What It Is
Cost of Retrieval is a concept from Koray Tugberk Gubur's methodology that measures how much effort a search engine must expend to crawl, parse, understand, and index your content. The lower the cost, the more efficiently Google can process your pages — and efficiency translates to better crawl allocation, faster indexing, and ultimately higher rankings.
Why It Matters for Your SEO
Google has a finite crawl budget for every site. Pages that are slow to load, poorly structured, missing schema markup, or buried behind complex navigation cost Google more resources to process. When the cost is too high, Google may deprioritise crawling — meaning your new content takes longer to appear in search results, and your updated content takes longer to be re-evaluated.
How Korvex Measures It
Cost of Retrieval is evaluated through several technical signals:
| Signal | What It Measures | Impact |
|---|---|---|
| Page Speed | Time to load and render | Slow pages = higher retrieval cost |
| Schema Markup | Structured data completeness | Schema reduces parsing ambiguity |
| HTML Structure | Clean heading hierarchy, semantic HTML | Well-structured pages are cheaper to parse |
| Crawl Efficiency | Sitemap coverage, internal link depth | Pages found via sitemap = lower discovery cost |
| Indexing Status | GSC coverage and exclusions | Already-indexed pages have zero discovery cost |
Business-Type Adjustments
Local Services receive enhanced Cost of Retrieval scoring:
- Formula:
original_score × 0.60 + local_weight × 0.40 - Local weight components: NAP consistency (25%), local schema (25%), maps embed (20%), service area schema (15%), review schema (15%)
- Local schema breakdown: LocalBusiness type (40 pts), complete address (25 pts), telephone (15 pts), geo coordinates (10 pts), opening hours (10 pts)
Ecommerce receives product-specific scoring:
- Formula:
original_score × 0.60 + ecommerce_weight × 0.40 - Ecommerce weight: product schema completeness (25%), rich snippet readiness (25%), collection structure (20%), product description quality (15%), trust signals (15%)
How to Improve Your Score
- Submit a comprehensive XML sitemap — every indexable page should be in your sitemap
- Add structured data — at minimum, Organization, BreadcrumbList, and page-type-specific schema
- Fix heading hierarchy — ensure every page has exactly one H1, with logical H2→H3 nesting
- Improve page speed — target Largest Contentful Paint under 2.5 seconds
- Reduce crawl depth — no important page should be more than 3 clicks from the homepage
Local Schema Scoring (0-100)
| Element | Points |
|---|---|
| LocalBusiness type present | 40 |
| Complete address (street, locality, region, postcode) | 25 |
| Telephone number | 15 |
| Geo coordinates (lat/lng) | 10 |
| Opening hours (bonus) | 10 |
Ecommerce Scoring Components
- Rich Snippet Readiness:
price_score × 0.60 + review_score × 0.40 - Product Description Quality: < 150 words = 25, 150-300 = 60, > 300 words = 100
- Collection Structure:
breadcrumb_coverage × 0.50 + word_count_score × 0.50 - Trust Signals: Review/AggregateRating (+50), aggregateRating nested data (+25), Offer schema (+25)
Data Sources
- Crawl data: Phase 4 Sitebulb (09:00 UTC), Phase 1.75 GSC Crawl Health (02:15 UTC)
- Indexing data: Phase 1.6 GSC Sitemap Coverage (01:30 UTC)
- Schema data: Extracted during Phase 5 page scoring
- Page speed: Collected via CrUX API during Phase 2.5 Site Health Diagnostics
Related Concepts
- The Koray Score — Cost of Retrieval influences overall scoring
- Schema Intelligence — structured data coverage analysis
- The Five Fundamentals — technical health feeds multiple fundamentals