How do you build a technical SEO strategy for large websites?

Long Answer

Large-scale SEO is less about one-off tweaks and more about systems that enforce best practices across millions of pages. The aim: ensure Googlebot can efficiently crawl, parse, and index critical content, while structured data enhances visibility and a sound architecture keeps the site performant.

1) Crawl budget management

Search engines allocate crawl resources based on authority, demand, and site health. With millions of pages, prioritize key URLs:

• Maintain XML sitemaps segmented by type (products, categories, blog) and under 50k URLs each.
  
• Enforce canonical tags on duplicate or parameterized URLs.
  
• Block low-value pages (filters, infinite combinations) in robots.txt.
  
• Implement log file analysis: track crawl frequency, identify orphaned or wasted URLs, and adjust linking accordingly.
  

2) Site architecture and hierarchy

Structure is the backbone:

• Use a clear, hierarchical URL system (domain/category/product).
  
• Limit depth to ≤4 clicks from homepage.
  
• Flatten redundant categories; use breadcrumb markup for clarity.
  
• Ensure faceted navigation has controlled parameters (no infinite crawl traps).
  
• Distribute link equity intentionally: hub pages receive internal links from high-authority nodes.
  

3) Structured data at scale

Schema.org markup is vital for enhanced SERP features:

• Build JSON-LD templates tied to CMS fields (e.g., Product schema with price, availability, reviews).
  
• Validate in CI/CD pipelines before deployment.
  
• Use organization-wide schema (Organization, Website, BreadcrumbList) plus content-type schemas.
  
• Monitor rich result reports in Search Console to detect drops.
  

4) Performance and Core Web Vitals

Crawlability is worthless if pages fail performance metrics:

• Deploy CDN edge caching and lazy-load non-critical assets.
  
• Use responsive images with WebP/AVIF and dimension attributes.
  
• Preload above-the-fold resources; defer heavy scripts.
  
• Track CLS, LCP, and INP across templates and block releases that regress.
  

5) Duplication, canonicals, and hreflang

At scale, duplication is inevitable:

• Use canonical tags for similar pages (sort orders, tracking parameters).
  
• Consolidate content clusters with 301 redirects where possible.
  
• Implement hreflang for multilingual sites, referencing consistent self-URLs and alternates.
  

6) Monitoring and automation

SEO at this level is ongoing:

• Automate audits (Screaming Frog API, custom scripts).
  
• Monitor server logs, crawl stats, and indexation daily.
  
• Use alerts for sudden changes in crawl rate, sitemap errors, or structured data failures.
  
• Build dashboards for impressions, CTR, indexation ratio, and CWV performance.
  

7) Governance and scalability

Policies must scale with teams:

• Provide SEO linting in CI/CD pipelines (broken canonicals, missing meta).
  
• Create reusable schema templates and internal linking modules.
  
• Train developers to consider SEO in deployments; no siloed last-minute fixes.
  

By combining structured crawl management, a resilient site architecture, and schema automation, a technical SEO strategy ensures large websites remain crawlable, indexable, and competitive in search.

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Table

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Common Mistakes

• Letting parameterized faceted URLs explode crawl budget.
  
• Overlooking log analysis, assuming sitemaps alone solve crawl efficiency.
  
• Embedding structured data inconsistently, leading to rich snippet loss.
  
• Ignoring performance at scale—shipping large JS bundles that degrade Core Web Vitals.
  
• Duplicating content without canonical enforcement, splitting link equity.
  
• Misconfigured hreflang (self-referencing errors, missing return links).
  
• Relying solely on Search Console without independent log-based crawl insights.
  
• Manual schema markup instead of automated templates.
  
• No CI/CD checks for SEO regressions.
  
• Treating SEO as post-launch QA rather than baked into the architecture.
  
  

Sample Answers

Junior:
“I would use sitemaps and robots.txt to guide crawling, ensure clean URLs, and add schema markup for products. I would also monitor performance with Lighthouse and make sure pages are mobile-friendly.”

Mid:
“I’d segment XML sitemaps by content type, enforce canonical tags, and analyze server logs to ensure crawl efficiency. Structured data would be templated and validated in CI/CD. I’d manage Core Web Vitals with CDN, lazy-load, and optimized images.”

Senior:
“A large-scale strategy begins with crawl budget audits using log analysis, automated sitemap generation, and canonical governance. Structured data pipelines must be automated via JSON-LD templates tied to CMS fields, validated pre-deploy. Site architecture prioritizes ≤4 click depth, faceted nav control, and hreflang governance. Performance budgets, CWV gating, and monitoring dashboards close the loop.”

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Evaluation Criteria

Interviewers expect systemic thinking. Strong answers should mention:

• Crawl budget controls (sitemaps, robots.txt, log analysis).
  
• Site architecture discipline (hierarchical URLs, shallow depth, hub linking).
  
• Automated structured data deployment and validation.
  
• Performance optimization tied to Core Web Vitals.
  
• Duplication management with canonicals, redirects, and hreflang.
  
• Monitoring with log analysis and CI/CD SEO linting.
  
  

Red flags: vague “optimize content” without crawl/indexation context, reliance only on Search Console, or ignoring automation. Senior candidates should cite tooling, automation in pipelines, and measurable SEO KPIs (crawl/index ratio, CWV scores).

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Preparation Tips

Practice with a demo:

• Spin up a sample site with thousands of synthetic URLs.
  
• Generate segmented sitemaps and configure robots.txt to block noise.
  
• Apply schema templates (Product, Article) tied to CMS fields.
  
• Run log analysis to detect crawl waste.
  
• Implement Core Web Vitals improvements (image optimization, CDN).
  
• Test canonical and hreflang strategies on duplicates/multilingual pages.
  
• Set up automated audits in CI/CD that fail builds if canonicals, schema, or sitemaps break
  
• Build dashboards in Looker Studio combining GSC, GA4, and server logs.
  
  

This will train you to think in systems, not pages, which is crucial for SEO at scale.

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Real-world Context

An e-commerce retailer with 10M SKUs cut crawl waste by 40% by pruning faceted URLs and analyzing logs; organic impressions rose as bots focused on core products. A media site automated Article schema templates, leading to a 25% increase in Top Stories visibility. A marketplace implemented canonical governance across duplicate category URLs, consolidating link equity and raising rankings. A travel site deployed hreflang governance at scale, resolving thousands of errors; international traffic rose by double digits. Another SaaS platform gated deployments with SEO lint checks (canonical, schema, sitemap) in CI/CD; regressions dropped to near-zero. Across industries, automation plus governance turned fragile SEO setups into scalable, resilient systems.

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Key Takeaways

• Control crawl budget with sitemaps, robots.txt, and log analysis.
  
• Design shallow, hierarchical site structures.
  
• Automate schema markup via templates and CI/CD.
  
• Optimize Core Web Vitals at scale.
  
• Govern canonicals and hreflang systematically.
  
• Bake monitoring and automation into SEO workflows.
  
  

Practice Exercise

Scenario:
You are tasked with designing a technical SEO strategy for a global marketplace with 5M+ product pages, faceted navigation, and multilingual domains.

Tasks:

1. Audit crawl waste with server log analysis; identify high-frequency but low-value URLs.
   
2. Segment sitemaps by language and content type; automate regeneration.
   
3. Configure robots.txt to disallow crawl traps; enforce canonical tags on duplicates.
   
4. Implement hreflang across languages with consistent self-referencing URLs.
   
5. Apply Product schema via JSON-LD templates tied to CMS; validate in CI/CD.
   
6. Optimize Core Web Vitals with CDN edge caching, responsive images, and lazy loading.
   
7. Create dashboards showing crawl/index ratio, CWV scores, and structured data coverage.
   
8. Build CI/CD linting rules to block deploys on SEO regressions.
   
9. Define KPIs: % of priority pages indexed, average crawl depth, Core Web Vitals compliance.
   
   

Deliverable:
An SEO playbook with sitemap architecture, crawl budget analysis, schema templates, hreflang plan, performance budgets, and dashboards for monitoring and reporting.