An overall enhancement in service could help the company strengthen its network effect by increasing users and ride requests per user, which helps Uber gather additional data, possibly further increasing the overall value of the data. Simply put, data can also be considered as an indirect network effect moat source.
