AI SEOPart 3 of 3: The AI Search Series

Does Your AI Visibility Report Reflect What Customers in Dubai Actually See?

The short answer

For a Dubai business, the useful question is whether relevant customers can find an accurate, suitable recommendation under conditions that resemble their own search.

We reviewed the SEO of a language institute whose traffic figures looked impressive. Much of that traffic came from the United States and India. The institute did not operate in those markets or offer its service online.

The numbers described website activity, but they did not demonstrate that the business was reaching suitable customers.

An AI visibility report can create the same problem. A brand may appear frequently in answers collected from another country, in the wrong language or for questions unrelated to the services it wants to sell. Before celebrating the percentage, check what it represents.

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Before celebrating the percentage, check what it represents.

Barish Elrekabi, DGTL Force

A country setting can change the competitive field

OtterlyAI’s October 2026 regional study compared more than 4.25 million citations across four markets and seven AI engines. UK answers sent 30.7% of citations to UK sites, while the corresponding local-source figures were approximately 76% for Germany and France. The share also varied substantially by engine.

This is vendor research covering Western markets, with its own prompt set and source-classification method. It contains no UAE or Arabic benchmark. We would not use its percentages to forecast Dubai performance.

It does, however, give us a reason to test regional differences rather than assume that one global collection describes every customer’s experience. The UAE implications below are a proposed measurement approach, not findings established by that study.

Define the audience before collecting answers

“Dubai customers” can include residents comparing nearby services, procurement teams evaluating UAE suppliers, parents choosing an academy or overseas investors researching a local provider. Those audiences ask different questions.

Audience 01ResidentsComparing nearby services in their own area.
Audience 02Procurement teamsEvaluating UAE suppliers for projects.
Audience 03ParentsChoosing an academy or nursery for their child.
Audience 04Overseas investorsResearching a local provider before committing.

Record the target service, geography, customer type and stage of decision. A business serving one neighbourhood needs a different question set from a supplier selling across the GCC.

English and Arabic questions deserve separate attention where both are commercially relevant. Work from how each audience actually asks, with fluent review of the phrasing. A literal translation may preserve the words while missing the local terminology or intent.

Build a question set that reflects buying decisions

Separate informational questions from commercial ones. “What is a volleyball academy?” and “Which volleyball academy offers beginner classes near me?” serve different needs. Both may matter, but their visibility should not be presented as equivalent evidence of purchase intent.

For each service, include a manageable mix of category discovery, provider comparison, location-specific needs and important constraints. Age group, delivery area, certifications, availability or budget may change which recommendation is suitable.

Keep branded questions separate from unbranded discovery questions. It is useful to know whether an assistant describes the business accurately when asked by name, but that does not show whether it introduces the business to someone choosing a provider.

Ask your agency to disclose the measurement conditions

SettingWhat the report should explain
MarketThe declared location and collection region, including what cannot be controlled
LanguageHow English and Arabic questions were developed and reviewed
ProductChatGPT, Gemini, Perplexity, AI Mode or AI Overviews, with the available model or mode
CollectionConsumer interface or API, account state and relevant personalisation settings
RepetitionHow often each question was run and whether the method stayed consistent
ScoringDefinitions of mention, explicit recommendation, accuracy and competitive share

These conditions do not make a test representative of every customer. They make its scope understandable and its changes easier to interpret. An API result and a consumer-interface result should not silently be treated as interchangeable.

Score suitability as well as appearance

A nursery recommended in the wrong city is a poor match. So is an academy recommended for an age group it does not accept. Record whether the answer correctly represents location, service scope and suitability, as well as how prominently it names the business.

Track the supporting sources separately. An assistant may recommend the client using third-party evidence without citing the client’s website. Equally, it may cite the website for a fact without recommending the business.

For a repeatable pilot, select 20 commercial questions per relevant language and run each three times under documented settings. Keep the set unchanged for four weekly checks. This is a practical starting design, not a statistically representative estimate of market share.

20commercial questions per relevant languagePilot design
3xruns of each question under documented settingsPilot design
4weekly checks with the question set unchangedPilot design

Use Google’s generative AI performance reporting as a complementary view of actual impressions by page and country where available. Keep that first-party exposure data distinct from a synthetic prompt benchmark.

Connect regional visibility to the business

Check whether identifiable referrals become suitable enquiries, appointments and customers. Ask where those customers are based and which service they need. Monitor branded search and direct traffic as supporting context, while recognising that other marketing and market conditions affect both.

If visibility rises without enquiries, investigate the questions, geography, recommendations, landing pages and buying cycle. Our AI SEO measurement framework explains that sequence. Our guide to website foundations before more blogs covers the changes that investigation may identify.

We believe clients deserve to understand whether a report reflects the people they can actually serve. That principle shapes our approach to AI SEO in Dubai. Speak to DGTL Force about a baseline grounded in your market, services and customers.

BE
Written byBarish Elrekabi

Co-founder and Director of DGTL Force, an AI SEO and performance marketing agency in Business Bay, Dubai. Former Procter and Gamble marketer; led group marketing at The Grooming Company Holding through its acquisition.

Sources

  1. OtterlyAI: AI Search Index UK Regional citation study across four markets and seven AI engines
  2. Google Search Console Help: Generative AI performance report First-party impressions in AI Overviews and AI Mode by page and country
  3. Google Search Central: Managing multi-regional and multilingual sites How Google handles content for different languages and regions

Research checked November 2026. Figures belong to their publishers and reflect their own samples and methods.

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