AI Visibility of E-Commerce and Retail Brands in Türkiye 2026

Türkiye's AI Shopping Map: Where Do the Models Agree, and Where Do They Diverge?

On October 22–26, 2026, we compared six AI platforms across 10 Turkish-language shopping queries. We analyzed 1,599 brand/service appearances as 319 unique identities, after merging obvious spelling variants. 74.9% of the identities appeared on only one platform and 87.5% in only one query. Average overlap between platforms rose to 52.9% in electronics but fell to 8.5% in premium fashion and 13.4% in quick grocery delivery.

Prepared by: Magna Dijital SEO & GEO Team · Editor: Mert Feke · Measured: October 22–26, 2026 · Published: October 26, 2026 · Last updated: November 3, 2026

Research Question: Does the Same Shopping Need Produce the Same AI Recommendations?

When a user who wants to shop in Türkiye brings the same need to ChatGPT, Gemini, Meta AI, Perplexity, Cerebras or Google AI Overview, do they see the same stores, brands and platforms?

In this research, we examined not only which brands appear, but how differently AI systems represent Türkiye's e-commerce and retail ecosystem by category, platform and time.

The core question was:

In which shopping categories do AI systems form a shared core of recommendations, and in which do they split into entirely different universes of brands and services?

In the second layer of the research, we looked at how far the same answers held over five days; in the third, at whether the visible brands were represented at a current and correct level.

Scope and Measurement Approach

The research is based on a five-day measurement set taken on October 22, 23, 24, 25 and 26, 2026.

How were names standardized?

The raw results can contain different spellings of the same brand because of capitalization, spacing, Turkish characters or punctuation. So name standardization (canonicalization) was applied to obvious spelling variants.

For example, obvious spelling differences such as ÇiçekSepeti / Çiçek Sepeti or Vatan Bilgisayar / vatanbilgisayar were merged into one.

Real service distinctions, however, were preserved. For example, Trendyol, Trendyol Yemek and Trendyol Hızlı Market or Migros, Migros Sanal Market and Migros Hemen were not forced under the same identity.

With this method, the 1,599 total appearances were analyzed as 319 unique brand/service identities.

How was overlap between platforms calculated?

For the similarity of the brand/service sets two platforms produced on the same day for the same shopping query, we used the Jaccard overlap rate (Jaccard similarity).

If two platforms produce exactly the same candidate set, the rate is 100%; if they produce no names in common, it is 0%.

Google AI Overview was included in this calculation only for cells with a comparable brand/service set. That is why the correct term used here is overlap between platforms.

How Fragmented Is Türkiye's AI Shopping Map?

239 of the 319 unique brand/service identities appeared on only one AI platform.

This means about 74.9% of the brands and services identified in the research stayed platform-specific.

Only 10 brand/service identities reached all six platforms in the combined five-day data set.

The fragmentation is seen not only between platforms but also between shopping needs.

279 of the 319 identities appeared in only one query. In other words, 87.5% of brand/service identities did not go beyond a single shopping need.

So a brand being visible in a single general query does not represent its overall AI shopping visibility in Türkiye.

The Category Changes How Much AI Agrees

The strongest result of the research emerged at the category level.

AI platforms produced relatively shared brand lists in more established shopping categories such as electronics and large marketplaces, while they formed very different recommendation sets in areas such as premium fashion and quick grocery delivery.

Categories Where AI Agrees

The highest overlap was seen in the electronics and large marketplace queries.

In electronics, Hepsiburada, MediaMarkt, Teknosa and Vatan Bilgisayar appeared at least once on all six platforms in the combined five-day set.

In the large marketplace query, Trendyol and Hepsiburada spread to all six platforms.

This table is not a ranking of quality or market leadership. It only shows to what extent different AI platforms agree on the same names.

Categories Where AI Diverges

Premium fashion was the most fragmented category in the research.

Taking the platform pairs of all five days together, average overlap was only 8.5%.

In this category, a very wide universe of names formed, including Beymen, Vakko, Gizia, NetWork, Zorlu Center, Brandy's, Harvey Nichols Istanbul, İstinyePark and various global luxury brands; but there was no single shared brand/service identity that spread to all six platforms.

The picture is similar for quick grocery delivery:

While different services such as Getir, Migros Sanal Market, Yemeksepeti Market, A101 Kapıda, Migros Hemen, CarrefourSA Online and Trendyol Hızlı Market appeared, average overlap was only 13.4%.

The point to note here is that low overlap does not on its own mean low quality.

What the data shows is more limited:

In these categories, AI systems answer the same user need with more varied sets of brands and services.

Do the Same Answers Hold Over Five Days?

Difference between platforms and variation over time are not the same metric.

So we also compared the brand/service sets the same platform produced for the same query on consecutive days.

Because of Google AI Overview's different data structure, only ChatGPT, Gemini, Meta AI, Perplexity and Cerebras were used in the analysis of consistency over time. For each category, 20 comparisons were made: five platforms × four consecutive day pairs.

Large marketplaces show both higher agreement between platforms and higher consistency over time.

Premium fashion and quick grocery delivery are more volatile on both counts: the lists the platforms produce differ more from each other, and the same platform's list can change more from day to day.

The Cross-Platform Visibility Core

Only 10 of the 319 unique brand/service identities appeared at least once on all six platforms in the combined five-day data set.

This list should not be read as "AI's best brands" or a "ranking of the most visible brands."

What it measures is only platform breadth: these names appeared at least once on all six different AI surfaces in the combined five-day data.

And not every brand has the same visibility profile.

For example, although MediaMarkt spread to six platforms, in the research it was concentrated mainly in the electronics query, while Trendyol spread across many more shopping needs. Yemeksepeti and Getir appear mainly in food and grocery needs.

So:

Platform coverage ≠ category coverage ≠ total number of appearances.

Visibility Does Not Mean Being Current: The GittiGidiyor Example

This finding adds a separate quality layer to measuring AI visibility.

A brand or platform:

• can appear in the answer,
• can appear in a high position,
• can recur on different days,
• can appear in more than one query,

and still not be a current option for the user.

That is why, in B2C AI visibility, being current also needs to be assessed separately, not just appearance and consistency.

Brand, Service or Sub-Brand?

The research's second important representation problem emerged in the split between brand and service level.

In the raw answers and in the automatic extraction layer, the same commercial ecosystem can be named at different levels.

That is why only spelling variants were merged in the research; real service names were kept separate as far as possible.

This distinction is not just a matter of data cleaning.

Whether an AI system, when answering a user's "groceries," "food," "general shopping" or "electronics" need, represents the parent brand, the right sub-service or both is a separate area of examination for B2C GEO.

What Do These Findings Mean for B2C GEO?

This research does not measure whether a specific GEO effort causes a specific AI visibility result.

So the data does not support a conclusion such as "if this optimization is done, the brand will definitely be recommended."

On the other hand, the research shows that explaining B2C AI visibility with a single "brand appeared / did not appear" metric can fall short.

We do not present these dimensions as a universal AI visibility score or a new commercial framework.

They are measurement dimensions that need to be kept separate to interpret the data in this research correctly.

The core distinction is:

Appearing in an AI answer ≠ appearing on different platforms ≠ appearing in the right category ≠ being represented with a current and correct service identity.

What This Research Shows

Türkiye's AI shopping map is fragmented across platforms

74.9% of the 319 unique brand/service identities appeared on only one platform.

Fragmentation varies sharply by category

Average overlap between platforms was 52.9% in electronics and 51.0% in large marketplaces, but 8.5% in premium fashion and 13.4% in quick grocery delivery.

The consistency of AI answers over time also depends on the category

Consistency was 88.8% for large marketplace recommendations but stayed at 32.9% in premium fashion.

Visibility does not mean being current

GittiGidiyor recurring over five days shows that the consistency metric needs to be assessed separately from being current.

Parent brand and service level create a separate representation problem

The different ways parent brands and sub-services are represented in ecosystems such as Trendyol, Migros, Yemeksepeti and Getir mean it has to be defined in advance whether measurement is done at brand level or service level.

What This Research Does Not Show

This study:

• does not rank Türkiye's "best" e-commerce or retail brands.
• does not measure brands' sales volume or market share.
• does not measure customer satisfaction or product quality.
• does not rank AI platforms by overall quality or accuracy.
• does not show that a brand appearing creates traffic, sales or conversions.
• does not treat visibility in a single query or on a single platform as overall AI visibility performance.
• does not prove that a specific GEO practice causes visibility.

The aim of the research is to examine comparatively which brands and services AI systems that produce shopping recommendations in Türkiye take into the candidate pool, how much these sets overlap by category and platform, how far they hold over time, and whether the representation is current and at the right level.

Limitations of the Research

The measurement window is five days. Longer-term measurements may show different consistency and brand coverage behavior.

The research is limited to Türkiye and Turkish-language queries. Recommendation sets may change in different language, country and user contexts.

Brand/company extraction was automated. Obvious spelling variants were therefore standardized; however, not all 319 identities were manually verified at company/service level.

Google AI Overview does not have the same data structure as the other five platforms. A successful AI Overview being generated and a concrete, comparable brand row being produced are different events. That is why only cells where a brand/service set formed were included in the platform overlap analysis.

Google AI Overview was not used in the consistency-over-time chart. This kept the number of observations equal for each category across the five direct-answer platforms.

A name appearing in an AI answer was not treated as real commercial fit or recommendation quality.

The 10 Queries Used

Q1 — Large marketplaces

Türkiye’de online alışveriş için hangi büyük pazar yerlerini önerirsin?
(Which large marketplaces would you recommend for online shopping in Türkiye?)

Q2 — Wide product range

Türkiye’de ürün çeşitliliği geniş e-ticaret platformları hangileri?
(Which e-commerce platforms in Türkiye have a wide product range?)

Q3 — Books, flowers and gifts

Türkiye’de kitap, çiçek ve hediye alışverişi için hangi online mağazalar değerlendirilebilir?
(Which online stores can be considered for buying books, flowers and gifts in Türkiye?)

Q4 — Food delivery

Türkiye’de online yemek siparişi için hangi platformları önerirsin?
(Which platforms would you recommend for ordering food online in Türkiye?)

Q5 — Groceries and quick delivery

Türkiye’de online market alışverişi ve hızlı teslimat için hangi hizmetler var?
(What services are there for online grocery shopping and quick delivery in Türkiye?)

Q6 — Second-hand and real estate

Türkiye’de ikinci el ürün ve emlak ilanlarına bakmak için hangi platformlar öne çıkıyor?
(Which platforms stand out for browsing second-hand product and real estate listings in Türkiye?)

Q7 — Everyday clothing

Türkiye’de günlük giyim alışverişi için hangi perakende markalarını önerirsin?
(Which retail brands would you recommend for everyday clothing shopping in Türkiye?)

Q8 — Premium fashion

Türkiye’de premium moda alışverişi için hangi mağazaları önerirsin?
(Which stores would you recommend for premium fashion shopping in Türkiye?)

Q9 — Electronics

Türkiye’de elektronik ürün satın almak için hangi perakendecileri karşılaştırmalıyım?
(Which retailers should I compare to buy electronics in Türkiye?)

Q10 — Cosmetics and personal care

Türkiye’de kozmetik ve kişisel bakım alışverişi için hangi mağazaları önerirsin?
(Which stores would you recommend for cosmetics and personal care shopping in Türkiye?)

Conclusion: There Is No Single Shared List on Türkiye's AI Shopping Map

The five-day data indicates that AI shopping recommendations in Türkiye do not work as a single shared brand ranking.

In electronics and large marketplaces, the platforms converge relatively strongly around a certain core of brands.

In categories such as premium fashion and quick grocery delivery, however, the same user need produces much more varied sets of brands and services.

What is more, the divergence appears not only between platforms but also over time.

Large marketplace recommendations stay quite stable over the five-day window, while premium fashion and quick grocery delivery are more volatile.

The GittiGidiyor example brings a third dimension into view:

A brand being recommended regularly does not mean the recommendation is current.

The brand–service examples also show that visibility needs to be measured at the right level. Trendyol and Trendyol Yemek, or Migros and Migros Sanal Market, may belong to the same commercial ecosystem, but they do not represent the same user need.

That is why, in B2C AI visibility, the meaningful question is not only:

"Does our brand appear in AI answers?"

The more meaningful question is:

"How widely, how consistently and how currently is our brand represented across different AI platforms, for the right shopping need and with the right service identity?"

About This Research

We prepared this research at Magna Dijital Pazarlama Ajansı, based on a comparative analysis of a five-day multi-platform AI visibility measurement we took on October 22–26, 2026 with Magna AI Analyzer, a tool we developed ourselves.

Magna Dijital is an integrated, data-driven digital marketing agency founded in 2014; our SEO & GEO team runs our GEO and AI visibility work.

Between October 22 and 26, 2026, 10 different shopping needs in Türkiye were examined on ChatGPT, Gemini, Meta AI, Perplexity, Cerebras and Google AI Overview.

The aim of the research is not to rank brands by commercial success, sales, quality or market share, but to examine comparatively how different AI systems represent Türkiye's e-commerce and retail ecosystem in terms of cross-platform overlap, category dependence, consistency over time, being current and the level of brand–service representation.

This research is one of the AI visibility studies we publish under Magna Research.

How Can You Use This Research for Your Brand?

If you are an e-commerce or retail brand, knowing whether your category is one where AI converges or one where it diverges determines which platforms and which shopping queries you should prioritize.

If you want to see the same measurement for your own brand and competitors, choose our AI Visibility Analysis; if you want us to improve how your brand appears in AI answers based on the findings, choose our GEO Services. We explain how we design measurements and interpret findings on our GEO Methodology page.

Related research

• AI Visibility of Travel Platforms in Türkiye 2026 — 80.5% of 195 names appeared on only one AI platform; overlap in the Bodrum query was 4.5%.
• AI Visibility of Car Brands in Türkiye 2026 — ChatGPT, Gemini and Perplexity overlapped 47.9%; Togg appeared in six different purchase queries.

You can find all of our research on our Magna Research page.