Uber vs. Lyft IPO: Timely Insights from Text Data

SumUp Analytics
May 19 · 2 min read

sumup.ai, May 2019

Uber and Lyft were two highly anticipated tech IPOs of 2019. In recent years, investors are analyzing huge volumes of text data — company annual reports, press releases, news, and even social media data — in order to gain that investment advantage.

Leveraging Nucleus, our high-speed text-analytics platform, we extracted key topics from the Uber and Lyft S1 documents and found some expected similarities, but also contrasting differences, all in mere seconds.

S1 documents are regulatory filings in anticipation of an IPO and are typically 1) lengthy — hundreds of pages 2) very complex — containing legal, financial, and company-specific terminology, and 3) very noisy — the reader doesn’t know ahead of time what to look for.

Within any S1 filing, we expected to extract commonly discussed themes, such as: [common-stock] [financial-condition] [preferred stock] [condition-operations] [adversely-affect] [business-financial]

Diving deeper, however, the interesting result for investors is what the key topics revealed about Lyft versus Uber’s respective business strategies:

  • Lyft: [bikes-scooters] [network-shared] [qualified-drivers][attract-retain] [riders-platform] [law-regulation] [business-risk factors] [executive-officer]
  • Uber: [Uber-eats] [bikes-scooters] [driver-incentives] [personal-mobility] [consumers-restaurants] [shippers-carriers] [operations-income][autonomous-vehicles]

For Lyft, their network of bikes and scooters are highlighted as a key topic. Given that the barrier for entry is low for such operations, investors should question this business model and its sustainability.

Also, given the nature of the ride-sharing business, regulatory risk continues to be very significant and evolving. However, Lyft’s documents suggest a passive, non-proactive approach to this key risk. It is important for Lyft to highlight their competitive advantages in relation to Uber, and the stability of their executive management is certainly a very big one.

In contrast, Uber sees UberEats and their network of drivers, consumers, restaurants, shippers, carriers, e-bikes and e-scooters, as well as underlying data, technology, and shared infrastructure as a significant business advantage. Tied to the topic of operations, we find that Uber’s joint venture with Yandex Taxi and the discontinuation of business in China to be important factors. The pursuit of autonomous vehicles also appears as a major area of focus for Uber.

Finally, for both Lyft and Uber, driver qualification and retention are vital areas of focus. This makes a lot of sense given that the two companies are competing for the same pool of available drivers and a critical business risk to monitor for investors.

With advents in text analytics, investors can now extract these crucial insights in seconds rather than hours.

SumUp Analytics

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