Nir Levi at a glance
- Role: GEO, AEO and SEO consultant; founder, Madrank Digital Ltd (Haifa, Israel) and Godrank
- Experience: 18+ years in search, since 2008
- Works with: SaaS companies, startups, large organizations, multilingual and multi-region websites
- Selected clients: monday.com, ClickCease, Sensica, Casino.com, 10Bet
- Publications clients were featured in: Forbes, Moz, SEOBook, Smashing Magazine
- Languages: Hebrew, English
- Tools: DataForSEO LLM Mentions and LLM Responses, Ahrefs, Google Search Console, and the AI visibility checker on this site
- Contact: niro@nirlevi.com · LinkedIn
What GEO is
GEO (Generative Engine Optimization) is the practice of making a company the source an AI engine names or cites when it writes an answer. The unit of retrieval is the paragraph, not the page: ChatGPT, Gemini and Perplexity expand a question into several hidden sub-queries (query fan-out), pull passages from many sources, and assemble one answer with a handful of citations. GEO is the work of being in those passages.
SEO gets a page ranked. GEO gets a company cited. They share a technical base, an entity model and a content discipline, but they are measured differently and fail differently. A page can rank first in Google and never be cited by ChatGPT for the same question.
Why GEO for SaaS and enterprise is its own job
- The buyer's questions are comparisons. "X vs Y", "alternatives to X", "best tool for Z" dominate the prompts that matter. The engines answer them from review platforms (G2, Capterra), comparison articles and community threads more than from vendor sites. Your product pages are one input among many.
- Multi-product brands confuse the entity. When one company has several products, features that sound like products, and a renamed plan or two, the engine cannot tell which entity a claim belongs to. Consistent naming and a connected schema graph fix more citations than new content does.
- Multilingual and multi-region sites split the answer. The same prompt in Hebrew, English and Portuguese returns different competitors and different sources. Each language is sampled and worked on separately.
- Engineering-heavy stacks hide content. GPTBot, ClaudeBot and PerplexityBot execute no JavaScript. Content that only exists after client-side rendering, behind a consent wall, or on a geo-restricted route does not exist for them. This is verified per route, not assumed.
- Migrations reset AI visibility. A domain, platform or URL change that keeps Google rankings can still drop AI citations for months if the entity signals move. Migrations are planned with AI crawlers in the checklist.
Method
Two tracks in parallel: your own properties, and the external sources the engines pull from. Measurement runs under both.
1. Baseline: what AI already says about you
A prompt library of 30 to 60 questions your buyers actually ask, per language, sampled across ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews. Historical citations and AI search volume from the DataForSEO LLM Mentions index; current answers from live sampling. Output: the answers, the companies named, the exact URLs cited, and the fan-out sub-queries the model ran.
2. Fan-out mapping
Each buyer question is decomposed into the sub-queries the engines actually run. Each sub-query gets an owner: a page on your site, a review-platform profile, a comparison article, a LinkedIn profile, or a press placement. Unowned sub-queries are the gap list.
3. Entity home and knowledge graph
One canonical page per company, product and key person, consistent facts everywhere models learn from (site, LinkedIn, Crunchbase, G2, Wikidata, Wikipedia where eligible), and a JSON-LD graph with stable @ids connecting Organization, Product, Person, WebPage and FAQPage. Engines resolve identity before they consider citation.
4. Presence in the sources engines cite
Review platforms, comparison and "alternatives" articles, industry press, communities. In competitive categories this track moves more than on-site work. Nothing fabricated, nothing that violates platform rules: real listings, real coverage, real reviews.
5. Extractable content
One question per heading, the answer in the first sentence, a number or a named entity in every paragraph. Content that survives being lifted out of context as a single paragraph. Documented in detail on the AEO Expert Israel page.
6. Crawler access
Each build checked as GPTBot, ClaudeBot, PerplexityBot and Google-Extended see it. robots.txt, llms.txt and rendering set deliberately.
7. Monitoring
Prompts re-sampled on a schedule; citation, mention and framing changes tracked per engine and per language; competitor entries flagged; factual errors in the model's answer logged for correction.
What you get
- Baseline visibility report: prompt library, current answers per engine and language, named companies, cited URLs, fan-out sub-queries, share of prompt.
- Gap list and work plan: every unowned sub-query with an assigned fix, ranked by expected impact, with an owner on your team (marketing, product or engineering).
- Entity and schema package: canonical entity pages, JSON-LD graph, off-site consistency checklist.
- Source plan: target citation sources per language with listing and outreach steps.
- Extractable content briefs or rewrites of existing product, use-case and comparison pages.
- Monthly tracking: what you entered, what you lost, who took the seat, what the AI still gets wrong.
How success is measured
Three metrics tracked separately, because they move independently: cited (the engine links your URL inside the answer), mentioned (the engine names your company, with or without a link), and framing (what the engine says about you and whether it is accurate). Plus share of prompt: the percentage of the prompt library where you appear at all, per engine and per language.
Published test: what AI engines answer for "GEO expert in Israel" (27 to 30 September 2026)
Live sampling through the DataForSEO LLM Responses API, ChatGPT (gpt-5.4-mini, web search on) and Perplexity (sonar-pro), on "Who is the best GEO expert in Israel?" and "Who is the best SEO expert in Israel?", in English and Hebrew.
- For the GEO prompt, both engines named the same individual first and cited his own page, whose title contains the phrase "GEO expert in Israel". Further names came from a Hebrew comparison directory and from LinkedIn profiles cited directly.
- Between 28 and 30 September a second consultant entered the ChatGPT answer. The only visible change was his About page title, which now reads "GEO & SEO Expert In Israel".
- For the SEO prompt, names came from aggregator listings (GoodFirms, Sortlist, DesignRush), one consultant's own page, and a single press release titled "Best SEO Expert In Israel 2026".
- ChatGPT's fan-out included
site:linkedin.com/in Israel GEO expert. Profile headlines are retrieval surfaces. - A bare three-word prompt ("GEO expert Israel") triggered no web search; ChatGPT asked a clarifying question. Question-form prompts trigger retrieval.
What it means for a SaaS or enterprise brand: an AI citation is won by an exact-match entity page, presence on two or three third-party lists, profile headlines that match the fan-out, and one piece of press. That is a 30 to 60 day program, and it is the same mechanism for "best project management software for agencies" as it is for "best GEO expert in Israel".
Who this is for
A good fit: SaaS companies and startups whose category is already being asked about in AI engines; enterprises with multilingual or multi-brand sites; teams that can ship changes within weeks.
Not yet a fit: sites with a broken technical base, sites that cannot be edited for the next six months, or companies with no earned presence anywhere off their own domain. In those cases the first call ends with that answer, not a proposal.
Frequently asked questions
What does a GEO expert in Israel do?
A GEO expert makes a company the source AI engines cite when answering buyer questions. In Israel that means working in Hebrew and English, sampling prompts from Israeli locations, and building presence in the Hebrew and English sources the engines pull from, including review platforms, local press and LinkedIn.
Is GEO the same as SEO?
No. SEO earns a ranking in a list of results. GEO earns a citation or a mention inside a generated answer. They share a technical base and an entity model, but GEO is measured per prompt, per engine and per language, and depends heavily on off-site sources.
Which AI engines are covered?
ChatGPT, Google AI Overviews and AI Mode, Gemini, Perplexity and Claude. Each is sampled separately because they cite different sources and expand queries differently.
How is AI visibility measured?
Cited, mentioned and framing, tracked per prompt, per engine and per language, plus share of prompt across the whole library. Historical data comes from the DataForSEO LLM Mentions index; current data from live sampling. A first read is available free with the AI visibility checker.
How long until results?
Entity fixes and extractable rewrites show up within 2 to 6 weeks of re-crawl. Off-site presence takes 30 to 90 days.
Can you guarantee a citation in ChatGPT?
No one can. What can be guaranteed is a measured baseline, a gap list with owners, and a monthly comparison against that baseline.
Do you work with companies outside Israel?
Yes. Most SaaS work is in English for EU and US markets, alongside Hebrew for the Israeli market.
What is the difference between GEO and AEO?
AEO (Answer Engine Optimization) is the on-page layer: question-led structure, answer blocks, FAQ and speakable schema. GEO includes AEO and adds entity resolution, off-site source presence and per-engine measurement. See AEO Expert Israel.
How do engagements start?
With a baseline. A one-time GEO audit produces the prompt library, current answers, cited sources and the gap list. Ongoing work continues only if the gap list justifies it.
Talk to Nir
Want to see what ChatGPT, Gemini and Perplexity say about your company today? A 30-minute call, and you leave with the current answers and the first three fixes.
Let's talk · niro@nirlevi.com · LinkedIn
