AEO & GEO for Brand New Websites

Launching a brand new website in 2026 means entering a search landscape that looks almost nothing like the one that existed five years ago. The first page of Google still matters — but increasingly, the answer your audience receives is never a page at all. It is a synthesised, AI-generated response that pulls from multiple sources, attributes citations, and delivers a complete answer without a single click required.

For new websites, this creates both a challenge and a genuine opportunity. The challenge: you have no domain authority, no backlink profile, no ranking history, and no indexed pages. The opportunity: AI search systems care far more about the quality and structure of your content than about how old your domain is. A new website that publishes exceptionally well-structured, authoritative, directly-answering content can appear in Perplexity AI within weeks and in Google AI Overviews within months — competing directly with established players who never optimised their content for AI citation.

This guide gives you the complete playbook: what AEO and GEO mean for new sites, a phased 12-month action plan, and separate strategy chapters for B2B and B2C businesses. Read it once to understand the framework; return to it repeatedly as your site grows.

AEO vs GEO: understanding the distinction

These two terms are often used interchangeably, but they describe related yet distinct disciplines. Getting the distinction right matters for building an accurate strategy.

Answer Engine Optimisation (AEO) is the broader practice of structuring content so that it can be extracted and delivered as a direct answer by any automated system — including Google's featured snippets, voice assistants like Siri and Alexa, zero-click search results, and AI chatbots. AEO has been evolving since the introduction of featured snippets around 2014. Its core principle is simple: structure your content so that the answer to a specific question is identifiable, extractable, and accurate at the paragraph or sentence level.

Generative Engine Optimisation (GEO) is a more recent and more specific discipline: it focuses on being cited and synthesised by large language model-powered search systems — specifically Google AI Overviews, ChatGPT Search, and Perplexity AI. GEO builds on AEO principles but adds additional layers: topical authority architecture, entity recognition, RAG-optimised content structure, and platform-specific citation signals.

For practical purposes in this guide, we treat AEO and GEO as a unified strategy: everything that makes your content good for AEO also makes it good for GEO. The difference is emphasis — AEO focuses on extractability, GEO adds topical authority and entity recognition. Build both simultaneously from day one.

The reality for new websites: what you're up against

New websites face a specific set of obstacles in the AI search landscape. Understanding them honestly is the first step to overcoming them strategically.

The authority gap. AI search systems, particularly Google AI Overviews, weight domain authority heavily in their retrieval and trust scoring. A site with 1,000 backlinks from relevant publications will be retrieved and cited ahead of a site with zero backlinks, even if the new site's content is technically superior. This gap cannot be closed overnight, but it can be closed within 6–12 months with focused effort.

The indexation lag. Before any content can be retrieved by AI search, it must be crawled and indexed by the underlying search engine. For Google, this takes anywhere from a few hours (for high-authority sites) to several weeks (for brand-new domains). For Bing — which powers ChatGPT Search — indexation for new domains can lag even further behind. Submitting your site and individual pages via Google Search Console and Bing Webmaster Tools immediately upon launch eliminates unnecessary delay.

The entity recognition gap. Language models build their understanding of the world through entities — recognised organisations, people, brands, and concepts. A new brand that has never appeared in any publication, Wikipedia article, or external reference is essentially invisible to LLMs as an entity. Building entity recognition is one of the most strategic long-term investments a new website can make, and it begins with consistent brand naming, social profiles, and early press or industry mentions.

Building the foundation: what to set up before publishing

Before you publish a single article, you need a technical and structural foundation that enables AI crawlability, indexation, and trust signalling from day one. These are not optional extras — they are prerequisites for every AEO and GEO tactic that follows.

Content architecture for AI-first websites

The single most important strategic decision you make for a new website is its content architecture. This means: what topics will you cover, how will those topics be organised, and how will the pages link to one another? Getting this right from the start is dramatically easier than retrofitting it later — and it is the primary structural factor that separates new sites that build AI citation authority quickly from those that struggle for years.

The topic cluster model (explained simply)

Imagine your website's content as a wheel. In the centre is your pillar page — a comprehensive, long-form page that covers a broad topic in your field at a high level. Connecting to that centre are cluster pages — focused, detailed articles that each cover one specific sub-topic within the broader theme. All cluster pages link back to the pillar page, and the pillar page links out to each cluster page.

This architecture does two powerful things simultaneously. For traditional SEO, it concentrates topical relevance signals on your most important page. For AI search, it signals to retrieval systems that your site has depth of coverage on a topic — making it more likely to be treated as an authoritative source rather than a single-article resource.

How many topic clusters should a new site build?

For a new site, focus on 1–2 topic clusters in your first 90 days. It is significantly more effective to own one topic deeply — with a pillar and 8–12 cluster articles — than to spread across five topics with 2 articles each. AI search systems recognise depth of coverage; thin coverage across many topics does not register as authority on any of them.

Question mapping: the content brief framework

Before writing any piece of content, map the real questions your audience asks. Use these sources to build your question map: Google's "People Also Ask" results, Reddit threads in your niche, Quora questions, industry forums, LinkedIn comment sections, and AnswerThePublic. For each article you plan to write, identify: (1) the primary question this article answers, (2) 3–5 secondary questions it should also address, and (3) the single-sentence direct answer that should appear in the opening paragraph.

The 12-month phased action plan

Building AEO and GEO visibility from zero is a sequential process. Each phase builds on the previous one. Attempting to skip phases — publishing advanced thought leadership before foundational definitional content exists, or chasing backlinks before your content is worth linking to — wastes resources and produces weak results.

B2B AEO/GEO strategy: the complete playbook

Business-to-business companies occupy a fundamentally different AI search landscape than B2C companies. B2B buyers use AI search tools differently — they are researching vendors, comparing solutions, building business cases, and validating technical claims. The queries they use are longer, more technical, and more intent-rich. The content they need is deeper, more evidence-based, and more explicitly tied to business outcomes.

B2B content priorities for AI citation

B2B entity and author authority

In B2B, who wrote the content matters enormously. A blog post written by "the TechSolutions team" carries a fraction of the E-E-A-T weight of an article written by "Sarah Chen, VP of Engineering at [Company], with 12 years of experience in enterprise cloud infrastructure." B2B AI search users are sophisticated — they are often verifying that the source they are reading has genuine domain expertise. Build named author profiles for every subject-matter expert in your company, and assign each piece of content to the author with the most relevant credentials for that topic.

Additionally, B2B brands should prioritise getting cited in industry-specific publications and analyst reports. A mention in a relevant trade publication, an inclusion in an industry analyst's vendor landscape, or a citation in a professional association's resource library are all external authority signals that LLMs weight heavily when evaluating B2B source credibility.

B2B thought leadership as an AEO asset

Original thought leadership — genuine opinions, predictions, and frameworks from your company's experts — is underutilised in AEO strategy but exceptionally valuable. When your company publishes a named framework ("The Four Stages of Supply Chain Digitisation"), a proprietary methodology, or an original industry prediction, that content becomes an entity reference. Other publications cite it, LLMs encounter it across multiple sources, and your brand becomes associated with a specific intellectual contribution to the field. Even a single genuinely original framework, regularly cited and referenced, can anchor your brand's entity recognition in an AI-search context.

B2B LinkedIn and professional platform strategy

ChatGPT and other LLMs are increasingly capable of incorporating content from LinkedIn articles, professional publications, and industry platforms into their training and retrieval data. B2B companies should publish substantive, article-length content on LinkedIn — not reposts or link shares, but original articles that address professional questions directly. Each LinkedIn article is an additional citation surface, and author profiles on LinkedIn strengthen the entity recognition of both the individual author and the company.

B2B-specific schema priorities

In addition to the universal schema implementations (Article, FAQPage, HowTo), B2B sites should prioritise: Organization schema with complete industry classifications, SoftwareApplication schema for SaaS products, Service schema for professional services, and Dataset schema for any original research data. These schema types help AI systems categorise your brand correctly and surface it for industry-specific queries.

B2C AEO/GEO strategy: the complete playbook

Business-to-consumer companies face a different AI search challenge. B2C queries are typically shorter, more intent-varied, and higher in volume. The buyer journey is often compressed — a consumer might go from discovery to purchase in a single session. AI search is used for product discovery, comparison, recommendation-seeking, and problem-solving. Being cited in AI-generated answers at the discovery and comparison stages directly impacts purchase decisions.

B2C content priorities for AI citation

B2C product page optimisation for AI citation

Unlike B2B, where informational blog content is the primary AI citation vehicle, B2C companies need to also optimise their product pages for AI extraction — because product pages are frequently cited in product recommendation and comparison queries. Key optimisations for B2C product pages include: a clear, question-answering product description paragraph at the top (not a marketing tagline — a functional description), a specifications table in HTML format, an explicit FAQ section addressing the most common product questions, and Product schema with full attribute completion including price, availability, and aggregate rating.

B2C review and user-generated content strategy

AI search systems cite review content — both professional reviews and user-generated content on platforms like Reddit and Trustpilot — far more frequently for B2C queries than for B2B queries. New B2C websites should actively cultivate genuine user reviews, integrate review schema (AggregateRating and Review) on product pages, and build a presence on the review platforms their customers trust. Encourage early customers to post honest reviews not just on your own site but on third-party platforms — these external mentions build entity recognition and provide additional citation surfaces for AI systems.

B2C local SEO and AI search

For B2C businesses with physical locations or local service areas, local AI search is a rapidly growing opportunity. Google AI Overviews are beginning to incorporate local business information for queries with local intent. The foundations of local AI search visibility are the same as traditional local SEO: a fully-completed and regularly-updated Google Business Profile, consistent NAP (Name, Address, Phone) information across all directories, and location-specific content on your website. Add LocalBusiness schema to your website's footer or contact page immediately upon launch.

B2C social proof and community presence

AI search platforms — particularly Perplexity when using its Reddit Focus Mode — frequently surface community discussions and forum content for B2C queries. Establishing an authentic presence in communities where your target audience already asks questions (specific subreddits, Facebook groups, Quora topics, niche forums) serves a dual purpose: direct engagement with potential customers and indirect AI citation building. When your brand or products are mentioned by real community members in substantive discussions, those mentions become citation sources for AI systems responding to product-discovery queries.

Schema markup playbook for new websites

Schema markup is the most direct signal you can send to AI systems about what your content means, who created it, and why it should be trusted. For new websites that have not yet built extensive backlink authority, schema markup is one of the most powerful trust levers available — and it costs nothing but implementation time.

All schema should be implemented in JSON-LD format placed in the <head> section of each page. Validate every implementation using Google's Rich Results Test (search.google.com/test/rich-results) before deploying to production. A single schema syntax error can invalidate the entire block.

Building E-E-A-T from zero: practical steps

E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is not something you can claim — it is something you demonstrate through concrete signals that AI systems and Google's quality evaluators can verify. New websites start at a disadvantage on E-E-A-T, but every action you take in the following areas compounds over time.

Experience signals

Experience means demonstrating that the people behind your content have actually done the thing they are writing about. Add first-person observations and real-world examples to every article where they are relevant. Include original screenshots, data, photographs, or test results that could only exist if you had direct experience with the subject. Reference specific events, decisions, or outcomes from your professional history. The pattern "In our experience running X campaigns for Y type of client, we found that Z..." is a strong experience signal that AI systems recognise from high-quality professional content in their training data.

Expertise signals

Every author on your site should have a fully-developed bio page that includes: professional credentials and qualifications, years of relevant experience, named prior employers or clients (where appropriate), links to external publications or appearances, and areas of specific expertise. For YMYL (Your Money or Your Life) content — health, finance, legal, safety — expertise signals are not optional; they are the primary gate through which AI systems decide whether to trust a source enough to cite it.

Authoritativeness signals

Authority is built externally — it cannot be manufactured on your own site. The most effective authority-building actions for a new site are: publishing original research that others will cite, contributing expert quotes to industry journalists and bloggers (use services like HARO or Qwoted to find journalist requests), guest-posting on established publications in your field, and getting listed in recognised industry directories and resource pages. Each external citation of your brand or content adds a small but cumulative signal to your authority profile.

Trustworthiness signals

Trust is built through transparency. Publish comprehensive disclosures — affiliate relationships, editorial policies, factual accuracy commitments, correction policies. Display your physical address and phone number if you are a legitimate business (LocalBusiness schema makes this machine-readable). Clearly date all content and update it when facts change. If an article contains a factual error, correct it publicly and note the correction at the bottom. Trust is earned slowly through consistent transparency and lost instantly through a single exposed deception.

Link building for AI citation authority

Links remain the most powerful domain-level authority signal for AI search retrieval. The difference between a new site and an established site, in the eyes of AI search retrieval systems, is largely a difference in link authority. Closing that gap is the most important long-term investment a new site can make.

For new sites, the most accessible and highest-quality link-building tactics are:

Original data and research

Publishing original research — even a simple 50-person survey on a specific industry question — is the single most reliable link-building tactic available to new sites. When you are the primary source of a statistic or finding that other writers want to cite, you earn editorial links that are both high-quality and algorithmically legitimate. Publish your findings in a dedicated page, promote them to journalists and bloggers in your niche, and include the data in your own articles so others encounter it naturally.

Expert roundups as a link acquisition vehicle

Publishing expert roundup articles — where you collect quotes from 10–15 recognised experts on a specific question — earns links from the experts themselves, who typically share and link to articles they are featured in. For new sites without existing relationships, this is an efficient way to earn links from established domains while simultaneously building relationships with key industry figures.

Resource page link building

Many established websites maintain "resources" or "links" pages that curate the best external resources on a topic. Find these pages in your niche using searches like "resources" + [your topic] or "useful links" + [your topic], and email the site owner with a personalised pitch for why your specific page deserves inclusion. Conversion rates are low but the links earned are high-quality and persistent.

HARO and journalist request services

Help A Reporter Out (HARO), Qwoted, and similar journalist-request services connect journalists seeking expert sources with subject-matter experts. Responding promptly and substantively to relevant journalist requests earns editorial mentions and links from news sites and industry publications — exactly the type of authoritative external reference that strengthens AI search citation authority. New sites can start earning links from major publications within their first month using this tactic.

The highest-ROI content formats for new sites

Not all content types are equally effective at the two tasks a new site needs to accomplish simultaneously: building organic rankings (to enable Google AI Overview citation) and being directly retrieved by real-time AI crawlers like Perplexity. The following formats deliver the highest return on content investment for new sites.

Why Perplexity is your quickest AI win as a new site

Of the three major AI search platforms, Perplexity AI is the one a brand new website can appear in fastest — often within 2–4 weeks of publishing well-structured content. This is because Perplexity crawls the live web in real time for each query, rather than relying on a pre-built index with accumulated authority signals. A new page that directly answers a specific question can be retrieved and cited by Perplexity even if it has zero backlinks and has never ranked in Google.

To maximise your early Perplexity citation likelihood, focus on three things: ensure PerplexityBot is allowed in your robots.txt, publish content that is exceptionally direct and specific in its answers (Perplexity's Sonar model rewards factual density), and target queries where existing web content is thin or outdated — Perplexity actively seeks fresh sources to supplement stale results.

Monitor your Perplexity citation frequency manually each month for your 20 target queries. When you spot a Perplexity citation of your content, analyse exactly which sentence or paragraph was extracted, and use that as a template for writing similar highly-citable passages in future articles. Early Perplexity wins build the evidence base for what works in your specific topic area.

Tools to track your AEO/GEO progress

GEO measurement is less mature than traditional SEO measurement, but a practical tracking stack can be assembled from the following tools.

For new sites on limited budgets, the four free tools — Google Search Console, Bing Webmaster Tools, Google Analytics 4, and manual AI query testing — give you 80% of the measurement capability you need in your first year. Add paid tools as your traffic and revenue grow.

Critical mistakes new sites make with AEO/GEO

The following mistakes are consistently observed across new sites attempting to build AI search visibility. Each one is costly — either in wasted time, wasted content investment, or delayed authority building. Avoiding them from day one is worth more than almost any positive tactic.

Priority action matrix by business type and timeline

Use this matrix to identify your highest-priority actions based on your business type and where you are in your website's growth timeline.

Conclusion: building AI search authority is a compounding investment

The brands that will dominate AI-generated search results in 2027 and 2028 are the ones building their foundations today. Every piece of well-structured, deeply authoritative content you publish now is a compounding asset — each article builds topical authority, each backlink strengthens domain trust, each schema implementation improves machine parseability, and each AI citation adds another data point to the retrieval algorithms that will decide whether your content is surfaced for the next query in your space.

New websites are not at a permanent disadvantage in the AI search era — they are at a temporary one. And that temporary disadvantage is closing faster for sites that build AI-first content architecture from day one than for established sites attempting to retrofit their legacy content strategy. The window to build a structural AI search advantage is open right now. Use this guide as your operational playbook, return to it as your site grows, and measure your progress monthly against the benchmarks we have set out.

The shift to AI-mediated information discovery is still in its early stages. The best time to invest was two years ago. The second-best time is today.