Solutions · Telecom · AI Answer Index

AI search visibility for Saudi telecom operators

Your customer asks an assistant before asking you. This measures what the assistant tells them.

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What it is

AI Answer Index measures how AI assistants answer questions about a telecom brand. The category calls this AI search visibility, generative engine optimisation or answer engine optimisation. A governed library of real customer questions runs weekly across ChatGPT, Perplexity and Gemini, in Arabic and English, from inside Saudi Arabia. Four indicators are scored on every answer: presence, position, sentiment and citation. Alongside the score, the module records which sources supplied each answer, which factual errors about the brand are reproducible today, which page a retriever actually landed on, and what the brand's own domain tells a machine that reaches it.

What it reads

Platforms
ChatGPT, Perplexity and Gemini: the assistants Saudi customers use that also return sourced answers, which is what makes citation measurable. The list is reviewed quarterly against usage in the Kingdom rather than global share.
Question library
Customer questions in Saudi-dialect Arabic and English, covering billing, coverage, plan comparison, roaming, fiber and FWA availability, complaints, porting and “which operator is best for” questions. Proposed at setup, approved by the operator, refreshed quarterly.
Answer sources
Every URL named in every answer, classified by owner: your own domains, Saudi publishers, government and regulators, foreign publishers, social and video.
Your own domain
Crawler policy, page index, Arabic-to-English page pairing, structured data, and the page a retriever actually reached against the page it should have reached.
Comparison set
Competitor operators scored on the same questions, in the same runs.
Cadence
Full run weekly. A named subset of priority questions daily, feeding the alert queue. Alerts issue on detection, not on the reporting cycle.
Location
Run from inside Saudi Arabia. Answers to the same question differ by country, and a reading taken elsewhere describes a market your customers are not in.

What you get

The index, and the four indicators beneath it

Presence at 30 per cent, position at 20, sentiment at 20, citation at 30. Every reading traces back to the answer that produced it, so the score is auditable rather than declared.

Source composition

Who actually supplies the answers about you, by owner type and by domain. Most markets turn out to be unowned: a long tail of domains each appearing once, and no third party consolidating the ground.

Error register

Reproducible factual errors about your brand, ranked by severity, each with its source and a proposed correction. Wrong service numbers, another company's procedure returned as yours, and old figures presented as current are the recurring three.

Retrieval landing report

Which page on your domain a retriever reached, set against the page that should have answered. Usually the correct page exists and nothing on the site signals it.

Machine legibility audit and remediation pack

What your domain tells a machine, checked against four gates: crawler policy, page index, language pairing, structured data. Findings arrive as a specification your web team can deploy, in delivery order.

How it works

01

Agree the library

Question library, comparison set, platform list and indicator weights are proposed at setup and approved before the first run. The baseline is set on the first full run.

02

Run

Every question, every platform, both languages, weekly. Priority questions daily. Each answer is captured whole, with its sources.

03

Score

Four indicators machine-scored and analyst-checked. Bilingual analysts review Arabic answers rather than translating them.

04

Diagnose

Source composition, error register, retrieval landing and domain checks turn the score into a list of causes.

05

Correct and re-ask

Errors are verified, notified with evidence and severity, and corrected at the page and at the source. The question is re-asked on the next run and the outcome logged.

Who uses it

Corporate communications
Owns the error register. Sees what is being said about the brand in the channel it cannot monitor manually, and gets a workflow for fixing it.
Marketing and brand
Tracks presence and position against competitors, and treats the gap as a content brief rather than an advertising problem.
Digital and web teams
Receive the machine legibility findings as a build specification with a delivery order, not as a list of complaints.
Customer service operations
Sees the wrong numbers and wrong procedures circulating before the call arrives at the contact centre.
Strategy
Reads which institutions and publishers the market treats as authoritative about your category, which is a map of where influence actually sits.

Questions

What is AI search visibility, and why does it matter now?

AI search visibility is whether an AI assistant names your brand when a customer asks a question in your category, and whether it uses your own pages as its sources. It matters because the answer increasingly replaces the visit. The Communications, Space and Technology Commission reports that 45.2 per cent of Saudi internet users now use AI tools, more than double the previous year, rising to 55.7 per cent among ages 20 to 29. Where the answer arrives on the page, the visit often does not follow: Pew Research Center found US click-through roughly halved when an AI summary appeared, at 8 per cent against 15 per cent.

How is this different from SEO?

SEO works on where you rank in a list of links. This works on whether you are named in an answer that replaces the list, which sources that answer draws on, and whether the facts in it are correct. Your SEO agency keeps its brief. This tells them, and you, what the assistants are actually doing with the site.

Which assistants are covered, and how often?

ChatGPT, Perplexity and Gemini, with the list reviewed quarterly. Full runs weekly, priority questions daily, alerts on detection.

Does the answer change in Arabic?

Consistently, yes, and not only in wording. Arabic answers draw on a visibly different source pool, and where local Arabic material is thin the assistants fall back on foreign content, including procedures from other countries presented as local fact. Every run covers both languages for that reason.

Can you make an assistant change what it says about us?

No, and any supplier claiming otherwise is selling something else. Platforms cannot be compelled to change an answer. They change what they read, so the work runs through the source: correct the page, correct the third party, make the domain legible, then re-ask and verify.

How is this different from the AI visibility tools built abroad?

Those tools report presence, position and sentiment for a brand. This adds citation share, source composition, a reproducible error register, retrieval landing and a machine legibility audit, and it runs natively in Arabic from inside the Kingdom. In this market the last point decides the other five.

You already know what your customers tell you. Do you know what they tell everyone else?

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