Pınar | Webtures References

Pınar Su ve İçecek worked with Webtures on a programme covering organic search and generative AI visibility together. Three separate publicly listed companies operate under the same umbrella brand, which makes this one of the entity clusters generative engines most often confuse. The programme therefore started where the risk starts: with whether machines recognise the company correctly at all.

Why Pınar Su needed SEO and GEO support

Four structural challenges specific to the bottled water category shaped the brief.

Entity confusion. Pınar Su ve İçecek (BIST: PINSU), Pınar Süt (PNSUT) and Pınar Et (PETUN) are three distinct listed companies sharing one umbrella brand. Add product brands such as Pınar Madran, Pınar Denge and Pınar Yaşam Pınarım, plus Yaşar Holding as majority shareholder with 64.51 per cent, and the result is a cluster AI assistants routinely merge. The answer to "which company is Pınar Su" needed to be learnable from the brand's own content.
Corporate data locked inside PDFs. The company's most distinctive facts, such as producing Türkiye's first bottled water in 1984 or accounting for 16.11 per cent of the country's total water exports in 2025, sit inside annual report PDFs with no HTML equivalent. Generative engines hit the same wall, which makes this a visibility gap the brand can close on its own site.
Ordering is local and dealer-dependent. Demand for 19-litre carboys forms at district level and is fulfilled through a dealer network of more than a thousand partners. Dealers using the brand name on their own sites create cannibalisation in local results, and the consistency of business data directly determines local visibility.
Two separate regulatory regimes. Spring and drinking waters fall under Turkish regulation on water intended for human consumption, while natural mineral waters sit outside it under a separate regime. Every statement about water quality or mineral content has to respect that division.

Goals set for the Pınar Su project

The programme aimed to define Pınar Su ve İçecek correctly as its own legal entity together with its product brands, to lift corporate data out of PDFs into citable HTML passages, to serve local carboy ordering intent without competing against the dealer network, and to strengthen presence in AI-assisted search. Each goal was defined with its regulatory boundary in place: statements about water quality and mineral values were written within the limits the relevant water regulations and the nutrition and health claims regulation allow.

How Webtures approached SEO and GEO for Pınar Su

Webtures applied a strategy combining technical SEO, content architecture and generative visibility. The premise is simple: there is no separate mechanism for appearing in generative answers. Being indexable and snippet-eligible is the precondition for being cited at all.

Technical SEO and AI accessibility

Crawlability was reviewed so search engines and AI systems could parse the content reliably. The decisive finding concerned format rather than access: every piece of verifiable corporate data lived inside a PDF. Even an indexable PDF is far less suited to passage-level citation than HTML, so company history, export figures and shareholding structure needed HTML counterparts. The division of roles between the corporate site, the ordering site and the umbrella brand site was clarified in the same pass.

Content and semantic authority

Content was developed around the questions people actually ask, which in this category fall into two groups. The first is informational: the difference between mineral water and soda, what the values in a water analysis report mean, which regulation governs spring water. The second is transactional: carboy pricing, subscriptions, the nearest dealer. The same layer established the entity distinction explicitly, describing the company's own product line, shareholding and history separately from the dairy and meat businesses that share the umbrella name but not the legal entity.

GEO and AI visibility

Work was carried out to strengthen presence across ChatGPT, Gemini, Perplexity and Google AI Overviews. A category-specific question set was defined and generative answers were monitored regularly. Part of that set was built deliberately to test entity resolution: whether an assistant conflates Pınar Su with Pınar Süt, whether it reports the shareholding structure correctly, whether it attributes product brands to the right company. Measurement relied on the Generative AI performance report in Search Console; third-party tools claiming access to Google's internal metrics were not accepted as evidence.

Experience and conversion

Page structures and journeys were arranged so visitors could reach both information and ordering without friction. Carboy ordering intent usually completes in an app or over the phone rather than on the page, so the page's job is to shorten the handoff. The dealer-finding journey was treated as a direct extension of local visibility, since inconsistent business data damages not only the user's experience but also the model search engines hold of the brand.

What was carried out in the Pınar Su project

Webtures delivered work across technical SEO, content architecture, site structure, structured data and GEO. The main workstreams:

Crawl, indexation and page experience audit
Migration of PDF-locked corporate data into citable HTML passages
Company and product brand relationships clarified through structured data
Role separation between the corporate, ordering and umbrella brand sites
Question-led content architecture with context-independent answer passages
Content review against both applicable water regulation regimes
Consistent business data and local intent work across the dealer network

What the SEO and GEO work delivered

The programme was tracked across three reinforcing layers rather than a single number: organic search performance, local and dealer-led visibility, and citation in generative answers. The measurement frame combined Search Console, analytics and regular review of the defined question set.

Organic traffic and search visibility

Search visibility was reported by query intent rather than by volume alone. Informational and ordering intent were tracked separately, with corporate queries treated as a third group, because the competition there is not a rival brand but third-party sources relaying the company's own data at second hand. On the local side, the measure was how much district-level demand was matched by consistent business data.

Visibility across AI platforms

Generative answers to the defined question set were monitored, tracking separately where the brand was cited and where it was absent. A second layer sat on top of that: being mentioned is not sufficient if the mention attaches to the wrong company. Answers that confused the entities were logged as content gaps in their own right.

The outcome of the Pınar Su and Webtures partnership

The strategy addressed organic search performance and AI-assisted visibility together. In a multi-brand structure, visibility is not measured by being mentioned but by being mentioned correctly, and that requires corporate data to sit in machine-readable form on the brand's own source rather than in a document nobody can quote from.