Most SEO agencies can't spell technical SEO.
The ones who can charge more: for good reason.

Google publishes thresholds at the 75th percentile of real-user data: LCP under 2.5 seconds, INP under 200 milliseconds, and CLS under 0.1. We benchmark with CrUX field data and use lab tools for diagnosis. The audit identifies the actual LCP element, interaction bottlenecks, and layout shifts by route template before recommending changes. Passing a threshold can improve the user experience, but it does not guarantee a ranking outcome.

Flat schema describes one entity in isolation. An @graph implementation can connect Organization, WebSite, WebPage, Person, Article, Product, Service, and BreadcrumbList entities through stable identifiers. We inventory the visible page facts, choose only the supported types and properties, and validate that the structured data matches the page. Correct schema can support machine understanding and rich-result eligibility, but it does not guarantee a rich result, ranking, or AI citation.

The decision rests on three axes: how often content changes, how big the URL space is, and how SEO-critical each route is. SSG (static generation at build time) is the gold standard for pages that change infrequently: marketing pages, blog posts, documentation. Fastest possible SEO performance, but rebuilds get expensive past ~10K pages. ISR (incremental static regeneration in Next.js) handles large catalogs that update periodically: ecommerce product pages, programmatic SEO templates, large content libraries: by regenerating pages on demand or on a schedule. SSR (server-side rendering on every request) is the right call for pages that need fresh data on every load: search results, personalized content, real-time dashboards. CSR (pure client-side rendering) is the trap most JS-heavy sites fall into. Googlebot can render JS but does it on a delayed second-pass crawl, indexation gets unreliable past a few thousand URLs, and Bing/Yandex/AI engines render JS far less reliably than Google. We audit the route map, classify each route, and migrate routes off CSR onto the right rendering mode for their SEO profile.

Crawl budget management at scale is mostly about preventing waste. The main levers are parameter handling, sitemap segmentation, internal linking, canonical rules, robots directives, and log-file analysis. We use server and Search Console evidence to see which URLs are being crawled, which priority pages are being missed, and where duplicate surfaces are consuming attention. The recommendation follows the site data; we do not assume a fixed amount of waste or promise a specific indexation lift.

Migration SEO reduces avoidable search risk during a re-platform, domain change, consolidation, or rebuild. The work normally includes a pre-migration crawl, URL inventory and mapping, redirect decisions, schema and metadata parity, staging verification, launch monitoring, and post-launch reconciliation. The exact checkpoints and monitoring window depend on the site's size and release plan. No agency can guarantee ranking preservation, but disciplined mapping and validation make failures easier to prevent and diagnose.

The deliverable is a working technical record sized to the agreed scope. It can include URL and architecture findings, indexation classes, schema validation, Core Web Vitals field data, rendering comparisons, crawl and log analysis where access permits, internal-link findings, and a prioritised remediation roadmap with implementation detail. We agree the included templates, data sources, and handoff format before the audit starts rather than promising a fixed page count.

An in-house technical SEO is usually the better fit when SEO review is needed across continuous releases and there is enough recurring work to support a dedicated role. An agency can fit a defined audit, migration, schema, rendering, or Core Web Vitals project, or support an internal team that needs senior direction for a specific period. The decision depends on release velocity, implementation ownership, and the shape of the backlog rather than company revenue alone.

The kit, by category. Crawl analysis: Screaming Frog (default), Sitebulb (relationship visualisation), our own custom Node.js crawler for client-specific edge cases. Log file analysis: Splunk for enterprise, Cloudflare Logs / Logflare for mid-market, custom parsers for self-hosted server logs. Indexation: Google Search Console URL Inspection API at scale (we automate batch inspection for 10K+ URL audits), Bing Webmaster Tools, IndexNow API submission. Schema validation: Google's Rich Results Test, Schema.org validator, our own internal validator that checks @graph relationship integrity. Core Web Vitals: PageSpeed Insights for spot-checks, CrUX BigQuery dataset for historical field data, Vercel Analytics / Cloudflare Web Analytics for real-user telemetry. JS rendering: Mobile-Friendly Test (deprecated but still useful for render comparison), Puppeteer / Playwright scripts for custom render diffing. Migration: WayBack Machine + custom diff scripts for legacy-site reconstruction, Screaming Frog redirect-chain analysis. Plus the GSC and Google Analytics MCPs we use across every engagement for data ingestion. Tooling matters less than the operator using it, but the kit above is the kit.