Seo Ecommerce

E-commerce SEO Analysis

Shared Data Cache

Step 0 -- Check shared data cache:

Before gathering, check .seo-cache/ for reusable context from related SEO skills. Reference: ../seo/references/shared-data-cache.md for schemas and dependency map.

Check these cache files when present:

• .seo-cache/site-meta.json for domain, business type, industry, and crawl context
• .seo-cache/audit-scores.json for prior full-audit priorities
• .seo-cache/pages/{url-slug}/page-analysis.json for page-level context when a URL is provided

• If found: parse and use clearly valid fields (note "Using cached [X] from [date]")
• If missing, corrupt, or irrelevant: continue with fresh evidence
• If the user says "refresh" or "re-run": ignore cache reads and overwrite on write

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. python scripts/fetch_page.py <url>         → raw HTML
2. python 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

---

2. Google Shopping Intelligence (DataForSEO Merchant API)

Live competitive analysis from Google Shopping results.

Cost Guardrail (MANDATORY)

Before EVERY Merchant API call:

python 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:

python scripts/dataforseo_costs.py log merchant_google_products_search <cost>

Workflow

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

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

# Normalize results for analysis
python 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.

---

3. Amazon Marketplace (DataForSEO)

Cross-marketplace intelligence comparing Google Shopping and Amazon.

Cost Guardrail (MANDATORY)

python 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
python scripts/dataforseo_merchant.py search "<keyword>" --marketplace amazon

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

Cross-Marketplace Report

---

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 2. Fetch Google Shopping presence via Merchant API: merchant_google_products_search for top organic keywords 3. 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.

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

---

Cross-Skill Integration

---

Error Handling

---

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`

Write to shared data cache

After completing all work, write a concise JSON summary to .seo-cache/ when the workflow produced durable findings. Use the schemas and naming rules in ../seo/references/shared-data-cache.md; include at least cache_type, analyzed_at, source URL/domain, key findings, issues, recommendations, and tool limitations. Add .seo-cache/ to .gitignore if it is missing.

DataForSEO Merchant API Reference

Endpoint details for Google Shopping and Amazon marketplace data.

Endpoints

Google Shopping Products

Parameters:

• keyword (required) -- search query
• location_code (default: 2840 = US) -- DataForSEO location ID
• language_code (default: "en") -- language
• price_min / price_max (optional) -- filter by price range
• sort_by (optional) -- "relevance", "price_low_to_high", "price_high_to_low", "rating"
• depth (optional, default: 100) -- number of results

Response fields:

• title -- product listing title
• price -- numeric price value
• currency -- currency code (USD, EUR, etc.)
• seller -- merchant name
• rating -- product rating (float, 0-5)
• reviews_count -- number of reviews
• url -- product listing URL
• image_url -- product image URL
• availability -- "in_stock", "out_of_stock", "preorder"
• delivery_info -- shipping details text
• product_id -- Google Shopping product ID

Google Shopping Sellers

Parameters: Same as products search.

Response fields:

• seller_name -- merchant name
• seller_rating -- merchant rating (float)
• seller_reviews_count -- merchant review count
• price -- price offered by this seller
• delivery_info -- shipping and delivery text
• url -- seller listing URL

Amazon Products

Parameters:

• keyword (required) -- search query
• location_code (default: 2840 = US)
• language_code (default: "en")
• depth (optional, default: 100)
• sort_by (optional) -- "relevance", "price_low_to_high", "price_high_to_low", "avg_customer_review"

Response fields:

• title -- product title
• price -- numeric price
• currency -- currency code
• seller -- seller/brand name
• rating -- star rating (float, 0-5)
• reviews_count -- review count
• url -- Amazon product URL
• image_url -- product image
• availability -- stock status
• asin -- Amazon Standard Identification Number
• is_prime -- Prime eligibility (boolean)
• is_best_seller -- Best Seller badge (boolean)

Task/Poll Pattern

All Merchant endpoints use the standard DataForSEO queue pattern:

1. POST task with parameters to create endpoint 2. Poll for results with exponential backoff (2s, 4s, 8s, max 60s) 3. GET completed results by task ID

This saves 60-80% compared to live endpoints.

Rate Limits

• Max 2000 tasks per minute (across all endpoints)
• Max 30,000 tasks per day on standard plans
• Backoff on HTTP 429: wait 60 seconds, then retry

Data Normalization

When consuming responses, normalize:

Use scripts/dataforseo_normalize.py --module merchant for automatic normalization.

Cost Reference

See skills/seo-dataforseo/references/cost-tiers.md for the full pricing table, budget presets, and cost reduction tips. All Merchant endpoints are $0.02/call on standard queue.