seo-ecommerce
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技能内容
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.jsonfor domain, business type, industry, and crawl context.seo-cache/audit-scores.jsonfor prior full-audit priorities.seo-cache/pages/{url-slug}/page-analysis.jsonfor 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
| 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. 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
| 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:
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
| 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_keywords for domain
- Fetch Google Shopping presence via Merchant API:
merchant_google_products_search for 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) |
| 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 |
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`
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.
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