How to target commute coupon users?

You are a Data Scientist on the commute team at a ride-sharing company such as Lyft. The team wants to launch a coupon campaign to increase usage of commute rides, but the budget is limited, so coupons should be sent only to users who are likely to generate incremental value. Design an analysis plan to identify the best target users. Your answer should address: - How you would define the business goal of the campaign: ride conversion, retained commute usage, profit, or rider reactivation. - What data you would use, such as trip history, commute-time behavior, origin-destination regularity, prior coupon exposure, price sensitivity, rider tenure, geography, and supply constraints. - How you would distinguish users who would ride anyway from users whose behavior is likely to change because of the coupon. - What user segments you would consider, for example frequent commuters, occasional commuters, churn-risk users, new users, and highly price-sensitive users. - How you would estimate incremental lift rather than just predicting coupon redemption. - What success metrics you would use, such as incremental rides, incremental gross bookings, contribution margin, retention, and return on coupon spend. - What risks or confounders you would watch for, including selection bias, seasonality, weekday effects, geography, driver supply constraints, and cannibalization of full-price rides. - How you would validate the targeting strategy before a full launch, including experiment design and guardrail metrics. Be specific about the difference between targeting users who are likely to redeem a coupon and targeting users for whom the coupon creates true incremental impact.