I jumped straight into segmenting the NPS data by customer type and purchase category, which felt right, but I spent too long on diagnosis and barely got to the actual improvement levers before time ran out.
Start by clarifying what NPS means for DoorDash and how it's measured, then break down the metric into its drivers (promoters, passives, detractors) and map them to the customer journey. Prioritize improvements using data and experimentation, and tie your approach to business impact like retention and order frequency.
Pro tip: Acknowledge that NPS is a lagging indicator and focus on leading indicators like order accuracy, delivery time, and Dasher communication that you can directly influence. Also, mention that you'd segment NPS by user cohorts (e.g., new vs. loyal, restaurant vs. grocery) to uncover specific pain points.
Clarify how NPS is calculated at DoorDash, what the current score is, and how it trends over time and across segments. Establish a baseline to measure improvement.
Analyze NPS survey verbatims and operational data to identify key drivers of detraction and promotion. Use cohort analysis to see which user groups have the lowest NPS and why.
Map drivers to the customer journey (ordering, delivery, support) and prioritize based on impact on NPS, effort, and alignment with business goals. Use a framework like RICE or impact/effort matrix.
Design A/B tests or pilot programs to address top drivers. Measure impact on NPS and other key metrics like retention and order frequency, and iterate based on results.
Roll out successful changes, continuously monitor NPS and leading indicators, and set up a feedback loop to sustain improvements.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.