/seo-ecommerce

name: seo-ecommerce
description: >
  E-commerce SEO analysis: Google Shopping visibility, Amazon marketplace
  intelligence, product schema validation, competitor pricing analysis, and
  marketplace keyword gaps. Combines on-page product SEO with marketplace data
  from DataForSEO Merchant API. Use when user says "ecommerce SEO", "product SEO",
  "Google Shopping", "marketplace SEO", "product schema", "Amazon SEO",
  "product listings", "shopping ads", or "merchant SEO".
user-invocable: true
argument-hint: "<url or keyword>"
license: MIT
compatibility: "Enhanced with DataForSEO Merchant API (optional)"
metadata:
  author: AgriciDaniel
  original_author: "Matej Marjanovic (Pro Hub Challenge)"
  version: "2.2.4"
  category: seo

E-commerce SEO Analysis

Comprehensive product page optimization, marketplace intelligence, and competitive pricing analysis. Works standalone (on-page + schema) and with DataForSEO Merchant API for live Google Shopping and Amazon data.

Commands

| Command | Purpose | DataForSEO? | |---------|---------|-------------| | `/seo ecommerce <url>` | Full e-commerce SEO analysis of a product page or store | Optional | | `/seo ecommerce products <keyword>` | Google Shopping competitive analysis | Required | | `/seo ecommerce gaps <domain>` | Keyword gap: organic vs Shopping visibility | Required | | `/seo ecommerce schema <url>` | Product schema validation and enhancement | No |

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1. Product Page Analysis (No DataForSEO Needed)

Fetch and parse any product page for on-page SEO quality.

Workflow

1. claude-seo run render_page.py <url> --mode auto → raw/rendered HTML
2. claude-seo run parse_html.py --url <url>   → SEO elements
3. Analyze product-specific signals (below)

Product SEO Checklist

Title Tag

• [ ] Contains primary product keyword
• [ ] Includes brand name
• [ ] Under 60 characters (no truncation in SERPs)
• [ ] Format: `[Product Name] - [Key Feature] | [Brand]`

Meta Description

• [ ] Contains product keyword + benefit
• [ ] Includes price or "from $XX" (triggers rich snippet interest)
• [ ] Call-to-action present (Shop now, Buy, Free shipping)
• [ ] Under 155 characters

Heading Structure

• [ ] Single H1 matching primary product name
• [ ] H2s for: Features, Specifications, Reviews, Related Products
• [ ] No duplicate H1 tags across product variants

Product Images

• [ ] Alt text includes product name + distinguishing feature
• [ ] File names are descriptive (not `IMG_001.jpg`)
• [ ] WebP format served (with JPEG fallback)
• [ ] At least 3 images per product (hero, detail, lifestyle)
• [ ] Image dimensions >= 800px for Google Shopping eligibility
• [ ] Lazy loading on below-fold images only

Internal Linking

• [ ] Breadcrumb navigation: Home > Category > Subcategory > Product
• [ ] Related products section (cross-sell / upsell)
• [ ] Link back to category page with keyword-rich anchor
• [ ] Reviews section links to full review page (if separate)

Content Quality

• [ ] Unique product description (not manufacturer copy-paste)
• [ ] Word count >= 200 for product description body
• [ ] Specs table present (not just prose)
• [ ] User reviews on-page (UGC signals)

Scoring

| Category | Weight | Criteria | |----------|--------|----------| | Schema completeness | 25% | Required + recommended Product fields | | Title & meta | 15% | Keyword placement, length, format | | Image optimization | 20% | Alt text, format, sizing, count | | Content quality | 20% | Unique description, specs, reviews | | Internal linking | 10% | Breadcrumbs, related products, categories | | Technical | 10% | Page speed, mobile rendering, canonical |

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2. Google Shopping Intelligence (DataForSEO Merchant API)

Live competitive analysis from Google Shopping results.

Cost Guardrail (MANDATORY)

Before EVERY Merchant API call:

claude-seo run dataforseo_costs.py check merchant_google_products_search

• `"status": "approved"` -- proceed
• `"status": "needs_approval"` -- show cost, ask user
• `"status": "blocked"` -- stop, inform user

After each call:

claude-seo run dataforseo_costs.py log merchant_google_products_search <cost>

Workflow

# Product search: who sells what at what price
claude-seo run dataforseo_merchant.py search "<keyword>" --marketplace google

# Seller analysis: merchant ratings and dominance
claude-seo run dataforseo_merchant.py sellers "<keyword>"

# Normalize results for analysis
claude-seo run dataforseo_normalize.py results.json --module merchant

Analysis Outputs

Pricing Intelligence

• Price distribution: min, max, median, P25, P75
• Price outliers (> 2 standard deviations from median)
• Price-to-rating correlation
• Currency normalization to USD (or user-specified)

Seller Landscape

• Top 10 sellers by listing count
• Merchant rating distribution
• Free shipping prevalence
• New vs established sellers

Product Listing Quality

• Title keyword patterns in top listings
• Average rating and review count benchmarks
• Image count per listing
• Availability status distribution

Load `references/marketplace-endpoints.md` for full API parameter details.

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3. Amazon Marketplace (DataForSEO)

Cross-marketplace intelligence comparing Google Shopping and Amazon.

Cost Guardrail (MANDATORY)

claude-seo run dataforseo_costs.py check merchant_amazon_products_search

Amazon endpoints are in the `warn_endpoints` set -- always requires user approval.

Workflow

# Amazon product search
claude-seo run dataforseo_merchant.py search "<keyword>" --marketplace amazon

# Cross-marketplace comparison
claude-seo run dataforseo_merchant.py compare "<keyword>"

Cross-Marketplace Report

| Metric | Google Shopping | Amazon | |--------|---------------|--------| | Avg price | $ | $ | | Median rating | X.X | X.X | | Avg review count | N | N | | Top seller share | % | % | | Free shipping % | % | % |

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4. Marketplace Keywor