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Microsoft·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Microsoft analytics interview with a revenue growth question. Not much context to go on but it felt like a product metrics case.

Questions Asked (1)

Q1

How would you calculate or analyze monthly revenue growth for a product?

Product Analytics & MetricsPricing & Monetization
Author's notes

Went with month-over-month percentage change as the baseline, then started layering in cohort breakdowns and new vs.

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AI HintsAI Generated

Suggested Approach

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.

1. Define the Metric and Scope

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).

2. Gather and Validate Data

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).

3. Calculate Growth

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.

4. Analyze Drivers and Segments

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.

5. Interpret and Recommend

Summarize findings, adjust for seasonality if needed, and provide actionable recommendations (e.g., double down on high-growth segments, address churn).

Key Points to Mention

  • Month-over-month (MoM) growth formula and alternative metrics like CMGR
  • Data sources and validation (e.g., SQL queries, ETL pipelines)
  • Segmentation analysis (e.g., by customer cohort, product line)
  • Seasonality and external factors (e.g., holidays, promotions)
  • Statistical significance and confidence intervals for growth rates
  • Actionable insights and business impact

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.