Investigate why conversion fell after a Pickup launch

Problem Statement Description

Product context: DoorDash is a local commerce and delivery platform; its products include restaurant delivery, DashPass, grocery and retail delivery, merchant tools, and dasher tools.

DoorDash has recently launched or materially updated a Pickup experience, allowing customers to order from merchants and collect food or goods themselves instead of using delivery. Soon after launch, overall conversion for the Pickup flow fell, raising concern across product, merchant, operations, and marketplace teams.

You are asked to investigate the drop as the product manager responsible for understanding what happened and guiding the response. The issue may involve customer-facing funnel friction, merchant readiness, pricing or fees, availability, menu/catalog quality, store operations, app instrumentation, or marketplace-side effects. Your task is to frame the anomaly clearly, identify the most likely causes, and determine what evidence is needed before taking action.

Focus on how you would structure the RCA rather than jumping to a fix. Consider the end-to-end Pickup journey: discovery, merchant selection, menu browsing, cart, checkout, order confirmation, merchant preparation, and customer pickup. Also consider whether the apparent conversion decline is real, localized, segment-specific, or caused by measurement or experiment setup issues.

The investigation should consider:

- How to define “conversion” for Pickup, including numerator, denominator, funnel stage, time window, and comparison baseline.

- Which segments to inspect, such as new vs. returning users, geography, merchant type, cuisine/category, platform, traffic source, and order size.

- Instrumentation checks to confirm events, attribution, experiment assignment, eligibility, and funnel logging are accurate after launch.

- Funnel breakdowns to identify whether the drop occurs at discovery, store page, menu, cart, checkout, payment, or confirmation.

- Merchant-side factors such as pickup availability, store hours, prep times, item availability, menu accuracy, pricing, and operational readiness.

- Customer experience hypotheses, including unclear Pickup value proposition, fees or savings confusion, ETA accuracy, distance, store location, or trust concerns.

- Marketplace and business guardrails, including merchant ROI, support contacts, cancellations, refunds, delivery cannibalization, and customer retention.

- Mitigation and prevention steps, including severity assessment, rollback or ramp decisions, monitoring, stakeholder communication, and post-incident learning.

Your goal is to present a structured RCA approach that helps DoorDash determine whether the conversion drop is a true product or marketplace problem, where it is occurring, which users or merchants are affected, and what evidence would justify mitigation, rollback, or further iteration.