Lyft Business Metrics Calculation and Understanding Questions

Finance and operations-focused interview topic about calculating and interpreting core business metrics and KPIs for a platform-based business (e.g., ride-hailing). Covers definitions and formulas for metrics such as CAC, LTV, gross margin, contribution margin, revenue per user, driver utilization, and cost per ride; data sources (ride data, marketing spend, driver and rider activity); dashboard design; segmentation and cohort analysis; and using metrics to drive pricing, incentives, growth, and operational decisions.

HardTechnical

50 practiced

You found a significant reporting error that affects quarterly investor metrics. How would you lead the discovery, remediation, and communication process? Describe steps to own the issue, coordinate with finance/legal/leadership, timeline estimates, and how you would prevent recurrence.

HardTechnical

51 practiced

Describe how you would build a forecasting model to predict cohort LTV for riders using survival analysis or probabilistic models. Explain feature selection, censoring handling, model choices (e.g., Kaplan-Meier, Pareto/NBD), evaluation metrics, and how to serve the forecasts in dashboards.

HardTechnical

55 practiced

Write a single ANSI SQL query (or explain a single-query approach) to compute contribution margin per city per week given these tables:

trips(trip_id, city, occurred_at, gross_fare, discount_amount)driver_payouts(trip_id, driver_payout)incentives(trip_id, incentive_amount)platform_variable_costs(trip_id, other_variable_cost)

Contribution margin = net_revenue - (driver_payout + incentive_amount + other_variable_cost). Explain handling of nulls and refunds.

MediumTechnical

53 practiced

The product team proposes a 5% increase in base fares. As a BI analyst, describe which metrics you would simulate to estimate the impact on demand, revenue, driver supply, and rider satisfaction. Outline an experiment design or modeling approach to validate the change before full rollout.

MediumTechnical

38 practiced

Outline the SQL and analytical steps to compute CAC payback period by marketing channel. Use these tables:

marketing_spend(channel, date, amount)installs(user_id, install_date, channel)revenue(user_id, date, amount)

Define payback period as number of days from install until cumulative revenue from that user equals CAC allocated to that user. Describe assumptions and a sample SQL approach to aggregate to channel-level payback.

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