Be the answer when buyers ask an AI instead of searching

AI assistants answer in two ways. Some rely on what the model learned in training. Others, such as Perplexity and the search modes in ChatGPT and Gemini, fetch live pages and summarise them with links. Google AI Overviews draw on the same index as Google Search. So the first requirement is simple: the page must be crawlable, rendered and indexed.

Beyond access, the pages that get quoted tend to share traits. They state a definition early, use clear headings that match how people phrase questions, give specific facts, and cite their own sources. They also come from sites whose identity is unambiguous, so the model can tell which company is speaking.

Nobody outside the vendors can promise a citation, and the behaviour changes as products update. What we can do is remove the obstacles, shape the content for extraction, and measure the result prompt by prompt. We document what each vendor publishes about its crawlers and re-check it, because those rules move.

We start with access. OpenAI, Google, Perplexity and others publish the names of their crawlers. We check whether your robots file, CDN or firewall treats them the way you intend. Some companies want to be cited and are blocking the crawlers by default. Others want to stay out of training but remain visible in search, and the settings differ, so this is a decision we make with you.

Next is entity clarity. The model needs to know who you are: legal name, what you sell, where you operate, who runs the company. We align the homepage, the about page, structured data and public profiles so they say the same thing. In Arabic, this includes the spelling of your name and your services, which often varies across the web.

Then structure. We rewrite priority pages so the opening paragraph answers the question outright, headings read like real questions, and tables or lists carry comparisons. Pages that are easy for a person to scan are easy for a model to quote. FAQ sections get matching structured data where it is appropriate.

AI answers do not have a position one to ten, and they vary between runs. So we measure differently. We write a fixed set of buyer prompts in Arabic and English, such as comparisons, how-to questions and who-offers-this questions in a Saudi city. We run them on a schedule across the main assistants and record whether you are cited, how you are described and which sources are used instead.

Expect a baseline in the first month, and trends after three. Wrong or outdated statements are logged and traced to the source that caused them, which is often an old directory listing or a stale page of your own. Fixing that source is usually faster than anything else on the list.

Referral traffic from assistants is small today and growing unevenly, so we also track it in analytics, using the setup described in our marketing analytics service. Treat this as an early-position investment on top of ordinary SEO, not a replacement for it. The same technical foundation serves both.