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ecommerce-analyst

Analyze e-commerce performance data from CSV or Excel files.

Updated Feb 20, 2026
Search Tags:#A/B testing#metrics#data analysis#visualization#statistics#e-commerce
One-click install
npx skills add https://github.com/letitbk/cursor-setup --skill ecommerce-analyst-letitbk
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ecommerce-analyst
Source: https://github.com/letitbk/cursor-setup/tree/main/skills/ecommerce-analyst
Command: npx skills add https://github.com/letitbk/cursor-setup --skill ecommerce-analyst-letitbk

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, scipy, plotnine, openpyxl, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables e-commerce professionals to analyze sales and user metrics efficiently, facilitating data-driven decision making.

Core Features & Use Cases

  • Data Inspection: Quickly review CSV or Excel files to assess data quality and structure.
  • Metrics Calculation: Compute key performance indicators such as conversion rate, revenue, and LTV automatically.
  • Analysis & Visualization: Conduct funnel, cohort, and trend analyses to identify growth opportunities or issues.
  • Statistical Testing: Evaluate A/B test significance and confidence intervals for experimental data.
  • Reporting: Generate executive summaries with insights, charts, and recommendations for stakeholders.

Quick Start

Load your e-commerce dataset, then ask the AI to analyze it and generate insights by providing the data file path and requesting a report.

Frequently Asked Questions about ecommerce-analyst

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate e-commerce conversion rate and LTV from a sales CSV file?▼

To calculate e-commerce conversion rate and LTV from a CSV file, load your dataset and request metrics calculation. The system computes key performance indicators automatically to reveal revenue trends and user behavior for optimizing online stores.

Can I run A/B test significance testing on my e-commerce data using scipy?▼

Yes, you can run A/B test significance testing using scipy. The system evaluates statistical significance and confidence intervals for your experimental e-commerce data, helping you validate marketing strategies and identify growth opportunities.

What's the best way to visualize cohort and funnel trends in e-commerce metrics?▼

The best way to visualize cohort and funnel trends in e-commerce metrics is using plotnine. It generates visualizations from your dataset to identify user behavior patterns, growth opportunities, and potential issues in your online store.

Does this e-commerce analysis tool support Excel files or only CSV data?▼

This e-commerce analysis tool supports both Excel and CSV data. It inspects file structures and assesses data quality using pandas and openpyxl, allowing you to analyze sales and user metrics efficiently from either format.

How do I generate an executive summary report with insights from my online store data?▼

To generate an executive summary report with insights from your online store data, load your file and request a report. The system produces executive summaries with charts, metrics, and recommendations for stakeholders based on statistical tests.

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