Lyft Inc

Lyft posted solid second-quarter results, with active riders up 17% to 30.5 million, and gross bookings up 23% to $5.5 billion. Partnerships drove 30% of North America rides (up from 27%), supporting growth. Adjusted EBITDA was up 37% to $177 million or 3.2% of gross bookings—an all-time high.

Why it matters: The demand side, with improving rider counts, and the supply side, with active drivers and hours worked near all-time highs, are healthier than usual and a welcome development for investors. However, we continue to view Lyft as a subscale network that lacks pricing power. Gross bookings revenue is accelerating, though approximately 6 percentage points of the headline growth are inorganic, driven by the Freenow acquisition. Roughly 17% organic growth is a decent improvement relative to the trailing eight-quarter organic growth average of 15%. Absolute scale versus Uber remains the key challenge. While not geographically or structurally apples-to-apples, Uber’s core user base of over 200 million (versus Lyft’s 30 million) and 3.8 billion quarterly trips (versus Lyft’s 260 million rides) translate to a 70-30 market share split in North America. We believe this disparity will cap Lyft’s margins.

The bottom line: We maintain our no-moat rating and $15 fair value estimate. Lyft made operational progress this quarter and is generating cash, but it isn’t enough to materially change our thesis that scale begets scale in network-effect economies—and Lyft still lacks that. The same competitive and verticalization threats from autonomous vehicle firms that have weighed on Uber should disproportionately affect Lyft and its smaller balance sheet. We believe the firm has very little bargaining power in potential partnerships.

Our $15 per share fair value estimate represents an enterprise value of 0.71 times our 2026 revenue estimate. We project Lyft’s revenue will grow 9% annually over the next five years, on average, consistent with our view of the maturing ride-hail market and Lyft’s weaker competitive position relative to Uber.

To build our revenue, we developed a model that captures a fast-growing yet maturing technology while also factoring in the incremental adoption of autonomous vehicles. We forecast gradually declining year-over-year growth in gross bookings, starting at 16% in 2026 and declining to 5% in 2035. We believe Lyft still has a role in the future of ride-hail, but that role is more likely than not to remain smaller than Uber's.

The 2010s era of zero interest rate policy, or ZIRP, is over, at least for now, making it prohibitively expensive to build a durable network. The ZIRP era allowed Uber and DoorDash to finance their buildouts by committing to demand- and supply-side subsidies over many years, operating at significant losses to build their networks. We believe similar-size, long-duration network-building losses, financed at today's rates, would be intolerable for Lyft investors. As such, Lyft's path to creating economic value, in an increasingly mature North American ride-hail market, requires resolute focus on efficiency and positive unit economics.

We expect net revenue growth to slightly outpace major cost components, including insurance, research and development, operations and support, and general and administrative expenses. Insurance costs, a significant driver of Lyft’s cost of revenue, have historically been a major headwind due to premium inflation and rising deductibles. However, Lyft has transitioned from an in-house captive insurance model to greater third-party risk transfer, benefiting from insurers’ growing comfort with ride-hail risks. Additionally, legislative pressure to cap auto insurance premium increases should help stabilize costs moving forward. Insurance premiums have also been decreasing from the 2023-24 peaks.

On research and development, Uber and Lyft have pulled back from capital-intensive autonomous technology. While this has boosted near-term profitability, it also introduces some uncertainty about whether the firms exited the space too early, potentially leaving them susceptible to AV penetration.

On employee costs, Lyft has implemented several workforce reductions over the past couple of years, reducing its workforce by more than a quarter. We like this leaner version of Lyft, and we expect it to remain cost-conscious through the projection period.

While the firm had previously struggled with profitability, we expect Lyft to be free cash flow positive throughout the next 10 years.

We don't believe Lyft has an economic moat. Lyft remains heavily reliant on a single business segment—mobility solutions—and has been unable to differentiate or expand meaningfully.

The network effect can be thought of loosely as supply informing demand and demand informing supply. For Lyft, supply is drivers, and demand is riders. Ride-hail companies like Lyft and Uber incentivize drivers (supply-side) by creating a marketplace where drivers can earn wages. At the same time, ride-hail marketplaces provide on-demand transportation for riders (demand-side). Ride-hailing companies aim for their networks to achieve a reinforcing cycle in which the marketplace's value proposition increases with each additional user. As a bonus for data-heavy businesses, indirect network effects can arise when more data is collected and used to improve the core product. In the ride-hail industry, an example of indirect network effects is incremental data collection with each ride, then using the data to improve pricing and routing algorithms, increasing the core product's value proposition. Unfortunately, Lyft has failed to ignite a virtuous cycle and lacks the critical mass needed for network effects to become self-sufficient.

To reach our no-moat conclusion, quantifying network effects is imperative. We quantify network effects by looking at core user base growth (MAPC, or monthly active platform consumers), engagement trends (frequency or trips per MAPC), monetization trends (revenue per trip), and incremental profit margin gains. These metrics paint a picture of struggle. On core user base growth, Lyft’s stagnant and lower absolute growth rates ranging from 7-12% (versus an average of 14.5% for Uber) since mid-2022 emphasize its inability to attract new users at a competitive pace. Lyft has the lowest engagement per user, with the slowest growth relative to Uber and DoorDash.

On monetization, Lyft has higher revenue per rider than Uber in aggregate, but this requires nuance because Uber’s monetization is skewed downward by its geographical diversity. Most concerning is Lyft's extremely volatile monetization, showing a willingness to change course at the drop of a dime to maintain its diminutive market share, creating a downward trend in incremental margins. Lyft is unable to achieve cost efficiencies or leverage its network effectively. We believe the poor incremental margins signal weakening network effects. Combined with subpar user-base growth and poor engagement, this leads to our no-moat conclusion.

We also examined New York City data to support our no-moat conclusion. NYC publishes granular monthly statistics on paid rides, and we analyzed more than one billion line items across multiple years. Our study shows that Lyft has lost market share at an alarming rate of 1% per year since 2020, while Uber and Yellow Cabs have gained 0.24% and 0.73% annually, respectively. Lyft has also generated less revenue per mile relative to Uber. Our base case is that this stagnant-growth trend will persist, leaving Lyft unable to attract users at scale and effectively capping direct and indirect network effects.

Lyft’s lack of scale also diminishes its value proposition to major autonomous vehicle companies, putting it at a disadvantage compared with Uber amid a potential technological inflection point for the industry. Lyft’s marginalized scale reduces the perceived value of its demand aggregation capabilities given that Uber has about 10 times as large a network.

Lyft is receiving nascent advertising revenue through Lyft Media, which offers potential avenues for margin expansion. However, Lyft’s advertising initiative could shift its emphasis to short-term profitability at the expense of the user experience, a risk given the early stage of this venture. Most consumers view ride-sharing as a utilitarian service, so unwanted pop-ups could drive users away. Uber believes this is a major obstacle and is unwilling to implement ads in ride-sharing engagements.

Ultimately, Lyft’s challenges in growing its core user base, scaling, driving engagement, and achieving stable monetization cast significant doubt on its ability to generate economic value. Our projections indicate returns on invested capital will remain below our estimate of Lyft’s cost of capital through most of the next decade, with a five-year forecast adjusted ROIC of 7%.

Lyft’s partnerships with nascent autonomous vehicle companies like May Mobility and Mobileye create upside to current unit economics by removing human drivers.

Lyft’s partnership model with public transit can result in a harmonious and symbiotic relationship with the cost-conscious consumer.

Lyft’s partnership with DoorDash should drive further in-app engagement. More engagement would help capture commuters' mindshare.

Lyft’s core user base growth and scale are significantly lower than Uber’s. As such, Lyft has a weak value proposition for major autonomous vehicle companies.

Autonomous vehicle companies could build an exclusive platform and remove Lyft from the ride-hailing marketplace equation.

Lyft has volatile, downward-trending incremental margins, indicating low pricing power.