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Ecommerce Competitor Analysis

nexscope-ai/ecommerce-skills

This does cross-platform competitive intelligence for ecommerce brands, pulling together what your competitors are doing on Amazon, Shopify, social media, and ad platforms into one coherent picture. You tell it who you're competing with and where they sell, it asks one follow-up to fill gaps, then delivers specific findings with prioritized actions. The multi-channel approach is the real value here since most competitor research tools silo themselves to one platform. Built by Nexscope, it covers eight platforms including TikTok Shop and Etsy. Useful when you need to understand competitive positioning across channels rather than obsessing over one marketplace in isolation.

skills.sh installs: 1.5K
GitHub stars: 1.4K
last updated: Aug 21, 2026

Install

$ npx -y skills add nexscope-ai/ecommerce-skills --skill ecommerce-competitor-analysis --agent claude-code

Installs into .claude/skills of the current project.

Files

E-commerce Competitor Analysis 🔍

Comprehensive cross-platform competitor intelligence. Analyze strategies, positioning, and performance across all channels.

Installation

npx skills add nexscope-ai/eCommerce-Skills --skill ecommerce-competitor-analysis -g

Usage Examples

Multi-platform competitor assessment:

"Analyze my top 3 competitors across Amazon, Shopify, and social commerce - where are they strongest?"

Strategic positioning analysis:

"Compare competitor strategies in the sustainable fashion space - pricing, messaging, and market positioning"

Channel performance evaluation:

"Which competitors are winning on TikTok Shop vs Amazon and what's their different approach?"

Core Capabilities

1. Cross-Platform Presence Analysis

Multi-channel footprint mapping and strategic assessment
Platform-specific performance and market share evaluation
Channel optimization and resource allocation analysis
Omnichannel strategy effectiveness assessment

SKILL.md on GitHub

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Details

Repository: github.com/nexscope-ai/ecommerce-skills
Category: Data Science & ML
First seen: Jun 3, 2026

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