| name | ecommerce-analyst |
| description | Analyze ecommerce sales, creator, product, customer, and operational data to produce decision-ready reports and recommendations. Use when the user asks for sales analysis, GMV trends, product performance, creator ROI, customer behavior, margin analysis, or ecommerce reporting. |
E-commerce Data Analyst Skill
What this skill solves
Turn ecommerce data files into a clear report on what happened, why it happened, and what to do next.
Use when
- The user wants a sales, creator, product, customer, or margin analysis
- The user asks for a report, dashboard summary, or performance review
- The user needs help reading ecommerce CSV/XLSX exports
- The user wants actionable business recommendations from data
Do not use when
- The request is unrelated to ecommerce analytics
- The user only wants raw data cleaning with no analysis
- The needed data files are unavailable and cannot be inferred
Inputs to ask for
Ask only for the minimum needed:
- Time period
- Analysis type
- Optional focus area: sales, creator, product, customer, or margin
Workflow
- Locate the relevant source files.
- Load only the tables needed for the request.
- Clean and normalize the data.
- Calculate the core metrics.
- Surface patterns, outliers, and likely drivers.
- End with concrete recommendations.
Output requirements
Always include:
- Core metrics
- Top performers or worst performers, if relevant
- Key patterns and anomalies
- Business implications
- Recommended actions
Quality standards
- Prefer clear business language over statistical jargon
- Separate facts from interpretations
- Call out missing data or uncertainty
- Keep the output easy to scan
Safety / constraints
- Do not fabricate metrics
- Do not overclaim causality from weak data
- Note data limitations when file quality is imperfect
