Marko Cvijić / Enterprise SEO
Enterprise SEO. Technical first.
Most enterprise engagements open with a content plan. I open with the crawl. If a search engine cannot access, render and index your pages correctly, every euro spent on content is subsidising a ceiling you cannot see.
The problem
Enterprise sites accumulate technical debt silently.
Crawl budget burned on faceted navigation. Canonicalization errors splitting link equity between four near-identical URLs. JavaScript rendering that hides the body copy from a crawler while showing it perfectly to you. Hreflang implementations that contradict themselves across markets, so the wrong country page ranks in the wrong language.
None of this appears in a rankings dashboard. It appears as a ceiling: organic performance that plateaus no matter how much content gets published, and a slow drift where each quarter's fix is undone by the next quarter's release. By the time it is visible in revenue, it has usually been compounding for two years.
Which is why I audit before I build. Every time, no exceptions - and I would rather lose the engagement than skip it.
What the work covers
Three layers, in this order.
01 · Technical foundation
Nothing else starts until this is verified
Crawl budget waste, orphaned pages, misconfigured robots directives, noindex leaks, redirect chains and canonicalization errors - found and prioritised before a single piece of content is briefed.
URL structure, faceted navigation, pagination, silo logic and internal link equity distribution. Architecture decisions that compound instead of ones you have to unwind in eighteen months.
LCP, CLS and INP diagnosed at infrastructure level, not plugin level: JavaScript rendering, server response times, resource loading order - whatever is standing between a crawler and your content.
Entity-level implementation - Organization, Product, Article, FAQ, BreadcrumbList, HowTo - built to feed both classical search and the answer engines that read structured data first.
Server logs to establish what a crawler actually requests, versus what you assume it requests, cross-referenced against Search Console coverage to surface the indexation gaps nobody reports on.
Hreflang, x-default logic, language-specific canonical architecture and crawl budget management across multi-country, multi-language deployments - the failure mode I have seen most often at enterprise scale.
02 · AI answer engines
A growing share of queries never reaches a SERP
Structured data and entity disambiguation so AI systems identify your brand, products and expertise correctly - instead of confidently describing a competitor when asked about you.
Content formatted for extraction: clear definitions, concise summaries, FAQ schema, factual claims structured for citation. Information architecture, not keyword density.
Editorial placements, co-citations and brand mentions in the sources that retrieval systems treat as authoritative. Being in the answer requires being in the places the answer is assembled from.
I test how your brand, products and category terms actually appear in generated responses across the major LLM platforms, then document the gap between that and where you should be.
03 · Content architecture
Built on a verified foundation, never before it
Hub-and-spoke clusters built around the pages that carry commercial intent, structured so the funnel is legible to a search engine and to a buyer at the same time.
Every page with one intent, one role in the funnel and one call to action. Written to rank and to move a buyer, not to hit a word count agreed in a retainer.
Briefs, review gates and publishing standards that hold when the volume goes up and the original team has moved on. Governance is what stops the architecture eroding.
Replatforms and redesigns are where hard-won organic revenue quietly disappears. Redirect mapping, parity checks and staged verification, run before the switch rather than diagnosed after it.
How an engagement runs
Audit, verify, then build.
01
Audit
Crawl, index coverage, rendering, architecture, structured data and the tracking underneath it. One to two days. I document what exists before proposing a single change.
02
Verify the data
Which numbers can be trusted and which cannot. Analytics that disagrees with the crawl gets reconciled first - there is no point prioritising work against a report that is wrong.
03
Sequence by return
Technical debt paid down in the order that returns money soonest, not the order it was discovered. Each item with an owner, a rationale and an expected outcome written down.
04
Build and ship
Fixes implemented with your engineering team or with mine. We own the build too, so the plan and the thing that runs it are not separated by a handoff nobody is accountable for.
05
Govern it
A monthly diagnostic loop: new crawl issues, coverage drift, schema breakage, rendering regressions from releases. The system stays honest as the site keeps changing.
06
Report on revenue
Organic reported as contribution to revenue by category and page type, connected to analytics and reconciled against actual business outcomes - not a rankings screenshot.
Operating rules
Not aspirations. Rules.
01
No content work commissioned before crawl and index status is verified.
02
Every technical recommendation carries a rationale and an expected outcome, in writing.
03
Architecture changes are modelled against crawl impact before they ship, never after.
04
Migrations get a redirect map and a parity check ahead of launch. No exceptions, regardless of the deadline.
05
Coverage and log data reviewed monthly. Indexation drift is treated as an incident, not a trend line.
06
One definition per metric, agreed once, used by everyone - including the paid team.
Track record
Where this has run.
Ran analytics and SEO for the World Economic Forum in Davos - an environment where the reporting has to be correct before it is fast, and where a wrong number travels further than a missing one.
Strategic SEO and analytics for the UAE Government (AML/ADQ) and Emirates Global Aluminium. Multi-stakeholder governance, strict review paths, and technical constraints that do not move for marketing convenience.
Search and measurement infrastructure for Advisera in the USA, Mirus in Australia and Eone Solutions in the USA - built to survive replatforms, market expansion and changes of team.
High-traffic marketplaces including KupujemProdajem, where crawl efficiency, faceted navigation and template-level decisions are the difference between growth and a plateau.
Enterprise search systems run across 10+ markets in Europe, the Middle East, North America and Australia, in several languages, under a single measurement definition.
Fit
Who this is for.
A large site and a real ceiling
Thousands to millions of URLs. Organic matters to the P&L and someone senior has noticed it stopped moving. There is an engineering team, or budget to build. And there is appetite for an audit that may say the last two years of content spend was structurally wasted.
Rankings as the deliverable
If the brief is a fixed number of articles per month, a keyword position report, or a retainer that cannot pause for a foundation fix, another provider will make you happier. I am not the cheapest option and I do not compete on volume of output.