promptsDBText Analysis & GenerationData Analysis
Generate Business Insights Report from CSV Data
Parse CSV data to profile, compute key metrics, trends, segments, anomalies, and deliver a goal-aligned, quantified insights report with recommendations in a standardized structure.
Prompt Content
Act as a senior data analyst. Analyze the CSV below and produce a business insights report with key findings, trends, patterns, anomalies, and actionable recommendations aligned to the stated goals.
Instructions:
1) Parse the CSV (first row = headers). Infer data types; detect date/time columns. Profile data: row count, date range, missing values, duplicates.
2) Compute core metrics relevant to the goals/context (totals, means, rates, growth/decline). If a date column exists, show time trends; if categories exist, show top segments by volume/impact.
3) Identify patterns (seasonality, correlations) and anomalies/outliers; quantify impacts.
4) Produce the report using the structure below, quantifying each claim and adding brief calculation notes for non-obvious metrics.
Constraints:
• Base all insights only on the provided data; do not invent values.
• Keep tone clear, concise, decision-oriented.
• If data is insufficient for a requested analysis, state what's missing and how to obtain it.
• Tailor depth and emphasis to the business context and goals.
Report structure (use these exact section headings):
1) Executive Summary
2) Data Notes
3) Key Metrics Snapshot
4) Trends & Patterns
5) Segment Insights
6) Anomalies & Outliers
7) Drivers & Correlations
8) Actionable Recommendations
9) Risks & Limitations
10) Next Steps
11) Appendix: Methods & Calculations
<example>
Key Finding: Revenue +12.4% MoM, driven by Channel A (+$84k, +28%) while Channel B declined (-$19k, -7%).
Recommendation: Action - Shift 10-15% budget from Channel B to Channel A; Rationale - Higher ROAS (3.2 vs 1.6) and rising CVR; Expected impact - +5-8% revenue in 4 weeks; Metric - Revenue, ROAS, CVR; Effort - Low.
</example>
Inputs:
Business context:
<business-context>
Business Context
</business-context>
Goals:
<goals>
Goals
</goals>
CSV data:
<csv-data>
Csv Data
</csv-data>
Variables
- Business Context
- Brief context: industry, product, regions, key columns, definitions, timeframe.
- Example: E-commerce DTC; US/CA; weekly data; columns include date, channel, campaign, sessions, orders, revenue, cost, aov, region.
- Goals
- Specific decisions or questions the report must answer.
- Example: Find revenue drivers; compare channels; flag March anomalies; recommend actions to improve ROAS and conversion rate.
- Csv Data
- Paste the CSV data as plain text (first row headers).
- Example: date,channel,sessions,orders,revenue,cost 2025-03-01,Search,12000,360,54000,18000 2025-03-01,Social,8000,160,18400,12000