Diagnose drop in shopper order acceptance

Question

Marketplace diagnosis case. An Instacart-like grocery-delivery marketplace sees Sunday afternoon shopper acceptance volume drop by roughly 2/3 relative to the usual baseline. Assume this is a same-day change, not a long multi-month trend. You can use standard marketplace logs: order creation / checkout, dispatch and offer events, acceptances, cancellations, ETAs, shopper app events, and merchant/store signals. Take the role of the on-call, bar-raiser-style interviewer and diagnose the problem.

1. Clarify the metric. Specify exactly what counts as an accepted order and which denominator(s) are relevant (e.g. accepted count vs. acceptance rate = accepted / offered). Provide a clean funnel decomposition.
2. Create a structured root-cause tree across three dimensions: (a) shopper supply / behavior, (b) customer demand / order mix, and (c) merchant / store operations and platform systems.
3. Enumerate the key metrics and slices you would check first (at least 10), and state what pattern in each would support or refute a hypothesis.
4. Differentiate a real behavioral change from a logging / measurement artifact — how would you confirm the drop is real?
5. Offer immediate mitigations and longer-term fixes, including at least one experiment or controlled rollout plan to test the leading hypothesis and prevent recurrence, and state the "next action" you would recommend. Overview: This PayPal data-scientist onsite analytics case involves a two-thirds drop in shopper order acceptance in a grocery-delivery marketplace on Sunday afternoon, and you must diagnose the cause. It assesses precise metric definition and funnel decomposition, supply/demand/merchant root-cause hypotheses, metric-driven investigation, ruling out logging artifacts, and proposing mitigations plus a switchback experiment.