Size opportunity for new product line

Q: Size opportunity for new product line

This question evaluates a data scientist's skills in financial opportunity sizing, sensitivity analysis, and experimental design by requiring quantitative modeling of impacted users, incremental orders, revenue, and gross profit for a proposed product line.

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Question

An e-commerce site considers adding a "Home Office" product line. Before any A/B test, size the opportunity and recommend whether to proceed. Assumptions (last quarter): 8M monthly active buyers; 30% browse adjacent categories monthly; their baseline purchase rate is 6%; AOV $60; gross margin 25%; expected attach of 0.5 items/purchase at$ 20/item; fixed setup cost $2M; variable cost$ 1 per browsing user reached; expected conversion uplift from better relevance and supply is +15% relative among the 30% segment. Tasks:

Estimate the monthly impacted population, incremental orders, revenue, and gross profit; include attach effect.
Compute break-even months and sensitivity to ±20% errors in AOV and uplift.
Identify the 3 most critical assumptions and how you would validate each with pre-experiment analyses (logs, surveys, cohort analysis) before committing engineering resources.
Propose the initial experiment design (targeting, success and guardrail metrics, exposure ramp) if the pre-test business case clears the hurdle.

Size opportunity for new product line

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