How to Promote a Website in the Age of AI – Guide 2026

25/08/2026

Users in Israel ask a question and receive a full answer. ChatGPT, Gemini , Perplexity , and Google’s AI Overviews summarize, recommend, and refer – often without the user even visiting the site. This change is felt in every Analytics report.

The business problem is clear: rankings are maintained, organic traffic is eroded. The opportunity is equally clear. Brands that succeed in being the source that the engine cites gain high-quality exposure and high trust from an audience that has already received a recommendation.

The guide is written for business owners, marketing managers, webmasters, and digital agencies involved in organic promotion in Israel. It offers a practical roadmap for promoting a website in AI engines: understanding the change in the search market, GEO principles, conversational keyword research , building citation-worthy content , technical infrastructure, structured data , strengthening EEAT , adapting to the local market, and measurement.

All recommendations are based on 2025–2026 data and actual engine behavior. Those who implement them build a real advantage in SEO 2026 and strengthen brand visibility in AI over time.

The gist of things

• Search engines have become answer engines, and the surfer’s journey sometimes ends within the answer itself.
• A high ranking on Google does not guarantee traffic – a combination of classic SEO with generative engine optimization is required.
• GEO focuses on mentions, quotes, and brand presence in ChatGPT, Gemini , and Perplexity responses.
• Content that provides a direct answer, is data-based, and up-to-date, receives priority in citation.
• An open technical infrastructure for AI crawlers and structured data are basic conditions for success in ChatGPT SEO .
• Brand authority, off-site mentions, and quality Hebrew are critical for organic promotion in Israel.
• Combined SEO and GEO measurement allows you to prove results and improve accordingly.
• AI web hosting companies

What has changed in the world of SEO with the introduction of artificial intelligence into search results?

The results page we’ve known for two decades has changed. Instead of a list of blue links, the user gets a single, synthesized answer built from multiple sources. This change requires a rethink of the entire promotion strategy.

From a list of links to a single synthesized answer

Google is no longer just a search engine, but an answers engine . The system breaks down the query into sub-questions, pulls information from different sources, and assembles a coherent answer. Smart search results of this type display citations to sources, but most of the attention remains within the answer itself.

Fewer Clicks, More Zero-Click Search

When the information is displayed in full at the top of the page, the user simply doesn’t click. Zero-Click Search primarily hurts short, informative queries, and lowers the CTR of organic results below the generated answer.

What is happening in the Israeli market?

AI Overviews are currently operating in Hebrew and appear at the top of the results page, above the ads and regular results. Many Israeli sites are reporting a decrease in the number of visits, along with an increase in their quality.

Those who enter after reading an AI response have already gone through the research phase, and come with a clearer intention.

The systems behind SGE derive citations in most cases from the top ten results. A strong organic ranking remains a prerequisite, but it is no longer sufficient on its own.

Website Promotion with AI Engines – Basic Principles for Those Starting Out in 2026

The shift to generative answers requires a change in mindset. Instead of fighting for the top spot on the results page, the new task is to enter the answer itself – as a source that the model cites, recommends, and mentions by name. This is the starting point for anyone starting the journey in the coming year.

The difference between traditional SEO and GEO (Generative Engine Optimization)

Generative Engine Optimization is an optimization that aims to make the brand appear in the body of the answer of a language model. The field of AEO , answer optimization, complements it and focuses on direct questions. Both fields do not replace classic SEO but build on it.

Map of relevant engines in the Israeli market

• ChatGPT – Live search with source display; ChatGPT promotion is currently the main goal in terms of user volume.
• Perplexity – displays visible citations for each claim, making it a particularly measurable arena.
• Gemini – Integrated into the Google ecosystem, search, Workspace, and Android.
• Claude – Preferred for professional, research, and business uses.

New success metrics you should start measuring

The dashboard is changing. Instead of just rankings, it measures mention frequency , source citation rate, mention sentiment, and referral traffic coming from AI engines.

The most significant metric is Share of Voice – your share of the total mentions in answers versus your competitors in the same category. This metric tells the real story of your digital visibility.

How language models select sources of information to cite

AI engines don’t “remember” the entire internet. When a user asks a question, the system runs a process called RAG (Retrieval-Augmented Generation): it formulates a query, retrieves information from live sources, ranks the results, and only then formulates an answer with citations in AI .

What increases the chances of your content being selected?

• Exact semantic match between the question and the wording on the page
• Independent paragraphs (chunks) that can be extracted without further context
• Clear, concise, and non-verbal language
• Consensus information – the same fact also appears in other reliable sources

The role of authority signals and digital reputation

Authority signals are the external proof that a brand is trustworthy. Media mentions, Wikipedia profiles, user reviews, professional databases, and industry websites all strengthen the chances of selection. A brand that appears repeatedly in a single thematic context becomes part of an informational consensus in its field.

The importance of up-to-date and up-to-date information

Content freshness directly affects ranking in information retrieval. Visible publication and update dates, year indication in the title and body of the text, and fresh data provide a clear advantage.

Keyword research in the age of conversational search

Once we understand how the models select sources, the next step is to understand what they are being asked. Classic keyword research , based on search volume and competition, is no longer enough. In the era of conversational search, the user writes a complete question in natural language, often with a business or personal context.

Long queries and deciphering the intent behind them

A typical query in 2026 looks like this: “Which media management service is suitable for a small business in Israel with a budget of 3,000 NIS per month?” This is a true long tail , so it is important to map the user’s search intent before writing the content.

Tools for analyzing common queries and prompts

• Google Search Console – a reliable source for real queries from Israeli surfers.
• Ahrefs and Semrush – AI modules that show brand mentions in generated answers.
• AlsoAsked and AnswerThePublic – mapping follow-up questions.
• Manual questioning – Enter key prompts in ChatGPT, Gemini , and Perplexity and check which sources are cited.

From a list of words to thematic clusters

Instead of a list of isolated words, we built Topic Clusters : a central pillar page covering a broad topic, surrounded by sub-pages answering specific questions, all linked together. Such a structure signals complete thematic authority to the models.

Building content that AI engines love to cite

Once you have mapped the queries and clusters, comes the practical part: generating quotable content that a language model can extract an accurate answer from. The rule is simple – the clearer, more structured, and more source-backed information, the more likely it is to appear in the generated answer.

Open with a reply, not an introduction.

The inverted pyramid method works great: immediately after the headline, write a direct answer of 40–60 words, and only then expand. Avoid long marketing openings.

Scanned structure helps with extraction: question-like subheadings, short paragraphs, numbered lists, comparison tables, and summary boxes.

A unique value that cannot be copied

Original research is the best reason to cite you. Consider publishing:

• Independent survey among customers or professionals in Israel
• Aggregated performance data from your system
• Local test cases with real numbers
• Expert quotes with full name and exact position

Generic content that is mass-produced and does not add new information is almost never mentioned.

Review and refresh as usual

Content refresh is an integral part of SEO content writing. Perform a quarterly Content Refresh and maintain quality and up-to-date content .

Technical Optimization: Website Infrastructure Ready for AI Bot Scanning

Great content won’t be cited if bots can’t reach it. This is where precise technical SEO comes in, ensuring that every page is accessible, quickly read, and understandable to the machine.

The first decision is strategic: block or allow. Blocking protects the content from model training, and removes the brand from responses that users see. For most businesses in Israel, visibility is worth more than protection.

Scanning permissions: Who gets a key to the site?

The robots.txt file is the starting point. Each provider runs its own bot, and each one plays a different role.

Speed, stability, and server-side rendering

A large portion of the models do not run JavaScript. A website built as a client-side application simply looks empty to them. Server-side rendering ( SSR ) or static rendering ensures that the content is present in the initial HTML code.

• Core Web Vitals mobile compliance
• HTTPS is correct on all pages
• An updated and error-free XML sitemap
• Hierarchical and clear address structure
• Canonical tags to prevent duplication

llms.txt and the new devices

The llms.txt file is an emerging standard: a Markdown document at the root of the domain that points to key pages and explains the site’s structure to the model. It is not yet mandatory, and its implementation is cheap and provides a head start.

Structured data and schemas as a language shared with the machine

Once the technical infrastructure is ready for crawling, the next step is to translate the content into a language that the machine understands without guesswork. Schema Markup in JSON-LD format provides just that: an unambiguous definition of who you are, what you offer, and to whom. Structured data reduces uncertainty in identifying entities, which is why language models rely on it when selecting a source for citation.

A language model doesn’t guess who wrote the article. It reads what you declared about it in the code.

Types of agreements that should not be skipped

Not every schema is suitable for every page. The table arranges the main types by use:

Consistency is a basic requirement: the same name, address, and phone number (NAP) across all your digital assets.

Linking entities to build an identified authority

Entity SEO starts with the sameAs attribute, which links consent to LinkedIn, Facebook, Wikipedia, Wikidata, and Crunchbase profiles. This builds an organizational knowledge graph that confirms the brand’s existence in external sources.

• Using @id to link internal entities on a site
• Connecting connectors to fixed profile posts
• Testing with Google’s Rich Results Test tool
• Basic validation using Schema Markup Validator

Proper markup increases the chance of Rich Results appearances and strengthens the foundation of brand authority.

Strengthening EEAT and building digital brand authority

Language models look for signs that someone real, experienced, and trustworthy is behind the content. The four components of EEAT – experience, expertise, authority, and credibility – have become the foundation upon which brand authority is built with results. In YMYL fields like healthcare, law, insurance, and finance, the bar is particularly high, and AI engines tend to cite only sources with a clear professional identity.

Author pages that build real trust

A weak author page is worthless. Build a full profile for each author:

• Real photo and full name, not a system nickname
• Position, education, seniority and areas of expertise
• Link to LinkedIn and professional profiles
• List of publications, lectures and certificates
• Person Schema markup to connect the entity to the brand

Community presence and brand mentions

AI engines draw a significant portion of their answers from community discussions. Reddit , Quora, professional Facebook groups in Israel, and industry forums have become a major source of citations. Brand mentions generated from a helpful and authentic answer are worth much more than a spammy link.

A brand that is talked about in places where the model reads – gets a quote.

Links and mentions in the Israeli market

Local link building works best through digital PR : expert articles in Calcalist, Globes, and TheMarker, interviews on business podcasts, and original research with Israeli data.

Local content strategy for the Israeli market

Brand authority is built in a local arena as much as in a global arena. Language models that generate answers in Hebrew draw information from a relatively limited database, so a well-organized Israeli website has a real opportunity to become a cited source. Promoting websites in Hebrew requires an understanding of the language, the audience, and the search patterns unique to the Israeli market.

Language complexity versus generative models

Hebrew poses a challenge for natural language processing: rich morphology, unpunctuated spelling, many roots and inflections, and frequent mixing of English terms. A model has difficulty recognizing that “promote,” “advance,” and “promote” refer to the same concept.

• Consistent use of one term for each concept throughout the site
• Interpretation of acronyms on first appearance, e.g. VAT (Value Added Tax)
• Including common spelling variations in the body of the text
• Short and clear sentences without unnecessary slang

Business presence in geographical areas

Local SEO relies on a complete and up-to-date Google Business Profile : accurate category, real photos, hours of operation, and ongoing response to reviews. Dedicated landing pages for Tel Aviv, Haifa, Jerusalem, and Beersheba strengthen geographic search and provide AI engines with clear local context.

Two languages, two audiences

Bilingual content requires a well-organized structure and proper hreflang tags between versions. Literal translation undermines trust; cultural adaptation that adapts examples, currencies, and regulations to the target audience is preferable.

Measuring, monitoring, and controlling performance in AI tools

Once you’ve built content, infrastructure, and authority, the key question is whether it works. Measuring performance in the age of generative search requires new metrics on the part of sellers. Traffic from AI engines is small in volume, but its quality is exceptionally high: users arrive after receiving a recommendation, so their conversion rates are higher.

Identifying new traffic and crawl sources

The first step is to set up a custom channel group in GA4 that will collect referral traffic from chatgpt.com, perplexity.ai, gemini.google.com, and copilot.microsoft.com. Compare dwell time, scroll depth, and conversions against regular organic traffic .

At the same time, server log analysis reveals how often GPTBot , ClaudeBot , and PerplexityBot are crawling the site. An increase in crawl frequency is an early sign of improved AI visibility .

Tools for tracking visibility in generated responses

Manual mention monitoring is not enough over time. Combining dedicated tools gives a continuous picture:

It is recommended to add monthly manual tests of ten key prompts in Hebrew and English.

An integrated report that connects the whole picture

Build a single SEO report in Looker Studio that unifies Search Console, GA4, and mention monitoring data. Recommended monthly metrics: Citation rate, share of voice vs. competitors, mention sentiment, referral traffic , and actual conversions.

conclusion

The most common mistake is to see SEO and GEO as two separate worlds. In reality, they rely on the same fundamentals: a technically sound website, original content that provides real value, and brand authority built over time. What serves Google also serves ChatGPT, Perplexity, and Gemini.

The practical order of work is clear. Start with technical infrastructure and opening access to crawlers like GPTBot and ClaudeBot , continue with structured data that explains to the machine who you are, build quotable content that opens with a direct answer, strengthen EEAT with author pages and brand mentions, adapt the message to the Israeli audience and close with ongoing measurement. This is the skeleton of any serious SEO work plan for the coming year.

The field is moving fast. Algorithms change, new engines come into play, and user search patterns continue to evolve. Promoting a website on AI engines requires constant experimentation, monthly visibility checks, and small adjustments along the way. Brands that start now gain an advantage that is difficult to achieve later.

The first step is simple: Conduct an initial visibility audit and see how your brand is mentioned in the responses of leading AI engines. Based on the findings, build a quarterly GEO strategy with measurable goals. This is how digital marketing 2026 goes from reacting to changes to planning ahead.