FİXA

About the Client and the Project

FİXA is a construction chemicals brand with a wide range of products and solutions for different building applications. This means users can reach the brand through a very broad set of queries: not only by brand or product name, but by application, technical problem, material need or the solution they are looking for.

As AI-powered search and answer systems spread, the way users look for answers to technical questions like these is changing. Instead of searching for a single keyword, users can now describe their problem, application or need in natural language and ask directly for a solution.

That is why our GEO work for FİXA focused on presenting the product, application and technical information behind the brand's expertise with clearer relationships, and on adapting the existing content to these new search behaviors.

Goals and Key Challenges

Project Goals

The main goals we set for FİXA were to:

• Give the brand a clearer information structure in AI-assisted research.
• Make the relationships between products, applications, technical needs and industry expertise clearer.
• Build the questions users ask before buying or choosing a solution into the content.
• Turn technical information into clear, direct and reusable blocks of information.
• Help AI-powered search and answer systems, as well as classic search engines, make sense of the content more easily.
• Track website traffic from AI platforms as a measurable performance indicator.

Key Challenges from a GEO Perspective

In GEO, the core task is not simply to produce more content. You have to show clearly which user questions a brand's existing expertise, products and solutions relate to.

• Technical and product information was spread across different pages.
• Users could describe their technical needs in questions that differ from the product names.
• The links between brand, products, applications and solutions needed to be clearer.
• Technical information had to be clear enough for both experts and people researching the topic.
• Traffic from AI platforms needed to be assessed separately from classic organic search traffic.

So we did not treat the project as a classic SEO effort aimed only at ranking for certain keywords. We focused on building a GEO structure that connects FİXA's expertise more clearly with user questions and solution needs.

Our Strategy and Solution

Strengthening the Links Between Products and Solutions

We reviewed FİXA's existing digital content from the point of view of the needs users might have when looking for a product or solution. We worked to make sure product information was not limited to technical specifications but could be understood together with its uses, application needs and the problem it solves.

By making the relationships between the brand, its products and their applications clearer, we aimed to build a stronger link between the needs users describe in natural language and the existing content.

Building User Questions into the Content

We made the questions users might ask before a purchase or technical decision part of the content plan. We gave more visibility to questions such as where a product can be used, which problem it addresses, under which conditions it is the right choice and how it relates to similar needs.

This approach aimed to take the content beyond a keyword-only structure, so it can match the longer, context-rich questions users put to AI platforms.

Making Technical Information Clearer and Easier to Use

Having the technical information on the site is not enough. It has to be presented clearly, with its context defined and its relationship to the relevant product or application easy to understand.

So we focused on making the connections between products, applications and technical needs more visible in the existing information structure. Our aim was both to help users reach the answer they need faster and to give AI-powered systems a foundation on which they can interpret the information more easily.

Strengthening Trust and Expertise Signals

With technical products, it matters not only that an answer exists, but that it is clear which brand, product and area of expertise the answer belongs to. So we focused on presenting the relationships between FİXA's industry knowledge, its products and their applications more consistently.

This structure aimed to connect FİXA more clearly not only with specific product names but also with the technical needs and applications it provides solutions for.

Measuring Traffic from AI Platforms

We did not judge the GEO work by classic organic search metrics alone. We also tracked sessions from AI platforms to the FİXA website as a separate traffic source.

The metric used here is not the brand's total visibility on AI platforms or how many answers it was recommended in. The performance result shared in this success story is based on measurable website sessions that actually reached the FİXA website from AI platforms.

Results

In the first three-month observation period of our GEO work for FİXA, website traffic from AI platforms developed as follows:

• A new traffic source: AI platform traffic, which was not measurable at the start, became a measurable source of website traffic in the following period.
• July–August growth: Sessions from AI platforms rose about 56%.
• Month-on-month growth: Each month of the three-month observation period recorded more AI-referred sessions than the month before.
• Peak level: The highest level of AI platform traffic in the period came in August.
• Measurable acquisition: Visits from AI platforms started to become a new website acquisition source that FİXA can track separately.

These results showed that traffic from AI platforms grew steadily over the three-month observation period, rather than jumping once in a single month. Still, three months is too early to draw firm conclusions about how sustainable this channel will be in the long term.

Why This Success Mattered

The first thing that makes the FİXA case important is that the performance of the GEO work could be tracked through real sessions reaching the website, not only through the abstract idea of "AI visibility." AI platform traffic went from not measurable at the start to being recorded steadily in the following months, showing that new search behavior is also becoming visible in web analytics.

Second, the case shows that for technical and B2B brands, GEO should not be limited to whether the brand name appears in AI answers. Layers of information such as which need a product meets, where it is used and which areas of expertise the brand is associated with are becoming more and more important in the new search experience.

Third, the roughly 56% increase in sessions from AI platforms between July and August is a concrete early signal that this traffic source keeps growing in a measurable way.

GEO Becoming a Measurable Traffic Channel

Our work for FİXA is an example of an approach in which we did not treat GEO only as a way to appear more often on AI platforms. While connecting the brand's product, application and expertise information more clearly with user questions, we also tracked separately whether these new search environments actually send traffic to the website.

By the end of the three months, AI platform sessions had risen every month and grown about 56% from July to August, showing that a new and measurable acquisition channel was starting to form for FİXA.

Our goal for the next phase is to track this early growth over a longer period, to see whether AI platform traffic spreads to more products and applications, and to measure how these sessions contribute to quote requests, leads and other business conversions.

If you want to measure how your brand is understood in ChatGPT and other AI-powered research environments, which topics it is associated with and whether these new channels send traffic to your website, see our AI Visibility Analysis and GEO Services, or contact Magna Dijital.

The roughly 56% increase in this success story is based on a comparison of measurable sessions from AI platforms to the FİXA website in July and August 2026. This metric should not be read as total AI visibility, a citation count or the total volume of brand mentions on AI platforms.