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Data AnalysisClaude / ChatGPT (Code Interpreter)

Sales Data Analysis and Forecasting

Analyze historical sales data to identify trends, top performers, seasonality, and generate a 90-day forecast.

The Prompt

Analyze this sales data and provide a complete business intelligence report.

[PASTE YOUR SALES DATA HERE — CSV format preferred with columns: date, product, revenue, units, region, channel]

Perform the following analysis:

1. REVENUE TRENDS
   - Month-over-month growth rates
   - Quarter-over-quarter comparison
   - Year-over-year if data allows
   - Identify the inflection points (biggest growth or decline moments)

2. TOP PERFORMERS
   - Top 5 products by revenue
   - Top 5 products by units sold
   - Top 5 regions/channels
   - Identify any Pareto pattern (what % of products drive 80% of revenue)

3. SEASONALITY
   - Identify any recurring seasonal patterns
   - Best and worst performing months historically

4. FORECAST
   - 90-day revenue forecast using trend analysis
   - High/low confidence range
   - Key assumptions behind the forecast

5. ACTIONABLE RECOMMENDATIONS
   - Top 3 opportunities based on the data
   - Top 2 risks to watch

Format as an executive summary first (5 bullets), then detailed sections.
Create Python code to generate visualizations for each major finding.

Tips for Best Results

  • →Use ChatGPT Code Interpreter (Advanced Data Analysis) to run the Python and see charts
  • →Upload as CSV file rather than pasting for larger datasets

Tags

sales analysisforecastingbusiness intelligencePythondata visualization

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