seo-ecommerce
agricidaniel/claude-seo
Analyze product pages, Google Shopping visibility, and marketplace SEO with schema validation and competitor pricing.
What is seo-ecommerce?
Comprehensive e-commerce SEO analysis covering on-page product optimization, Google Shopping and Amazon marketplace intelligence, keyword gap identification, and product schema validation. Use when optimizing product listings, analyzing shopping ads visibility, or comparing marketplace performance.
- On-page product SEO analysis with checklist covering titles, meta descriptions, images, schema, and content quality
- Google Shopping competitive analysis including pricing intelligence, seller landscape, and listing quality benchmarks
- Amazon marketplace cross-comparison and keyword visibility across platforms
- Keyword gap detection between organic and Shopping visibility to identify optimization opportunities
- Product schema validation and enhancement with required and recommended properties for rich results
- Marketplace keyword analysis with pricing, ratings, and seller distribution metrics
How to install seo-ecommerce
npx skills add https://github.com/agricidaniel/claude-seo --skill seo-ecommerce- DataForSEO API key (optional for standalone on-page analysis; required for Shopping and Amazon data)
- Python 3.x environment with scripts for page rendering and HTML parsing
- Google Merchant Center feed access (for implementing Shopping recommendations)
How to use seo-ecommerce
- 1.Run `/seo ecommerce <url>` on a product page to get on-page SEO analysis with scoring across schema, titles, images, and content
- 2.Use `/seo ecommerce products <keyword>` to fetch Google Shopping competitive data including pricing, sellers, and ratings
- 3.Execute `/seo ecommerce gaps <domain>` to identify keywords visible organically but missing from Shopping, or vice versa
- 4.Run `/seo ecommerce schema <url>` to validate product schema markup and receive enhancement recommendations
- 5.Review cost guardrails via `dataforseo_costs.py check` before running Merchant API calls to control spending
Use cases
- Optimize a product page for Google Shopping eligibility and organic search ranking
- Analyze competitor pricing and seller dominance for a product category on Google Shopping and Amazon
- Identify keywords ranking organically but missing from Google Shopping feed to expand paid visibility
- Validate and enhance product schema markup to improve rich snippet eligibility
- Compare marketplace performance across Google Shopping and Amazon for the same product keyword
- E-commerce product managers optimizing shopping feed performance
- SEO specialists managing product page rankings and schema markup
- Marketplace sellers analyzing competitive pricing and visibility
- Digital marketers running Google Shopping campaigns
- Content strategists identifying keyword opportunities across channels
seo-ecommerce FAQ
No. On-page product analysis, schema validation, and basic SEO checks work standalone. DataForSEO Merchant API is optional but required for live Google Shopping, Amazon data, and keyword gap analysis.
Before each Merchant API call, the skill checks `dataforseo_costs.py` for approval status. If cost is high, it asks for user confirmation before proceeding. After each call, it logs the cost to prevent budget overruns.
Yes. Use `/seo ecommerce products <keyword> --marketplace amazon` for Amazon data, then use the compare function to see pricing, ratings, and seller distribution across both platforms.
It identifies four gap types: Organic Only (create Shopping feed), Shopping Only (create organic content), Both Present (optimize consistency), and Neither (low priority). Includes volume and CPC data for prioritization.
Required: name, image, description, brand, offers (with price, currency, availability, seller). Recommended: sku, gtin, mpn, aggregateRating for enhanced rich results.
Full instructions (SKILL.md)
Source of truth, from agricidaniel/claude-seo.
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: "2.2.0" 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 |
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
| 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 |
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.
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
| Metric | Google Shopping | Amazon |
|---|---|---|
| Avg price | $ | $ |
| Median rating | X.X | X.X |
| Avg review count | N | N |
| Top seller share | % | % |
| Free shipping % | % | % |
4. Marketplace Keyword Gaps
Identify mismatches between organic and Shopping visibility.
Workflow
- Fetch organic rankings via seo-dataforseo:
dataforseo_labs_google_ranked_keywordsfor domain - Fetch Google Shopping presence via Merchant API:
merchant_google_products_searchfor top organic keywords - Cross-reference results
Gap Types
| Gap Type | Meaning | Action |
|---|---|---|
| Organic Only | Ranks organically but no Shopping ads | Create Google Merchant Center feed, bid on these keywords |
| Shopping Only | Shopping visibility but weak/no organic | Create content (buying guides, comparison pages) for these keywords |
| Both Present | Visible in both channels | Optimize: ensure price consistency, enhance schema |
| Neither | No visibility in either | Low priority unless high volume |
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 identifiergtin13/gtin14/mpn-- global trade identifiersaggregateRating-- star rating + review countreview-- individual reviews (minimum 1)color,material,size-- variant attributesshippingDetails-- ShippingDetails with rate and delivery timehasMerchantReturnPolicy-- MerchantReturnPolicy with type and days
Validation Rules
pricemust be a number string, not "$29.99" (no currency symbol)availabilitymust use full Schema.org URL enumimageshould be array with >= 1 high-res image URLpriceCurrencymust be ISO 4217 (USD, EUR, GBP)brand.namemust not be empty or "N/A"- Dates in
priceValidUntilmust be ISO 8601 - If
aggregateRatingpresent:ratingValueandreviewCountrequired
Schema Scoring
| Completeness | Score |
|---|---|
| All required fields | 50/100 |
| + aggregateRating | 65/100 |
| + sku/gtin/mpn | 75/100 |
| + shippingDetails | 85/100 |
| + merchantReturnPolicy | 90/100 |
| + reviews (3+) | 100/100 |
Cross-Skill Integration
| Skill | Integration Point |
|---|---|
| seo-schema | Delegates Product schema generation; reuses validation logic |
| seo-images | Product image audit (alt text, format, dimensions) — plus DigitalSourceType: TrainedAlgorithmicMedia IPTC label for AI-generated product images (Merchant Center requirement) |
| seo-content | Product description E-E-A-T and uniqueness analysis |
| seo-dataforseo | Organic keyword rankings for gap analysis |
| seo-technical | Core Web Vitals for product pages (LCP on hero image) |
| seo-google | Google Merchant Center feed validation via GSC |
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.
Error Handling
| Error | Cause | Response |
|---|---|---|
| No Product schema found | Page lacks JSON-LD | Analyze page content, generate recommended schema |
| DataForSEO credentials missing | Env vars not set | Run analysis without marketplace data, note limitation |
| Cost check blocked | Daily budget exceeded | Inform user, offer free-only analysis |
| Empty Shopping results | No products for keyword | Suggest broader keyword, check location settings |
| Amazon API timeout | Network/rate limit | Retry with backoff, fall back to Google-only |
| Invalid URL | Malformed input | Validate via google_auth.validate_url(), show error |
| Non-product page | URL is category/homepage | Detect page type, suggest /seo ecommerce schema instead |
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`
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