Strategy question
Lyft wants to add Shared Saving rides. What factors will you consider to determine riders' willingness to pay? What experiments will you run to test your assumptions?
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What this question tests
Pricing and demand testing strategy for a new lower cost shared ride product, identifying real willingness to pay drivers.
How to approach it
- Identify factors affecting willingness to pay, price sensitivity of the rider segment, tolerance for a longer or shared route, and the size of savings versus a standard ride.
- Consider trip context, willingness to accept a shared, cheaper ride likely varies by trip purpose, commuting versus an airport trip.
- Propose experiment one, a price elasticity test, offering different discount levels for the shared option and measuring uptake rate at each price point.
- Propose experiment two, a route tolerance test, measuring how added detour or wait time from sharing affects uptake and cancellation, to find the acceptable delay threshold.
- Define the decision metric, the discount and delay combination that maximizes overall marketplace revenue without pushing standard ride riders to switch down.
What a strong answer includes
- Segments willingness to pay by trip context explicitly, commute versus airport versus leisure, rather than assuming one flat price sensitivity across all riders.
- Proposes two distinct, specific experiments, a price elasticity test and a delay tolerance test, rather than one vague test pricing statement.
- Names the real business risk, cannibalization of full price rides by price sensitive existing riders switching to the cheaper shared option, and proposes measuring it directly.
Common mistakes
- Treating all riders as having the same willingness to pay regardless of trip purpose or urgency.
- Proposing only a price test with no consideration of delay or detour tolerance, the other core lever in a shared ride product.
- Ignoring cannibalization risk from existing full price riders switching down to the cheaper option.
Likely follow-up questions
- How would you prevent this product from cannibalizing higher margin standard rides?
- How would you set the initial discount level before you have real elasticity data?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop