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. 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

---

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.

---

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 %	%	%

---

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

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.

Confirmed Required Properties (Google Merchant)

Confirmed required fields are name, image, and offers; use Offer, not AggregateOffer, for merchant listings.

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

Recommended Properties (Enhance Rich Results)

• sku -- product identifier
• description, brand, offers.seller -- recommended context fields
• 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 (merchant-level shipping via ShippingService is also supported; shipping/returns can be set in Search Console without a Merchant Center account)
• hasMerchantReturnPolicy -- MerchantReturnPolicy with type and days
• hasAdultConsideration -- required for adult-oriented products (added 2026-05-20 to Product variant / Merchant listing); Google Search supports only the value https://schema.org/SexualContentConsideration
• category -- Text, CategoryCode, or an array mixing both. Use custom text for merchant-defined product types and CategoryCode with Google's taxonomy URL plus codeValue for Google Product Categories.

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. If brand is present, brand.name must not be empty or "N/A"
6. Sale periods use validFrom plus either validThrough or priceValidUntil, in ISO 8601 format. Include time and timezone when known.
7. If aggregateRating present: ratingValue and reviewCount required
8. Do not include fake reviews or undisclosed incentivized reviews in visible content or structured data. Clearly and prominently disclose incentives.

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	GSC indexation + Performance data for product URLs (NOT Merchant Center feed validation, that is done in Merchant Center / the Merchant API; the legacy Content API for Shopping sunsets 2026-08-18)

UCP: Universal Commerce Protocol (live)

Google-initiated open standard (co-developed with Shopify, Etsy, Wayfair, Target, Walmart; payment partners Visa/Mastercard/Stripe/Adyen/Amex) for letting AI agents discover, negotiate, and transact with merchants without one-off integrations. Google confirms a first reference implementation for conversational buying in AI Mode in Search. Broader Universal Cart rollout details are reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned source. ucp.dev lists 2026-04-08 as the latest release in its date-based versioning scheme, not 1.0; two integration paths: Native (default) and Embedded (approved merchants). Pairs with AP2 (reportedly moving toward FIDO governance). Canonical: developers.google.com/merchant/ucp and ucp.dev.

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
claude-seo run ucp_check.py https://store.example.com --json

# With endpoint reachability probes (HEAD each declared capability)
claude-seo run 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 itself is live; what's early is broad merchant adoption. Flag a literal "version": "1.0" as invalid (UCP versions are date-based, e.g. 2026-04-08).

---

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`