Estimation question
What is the size of the micromobility market in the United States?
- Lime
- Estimation
- Medium
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What this question tests
Whether you can size a market using ridership, pricing, and geographic coverage assumptions rather than a guess.
How to approach it
- Clarify scope: revenue from e-scooter and e-bike rentals across US cities where services currently operate, not a future potential size.
- Estimate the number of US cities with active micromobility service and average population per city currently served.
- Estimate ridership: average rides per day per served city, and average revenue per ride based on known typical per-minute pricing.
- State each assumption clearly, such as roughly 100 major cities served, and a few thousand rides per day in an average-sized market.
- Multiply rides per day by revenue per ride by number of served cities, then scale to an annual figure.
- Present the result as a range and flag ridership per city as the most uncertain, most sensitive assumption.
What a strong answer includes
- Builds the estimate from ridership and per-ride revenue rather than guessing a total dollar figure directly.
- States a labeled assumption for served cities and average rides per city, grounding the estimate in a defensible structure.
- Uses known typical per-minute or per-ride pricing as an anchor instead of an arbitrary revenue-per-ride number.
- Flags ridership per city as the most sensitive assumption, since it varies hugely between dense and sparse markets.
Common mistakes
- Giving a single guessed total with no visible ridership or pricing structure behind it.
- Ignoring that ridership varies enormously between dense urban markets and smaller cities.
Likely follow-up questions
- How would this estimate change if you included both scooters and e-bikes as separate categories?
- Which assumption would you most want real data on to sharpen this number?
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More questions from Lime
Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop