How to Get Started with Store Benchmark Analysis in Your AI Workflow

Store Benchmark Analysis is a powerful AI agent skill that extends your assistant with new capabilities. Store Benchmark analysis tool. Compare with other stores in the group/region and analyze store level, ranking changes, unit price × joint rate matrix quadrant. Core capabilities: 1. Multi-dimensional comparison scope (all groups, regions, provinces, cities) 2. Store level evaluation (based on sales, number of orders, unit price per customer, and linkage rate) 3. Tracking of ranking changes (ranking in this period vs. ranking in the previous period) 4. Unit price × linkage rate matrix quadrant analysis (identification door... This guide walks you through installing Store Benchmark Analysis, configuring it for your setup, and running your first commands — so you can start getting value in minutes.

Step-by-Step Guide

1. 1

   Install Store Benchmark Analysis: npx clawhub@latest --dir ~/.claude/skills install retail-store-benchmark-analysis

2. 2

   Restart your AI client (Claude Code, Cursor, Gemini CLI, or OpenClaw)

3. 3

   Type a natural language request related to data & analytics to trigger Store Benchmark Analysis

4. 4

   Review the output and refine your prompt for better results

5. 5

   Combine Store Benchmark Analysis with other skills to build multi-step workflows

Example Prompts

Copy these prompts and use them with your AI agent after installing Store Benchmark Analysis

More Use Cases for Store Benchmark Analysis