Data Analysis AI prompts

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Complete “Multichannel Marketing Data Correlation with Revenue Attribution” with an analysis or query/formula plan with definitions, checks, findings, limitations and decision implications that can be checked against the supplied evidence.

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Implement cohort analysis across three dimensions—usage retention, cumulative revenue, and feature adoption—to identify which customer cohorts are most valuable, what differentiates users who stay from those who churn, and where to focus product and marketing efforts.

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Complete “LTV Calculation for SaaS: Models, Segmentation, and Growth Impact” with an analysis or query/formula plan with definitions, checks, findings, limitations and decision implications that can be checked against the supplied evidence.

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Create a Google Sheets pricing model that factors in variable costs, fixed costs, competitor prices, and minimum margin thresholds to generate optimal pricing recommendations for each SKU.

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Build an Excel-based HR dashboard that gives leadership real-time visibility into workforce metrics, identifies retention risk areas, and tracks diversity goals.

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Create a multi-project tracking system that gives PMO visibility into budget consumption, resource utilization, and delivery risk across the entire project portfolio.

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Build an RFM customer segmentation model in Excel that scores each customer on recency, frequency, and monetary value, then classifies them into segments with specific marketing strategies.

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Write SQL queries that reconstruct user journey funnels from event-level data, calculate step-by-step conversion rates, and identify the highest-impact drop-off points for optimization.

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Create a set of SQL monitoring queries that automatically detect data pipeline problems including missing data, schema changes, volume anomalies, and freshness issues.

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Use geospatial SQL functions to calculate distances between stores, analyze customer catchment areas, detect revenue cannibalization, and recommend optimal new store locations.

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Build SQL-based sessionization logic that groups raw events into meaningful sessions, reconstructs user paths, and calculates engagement metrics typically found in analytics platforms.

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Create a one-page KPI dashboard design that follows information hierarchy principles, uses visual encoding effectively, and enables executives to understand business health in under 30 seconds.

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Create waterfall visualizations that break down the difference between two financial states into contributing factors, enabling stakeholders to understand exactly what drove changes in revenue, margin, or profit.

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Build geographic dashboards that visualize data by region, state, or city, enabling regional managers to compare performance and identify geographic opportunities or problems.

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Create Sankey diagrams that show how customers flow through multiple stages or how revenue distributes across dimensions, revealing patterns that traditional charts miss.

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Create a comprehensive unit economics framework that answers the fundamental question: does each customer generate more value than it costs to acquire and serve them?

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Build a composite health score (0-100) that predicts customer churn risk, identifies expansion opportunities, and prioritizes Customer Success team efforts.

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Complete “North Star Metric Selection Framework for Product-Led Growth” with an analysis or query/formula plan with definitions, checks, findings, limitations and decision implications that can be checked against the supplied evidence.

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Create an engineering metrics dashboard that measures delivery performance, code quality, and team health without incentivizing harmful behaviors like velocity inflation or quality shortcuts.

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Create a repeatable WBR format that keeps leadership focused on the right metrics, drives accountability through action tracking, and enables rapid course correction.

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Complete “A/B Test Results Report with Statistical Rigor and Business Context” with an experiment design/readout with hypothesis, metrics, limitations and decision rules that can be checked against the supplied evidence.

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Create a systematic competitive intelligence framework that updates regularly, tracks competitor movements, and informs product roadmap and go-to-market strategy.

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Design a standardized quarterly board deck that tells a clear story about company performance, builds investor confidence, and facilitates strategic discussion rather than just reporting numbers.

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Complete “Data Cleanup Formula for HR metrics Sheet” with a spreadsheet formula or transformation plan with example inputs, expected outputs and validation checks that can be checked against the supplied evidence.

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Complete “Spreadsheet Automation for user behavior Data” with a spreadsheet formula or transformation plan with example inputs, expected outputs and validation checks that can be checked against the supplied evidence.

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Complete “Budget Tracker for sales performance Project” with a cost/budget/pricing worksheet with calculations, assumptions and sensitivity checks that can be checked against the supplied evidence.

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Complete “Google Sheets Setup for customer churn Team” with a spreadsheet formula or transformation plan with example inputs, expected outputs and validation checks that can be checked against the supplied evidence.

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Complete “Excel Dashboard for HR metrics Metrics” with a spreadsheet formula or transformation plan with example inputs, expected outputs and validation checks that can be checked against the supplied evidence.

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Complete “Macro Automation for marketing analytics Excel” with a spreadsheet formula or transformation plan with example inputs, expected outputs and validation checks that can be checked against the supplied evidence.

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Complete “Sales Report Excel for dashboard design” with a spreadsheet formula or transformation plan with example inputs, expected outputs and validation checks that can be checked against the supplied evidence.