I went straight to data signals, cancellation rates, support tickets, that kind of thing.
Start by defining what 'negative member experience' means in the context of a rideshare membership program, then outline a data-driven approach to identify pain points across the member journey. Use a mix of quantitative metrics (e.g., churn, NPS, complaint rates) and qualitative signals (e.g., user feedback, support tickets) to pinpoint the most impactful negative experiences.
Pro tip: Tie negative experiences to business outcomes like retention and lifetime value to prioritize fixes that matter most. Show empathy for the member while balancing with company goals.
Clarify what constitutes a negative member experience (e.g., ride cancellations, long wait times, billing issues, poor driver interactions) and how it differs for members vs non-members.
List relevant data sources: app analytics (e.g., ride completion rate, time to match), customer support tickets, in-app ratings, surveys (NPS, CSAT), and churn data.
Analyze the data to find patterns and segment by member tenure, frequency, geography, etc. Use cohort analysis to see if negative experiences are concentrated in specific groups.
Prioritize negative experiences based on frequency, severity, and impact on key metrics like retention, member satisfaction, and lifetime value.
Validate findings with qualitative research (e.g., user interviews) and propose solutions or experiments to address the top issues.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.