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Went with month-over-month percentage change as the baseline, then started layering in cohort breakdowns and new vs.
Start by clarifying the product context and what 'revenue growth' means (e.g., month-over-month percentage change). Then outline a structured method: define the metric, gather and validate data, compute growth, and analyze drivers and segments to provide actionable insights.
Pro tip: Emphasize data quality and seasonality adjustments; showing awareness of these demonstrates engineering rigor and business acumen. Also, tie the analysis to a decision or action to show impact.
Clarify what revenue growth means (e.g., MoM percentage change) and the product boundaries (e.g., which revenue streams to include). Confirm the time period and any exclusions (e.g., one-time charges).
Collect monthly revenue data from reliable sources (e.g., billing system, data warehouse). Validate for completeness, accuracy, and consistency (e.g., check for missing months, currency issues).
Compute month-over-month growth rate using the formula: ((Current Month Revenue - Previous Month Revenue) / Previous Month Revenue) * 100. Consider also calculating absolute growth and compound monthly growth rate (CMGR) for trends.
Break down growth by dimensions such as customer segment, geography, product tier, or acquisition channel. Identify key drivers (e.g., new customers, upsells, churn) and investigate anomalies.
Summarize findings, adjust for seasonality if needed, and provide actionable recommendations (e.g., double down on high-growth segments, address churn).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.