seo-ecommerce

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

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1. Product Page Analysis (No DataForSEO Needed)

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

Workflow

1. python3 scripts/render_page.py <url> --mode auto → raw/rendered HTML
2. python3 scripts/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

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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:

python3 scripts/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:

python3 scripts/dataforseo_costs.py log merchant_google_products_search <cost>

Workflow

# Product search: who sells what at what price
python3 scripts/dataforseo_merchant.py search "<keyword>" --marketplace google

# Seller analysis: merchant ratings and dominance
python3 scripts/dataforseo_merchant.py sellers "<keyword>"

# Normalize results for analysis
python3 scripts/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)

python3 scripts/dataforseo_costs.py check merchant_amazon_products_search

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

Workflow

# Amazon product search
python3 scripts/dataforseo_merchant.py search "<keyword>" --marketplace amazon

# Cross-marketplace comparison
python3 scripts/dataforseo_merchant.py compare "<keyword>"

Cross-Marketplace Report

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4. Marketplace Keyword Gaps

Identify mismatches between organic and Shopping visibility.

Workflow

1. Fetch organic rankings via seo-dataforseo:

dataforseo_labs_google_ranked_keywords for domain

1. Fetch Google Shopping presence via Merchant API:

merchant_google_products_search for top organic keywords

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 |
|---------|-------------|--------|-----|-------------------|

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5. Product Schema Enhancement

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

Required Properties (Google Merchant)

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "",
  "image": [""],
  "description": "",
  "brand": { "@type": "Brand", "name": "" },
  "offers": {
    "@type": "Offer",
    "url": "",
    "priceCurrency": "USD",
    "price": "0.00",
    "availability": "https://schema.org/InStock",
    "seller": { "@type": "Organization", "name": "" }
  }
}

Recommended Properties (Enhance Rich Results)

• sku -- product identifier
• gtin13 / gtin14 / mpn -- global trade identifiers
• aggregateRating -- star rating + review count
• review -- individual reviews (minimum 1)
• color, material, size -- variant attributes
• shippingDetails -- ShippingDetails with rate and delivery time
• hasMerchantReturnPolicy -- MerchantReturnPolicy with type and days

Validation Rules

1. price must be a number string, not "$29.99" (no currency symbol)
2. availability must use full Schema.org URL enum
3. image should be array with >= 1 high-res image URL
4. priceCurrency must be ISO 4217 (USD, EUR, GBP)
5. brand.name must not be empty or "N/A"
6. Dates in priceValidUntil must be ISO 8601
7. If aggregateRating present: ratingValue and reviewCount required

Schema Scoring

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Cross-Skill Integration

UCP — Universal Commerce Protocol (forward-looking)

Google-led standard (co-developed with Shopify, Etsy, Walmart, Wayfair, Visa, Mastercard, etc.) for letting AI agents discover, negotiate, and transact with merchants without one-off integrations. Already powers direct buying from AI Mode and Gemini.

Merchants already on Google Merchant Center with clean Product schema can declare a UCP profile at /.well-known/ucp listing capabilities (dev.ucp.shopping.checkout, .fulfillment, .discount). See references/ucp-universal-commerce-protocol.md for audit criteria, capability examples, and the relationship to AP2 (Agent Payments Protocol).

Audit command

# Discover and validate the UCP profile
python3 scripts/ucp_check.py https://store.example.com --json

# With endpoint reachability probes (HEAD each declared capability)
python3 scripts/ucp_check.py https://store.example.com --probe-endpoints --json

The script returns: profile presence, version, declared capabilities, structural issues (missing fields, unknown capability IDs), and (with --probe-endpoints) per-endpoint reachability. SSRF-blocked endpoints are reported explicitly. Missing profile is reported as opportunity, not failure — UCP adoption is early.

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Error Handling

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Output Template

## E-commerce SEO Report: [URL or Keyword]

### Overall Score: XX/100

### Product Page SEO
- Schema Completeness: XX/100
- Title & Meta: XX/100
- Image Optimization: XX/100
- Content Quality: XX/100
- Internal Linking: XX/100

### Marketplace Intelligence (if DataForSEO available)
- Google Shopping Listings: N products found
- Price Range: $XX - $XX (median: $XX)
- Top Seller: [name] (XX% market share)
- Amazon Comparison: [available/not checked]

### Top Recommendations
1. [Critical] ...
2. [High] ...
3. [Medium] ...

Generate a PDF report? Use `/seo google report`