What to expect, what they’re really testing, and what a strong answer looks like — scored.
Ride-sharing marketplace, driver and rider experience, safety, and competitive positioning against Uber. Lyft PMs must think about how to differentiate in a commodity market and reason about the marketplace dynamics that affect driver supply and rider demand.
The question below was asked by Lyft interviewers. The answer is graded on the five dimensions real PM interviewers use: structure, specificity, reasoning, decision quality, and delivery.
“How would you improve Lyft's driver experience to reduce driver churn?”
Driver churn is a supply-side problem, and supply-side health is the constraint that limits Lyft's ability to serve riders. Understanding why drivers leave is the first step.
I'd segment churn by driver tenure: early churn (first 30 days), mid-tenure churn (1-6 months), and long-tenure drivers who leave after a year or more. These have different causes and different solutions.
Early churn is likely onboarding and earning expectations: drivers who signed up expecting $X per hour and earned $Y on their first week. I'd look at whether there's a gap between the earnings Lyft advertised in acquisition campaigns and what drivers actually earned in their first 30 days.
Mid-tenure churn is likely income volatility and driver-rider friction: drivers who've figured out the platform but find that inconsistent earnings or difficult passengers are not worth the stress.
For the highest-impact intervention, I'd target mid-tenure drivers with an income smoothing feature: a weekly earnings guarantee for drivers who complete a minimum number of trips. If a driver completes 30 trips in a week and earns less than $600 (the guaranteed floor), Lyft makes up the difference. This converts income volatility — the main unpredictable stressor — into a predictable floor.
This isn't free — it costs Lyft in high-volatility market conditions — but it's targetable: only activate the guarantee for drivers in their 1-6 month window, where churn is most preventable.
Success metric: 90-day driver retention rate for mid-tenure drivers who receive the guarantee vs. control group (primary). Secondary: number of trips completed per driver per week (are guaranteed drivers more active, since the guarantee reduces the risk of a slow week?).
Segments churn by tenure, explains different causes for each segment, and focuses on the highest-impact one.
Names the $600/30-trip example, 1-6 month window, and 90-day retention metric concretely.
Income volatility as the key mid-tenure driver stressor is correct and the guarantee is the right structural solution.
Commits to one intervention for a specific segment; acknowledges the cost and proposes how to make it economically sustainable.
Well-organized; the tenure segmentation adds structure without making the answer feel formulaic.
The tenure segmentation is the answer's best structural move — it correctly identifies that 'driver churn' is not one problem but three. Focusing on mid-tenure with an income guarantee is the right call because it addresses the most preventable churn. The cost acknowledgment and targeted activation window show business maturity. The weakness: the answer doesn't discuss how drivers would experience the guarantee (is it automatic? Do they need to opt in?) — the UX matters for whether drivers actually value it.
Add one sentence on guarantee UX: is the weekly floor automatically applied or opt-in? Argue for automatic application, since opt-in requires drivers to know about and trust a benefit they've never used.
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