Çelebi | Webtures References

Çelebi Aviation worked with Webtures on a programme that treated organic search and generative AI visibility as one problem. In aviation ground handling, buyers do not purchase from a search result. They run tenders. The starting point was therefore verification, not traffic: the checking done before a shortlist had to rest on the company's own sources.

Why Çelebi needed SEO and GEO support

Five structural challenges specific to ground handling shaped the brief.

Search plays a different role here. An airline or cargo operator does not transact through a search engine. Search functions as verification: which countries are covered, which licence categories are held, which service lines are operated. If that cannot be done from the company's own pages, third parties answer instead.
Employment intent dominates brand queries. A large share of brand-name searches comes from job seekers. Unless the content architecture separates the two audiences, generative systems learn the brand as an employer rather than a provider.
Difficult entity resolution. Çelebi is a common Turkish surname, so the holding, the ground handling company and unrelated businesses can collapse into one query space. The holding owns 89.91 per cent, and that relationship needed to be legible to a machine.
A language and audience mismatch. The corporate site is English only, while the company runs 32 stations in Türkiye, where partners, customers and candidates search in Turkish. Investor content on a separate domain splits authority further.
Regulatory questions with real depth. Ground handling operates under the Turkish civil aviation authority within the SHY-22 regulation and the SHT-YHT directive. What the A, B and C category licences cover is a recurring question for buyers and candidates alike.

Goals set for the Çelebi project

The programme aimed to bring the company's own sources forward on verification queries, serve commercial and career intent on separate surfaces, make the holding and operating company relationship machine-readable, and strengthen presence in AI-assisted search. Every goal was framed in the language of aviation regulation, so statements about licences and scope stayed faithful to it.

How Webtures approached SEO and GEO for Çelebi

Webtures combined technical SEO, content architecture and generative visibility. The premise is straightforward: there is no separate mechanism for appearing in generative answers. Google states that AI Overviews and AI Mode need no special markup; the precondition is being indexable and snippet-eligible.

Technical SEO and AI accessibility

Crawlability and parsability for AI systems were reviewed; the decisive item here is language and domain architecture. The gap between an English-only site and an audience searching in Turkish required the hreflang structure to be reconsidered, while corporate and investor content on separate domains made entity relationships something to state explicitly through structured data.

Content and semantic authority

Content was developed around the questions people put to search engines and AI assistants, which here come from three audiences. Newcomers ask what ground handling is and what the SHY-22 licence categories cover. The commercial side researches cargo and bonded warehouse services, general aviation and the Platinum premium line. Passengers ask about CIP and lounge access. In all three the rule was the same: the first sentence answers the question. Career intent was not suppressed but served on its own surface.

GEO and AI visibility

Work targeted presence across ChatGPT, Gemini, Perplexity and Google AI Overviews. The question set followed pre-tender verification logic: which countries and airports are served, which business lines operated, how the corporate structure is arranged. Verifiable facts anchored it: the 1958 founding as Türkiye's first private ground handling company, the 1996 listing, and a Turkish operation serving 250-plus customers with roughly 9,000 employees. Uncited questions were treated as content gaps. Measurement relied on Search Console's Generative AI performance report; third-party tools claiming access to Google's internal metrics were not accepted as evidence.

Experience and conversion

Conversion here is not a basket but the opening of a corporate conversation. Making station and service coverage visible and keeping job applications clear of the commercial journey were the priorities.

What was carried out in the Çelebi project

Main workstreams across technical SEO, content, structured data and GEO:

Crawl and indexation audit
Language version and hreflang review
Structured data linking corporate and investor domains
Content architecture separating commercial from career intent
Context-independent answer passages on regulation and licensing
Consistent description of station and service coverage
Question-set monitoring across generative surfaces
Page experience and Core Web Vitals improvements

What the SEO and GEO work delivered

The programme was tracked across three layers: organic performance on verification queries, the split between commercial and career intent on brand queries, and citation in generative answers.

Organic traffic and search visibility

Coverage widened across service, scope and regulatory queries. Search visibility was reported by query intent rather than volume, with the commercial share of brand queries tracked separately.

Visibility across AI platforms

Generative answers to the ground handling question set were monitored, tracking separately where the brand was cited and where it was absent. Whether those answers attached the brand to the correct legal entity was its own check, because in this category an entity error becomes a scope error.

The outcome of the Çelebi and Webtures partnership

In a category where the decision is made at a tender table, search does not close the sale. It makes sure the right information is already in place before anyone sits down. That is held by a content discipline keeping scope current and a measurement loop.