seo-ecommerce skill

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

1. Product Page Analysis (No DataForSEO Needed)

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

Workflow

1. "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run render_page.py <url> --mode auto → raw/rendered HTML
2. "${CLAUDE_PLUGIN_ROOT}/scripts/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)
• [ ] High-resolution images: Google recommends at least 50K pixels (width x height) for merchant listings; larger (for example 800px+) is common practice, not a rule
• [ ] 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

2. Google Shopping Intelligence (DataForSEO Merchant API)

Live competitive analysis from Google Shopping results.

Cost Guardrail (MANDATORY)

Before EVERY Merchant API call:

"${CLAUDE_PLUGIN_ROOT}/scripts/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_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_costs.py log merchant_google_products_search <cost>

Workflow

# Product search: who sells what at what price
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_merchant.py search "<keyword>" --marketplace google

# Seller analysis: merchant ratings and dominance
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_merchant.py sellers "<keyword>"

# Normalize results for analysis
"${CLAUDE_PLUGIN_ROOT}/scripts/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.

3. Amazon Marketplace (DataForSEO)

Cross-marketplace intelligence comparing Google Shopping and Amazon.

Cost Guardrail (MANDATORY)

"${CLAUDE_PLUGIN_ROOT}/scripts/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_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_merchant.py search "<keyword>" --marketplace amazon

# Cross-marketplace comparison
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_merchant.py compare "<keyword>"

Cross-Marketplace Report

4. Marketplace Keyword Gaps

Identify mismatches between organic and Shopping visibility.

Workflow

dataforseolabsgooglerankedkeywords for domain

1. Fetch organic rankings via seo-dataforseo:

MCP tool; the cost-ledger key is merchantgoogleproductssearch): "${CLAUDEPLUGINROOT}/scripts/claude-seo" run dataforseomerchant.py search for the top organic keywords

1. Fetch Google Shopping presence through the Merchant REST script (not an

1. Cross-reference results

Gap Types

Output Format

## Keyword Gap Analysis: example.com

### Opportunities: Organic → Shopping (12 keywords)
| Keyword | Organic Pos | Volume | CPC | Recommended Action |
|---------|------------|--------|-----|-------------------|

### Opportunities: Shopping → Organic (8 keywords)
| Keyword | Shopping Rank | Volume | CPC | Content Type Needed |
|---------|-------------|--------|-----|-------------------|

5. Product Schema Enhancement

Validate and generate Product schema following Google's current requirements.