Yuvraj’s approach
Observed metric change: Reorder rate= % of customers who place another order within the same month. Change: 15% decline in vancouver in last 1 week.
Key segments to inspect: Customer: new vs repeat user, age groups Platform: ios, android, web Restaurant type: fast food vs premium dining time of day: breakfast, lunch, dinner, late night Availability: waiting time, cancellations, restaurants close
Possible causes: Operational issues: delivery delay, driver shortage, restaurant unavailable Product changes: new app updates, checkout issue, payment gateway Expternal factors: local events, weather disruption, competitor promotions, no discounts/coupons
User experience: price hike, bad food quality, negative reviews Data issue: inaccurate logs in system or miscounted re orders
Most likely root cause: For a localised issue, most probably it will be operational/ driver availability issues, weather disruption(restaurants not open)
How I would validate it: Segment analysis: compare reorder rates across cities operational metrics: check delivery times, cancellation rates, weather conditions and disruptions Competetive scan: Compare promotions and discounts by competitors App updates: check if recent updates caused any checkout or payment issues Reviews: check customer feedback to point out any specific negative tickets, etc
Recommended fix: Increase operational efficiency by having more driver count to fix shortage. Work with restaurants for menu availability and resuce cancellations. Custoemr recovery: target lost custoemrs with coupons, discounts to increase the average weekly/monthly spent back on track. Engagement: Use push notifications to attract customers