← Clipboard Health Interview Insights
I went straight to demand elasticity and probably stayed there too long.
Start by clarifying the goal: maximize revenue, not just price. Then outline a data-driven framework that balances pricing levers with demand elasticity, rider and driver behavior, and long-term marketplace health. Emphasize experimentation and monitoring to avoid unintended consequences.
Pro tip: Frame revenue maximization as a two-sided marketplace problem: increasing rider prices can reduce demand and driver supply, so focus on net revenue and lifetime value, not just short-term gains.
Confirm whether the goal is short-term revenue or sustainable growth, and identify constraints like rider churn, driver supply, and brand perception.
Define metrics such as revenue per ride, total rides, rider acquisition/retention, driver utilization, and price elasticity to measure impact.
Examine historical pricing data, rider segments, demand patterns, and competitive pricing to determine which levers (e.g., base fare, surge, discounts) can be adjusted.
Propose A/B tests or multivariate tests to measure the effect of pricing changes on revenue and other metrics, ensuring statistical significance.
Continuously track outcomes, watch for unintended consequences (e.g., driver shortage), and refine the pricing strategy based on results.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.