Identify Key Drivers

Find what factors are driving a metric up or down and quantify their impact

🧪 Tested by a human Advanced 👤 Analyst 👤 Manager 👤 Executive
Analyse this data and identify the biggest drivers behind [METRIC — revenue growth / ticket volume / churn rate]. For each driver: quantify its impact, explain the mechanism, and suggest what we can do about it. Rank drivers by impact size. Create a chart showing the contribution of each driver.

Works on

⭐ M365 Copilot (Best)

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Tips for Best Results

  • The Analyst agent uses Python for statistical analysis behind the scenes
  • Include enough data columns — the more variables, the better the driver analysis
  • Add “State your confidence level for each finding” to set realistic expectations

📎 More Prompts

A/B Test Results Analyser

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Analyse this A/B test: Control [A METRICS] vs Variant [B METRICS]. Determine: (1) Statistical significance (p-value), (2) Confidence interval, (3) Effect size, (4) Sample size adequacy, (5) Winner recommendation with caveats, (6) Whether to continue testing.
⭐ M365

Analyse Dataset for Top Insights

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Analyse this data and give me the top [NUMBER — 3 / 5] insights. For each insight explain: what the data shows, why it matters, and what I should do about it. Include a supporting chart or visualisation for the most impactful finding. Write for [AUDIENCE — management / the team / a technical audience].
⭐ M365

Benchmark Comparison

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Compare our metrics against industry benchmarks. Our data: [PASTE KEY METRICS]. Industry: [INDUSTRY]. For each metric: (1) Our value, (2) Industry benchmark, (3) Percentile ranking, (4) Gap analysis, (5) Whether the gap matters and what to do about it. Flag where we significantly lag or lead.
⭐ M365
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