AI Visibility Resources
This library collects QBiz guides on AI visibility, Google AI Overviews, ChatGPT source selection, llms.txt, AEO vs SEO and local-business readiness. It is written for business owners who need a practical place to start, not another abstract trend briefing.
Start here
The guides are free to read. Each one explains what it covers, which evidence it uses and which parts of the work are still controlled by the platforms, not by an agency.
AI-generated answers now sit beside traditional search results and can shape a buyer's decision before they click through to a website. The old work still matters: crawlable pages, clear service information, links, reviews and technical SEO. What has changed is the format in which some of that information is read and summarised.
These resources focus on the on-site work a business can check: whether a page states the service plainly, whether schema supports the visible copy, whether crawlers can reach the content, whether FAQs answer real buyer questions and whether related pages help a search system understand the business.
On-site clarity is half the picture. The other half sits off your own pages: brand distribution and earned mentions in the independent sources AI systems already read, so an answer engine can corroborate what your site says rather than take it on trust. The guides keep that in view, and the service pages explain how QBiz handles it as part of the same work.
The library is organised by use case. New to the topic? Start with the AI visibility guide. Comparing it with SEO? Read the AEO vs SEO page. Trying to understand a specific platform or file standard? Use the ChatGPT, Google AI Overview and llms.txt explainers.
Where a guide cites a statistic, it links to the source. Where it discusses platform behaviour, it keeps the claim bounded: what can be observed in search results, what is documented by the platform and what remains outside anyone's control.
Where to show up
The platforms that drive most commercial answers select sources in different ways. Here is what each one weighs and what your content needs to be considered.
Large-scale AI answers in Search
How it selects sources: Pulls from indexed pages, weighs quality signals and prefers structured answers. It extends existing rankings but applies stricter content standards.
What your content needs: Schema markup, clear H2 and H3 structure, FAQ sections and explicit service definitions. Technical SEO foundations plus answer-format content.
Major conversational search platform
How it selects sources: Searches the web in real time and selects sources that directly answer the query. It favours specificity and clarity over domain authority alone.
What your content needs: Explicit statements of what you do, where, for whom and why you are credible. Entity-level clarity, so AI understands you as a business, not just a page.
More than 100 million queries per week
How it selects sources: Indexes and cites multiple sources per answer and attributes inline. Query volume supported by TechCrunch reporting that Perplexity CEO Aravind Srinivas said the AI search engine was performing 100 million queries each week.
What your content needs: Long-form, well-organised content with clear section headings and supported data points. The clearer your content, the more likely it can support citations.
Bing-powered
How it selects sources: Draws from the Bing index and applies conversational ranking. Bing SEO basics plus structured data and clear business definitions.
What your content needs: Bing Webmaster Tools verification, complete schema and direct answer formatting. Often overlooked: Bing optimisation is Copilot optimisation.
Figure 1
The platforms that drive most commercial answers select sources in different ways. Each card pairs what the platform weighs with what your content needs.
Extends rankings, applies stricter standards
Pulls from indexed pages and prefers structured answers. Needs schema, clear heading structure, FAQ sections and explicit service definitions.
Favours specificity over domain authority
Searches the web in real time and picks sources that directly answer the query. Needs explicit statements of what you do, where, for whom and why you are credible.
Cites multiple sources and attributes inline
Needs long-form, well-organised content with clear section headings and supported data points.
Draws from the Bing index
Needs Bing Webmaster Tools verification, complete schema and direct answer formatting. Bing optimisation is Copilot optimisation.
Resource Library
Each resource tackles a specific question about AI visibility. Start wherever matches your current situation, or follow the suggested reading order below.
Research
An independent study examining how local service businesses appear in AI-generated search results across ChatGPT, Perplexity, Google AI Overviews, and Gemini. Published June 2026, available as a SocArXiv preprint and archived on Zenodo with the paper, audit script, and supporting data files.
Archive, PDF, data, and code on Zenodo
Dataset + code companion on Kaggle
Cite the permanent record on Figshare (DOI: 10.6084/m9.figshare.33086327)
ResearchGate preprint (alternate discovery route for the same UK study)
Eastwood, E. (2026). AI Visibility Gap Report 2026 (2.0). QBiz Leads AI. Preprint: https://osf.io/preprints/socarxiv/dz9rg_v1. Archive + DOI: https://doi.org/10.5281/zenodo.21182318. Dataset companion: https://doi.org/10.34740/kaggle/dsv/18044594. Also on Figshare: https://doi.org/10.6084/m9.figshare.33086327
Guide
The foundational guide. Covers what AI visibility means in practice, how it differs from traditional SEO, which platforms matter and what the shift means for businesses that depend on being found online. If you read one resource first, make it this one.
Explainer
Cuts through the hype around "ranking in ChatGPT". Explains how ChatGPT selects sources for its answers, what makes a business citable, and the specific content and technical signals that increase your chances of being recommended when someone asks ChatGPT for help.
Comparison
A side-by-side comparison of traditional SEO and answer engine optimisation (AEO). Covers where the two overlap, where they diverge, and how to build a strategy that works for both without doubling your workload. Includes a practical breakdown of which tactics transfer and which do not.
Explainer
A practical explanation of the llms.txt standard: what it does, how AI platforms use it, how to create one for your site, and whether it makes a measurable difference to AI visibility. Covers the specification, real-world adoption and the cases where it matters most.
Checklist
A step-by-step checklist covering every AI visibility signal a local business can control: from Google Business Profile optimisation to structured data, content clarity, review management and AI crawler access. Built for businesses that serve a geographic area and need AI to recommend them locally.
Where do you stand?
Use this as a reading aid, not a market-wide scorecard. The labels show common page states QBiz looks for during reviews: whether the content can be crawled, whether it answers a buyer's question, whether the page structure is clear and whether the business has enough proof to be considered a useful source.
Pages with weak or hidden answers that search and AI systems struggle to read or interpret.
Crawlers can reach the page, but the answer is vague and easy to skip over.
Content is organised around clear questions, with headings and schema that match the copy.
The page is easier to cite when it matches the query and the proof is visible.
Figure 2
A reading aid, not a market-wide scorecard. These are common page states QBiz looks for during reviews, in the order a page tends to move through them.
If the same buyer question appears in Google, ChatGPT or Perplexity, a page with a clear, crawlable answer has more chances to be selected than a page that hides the answer in vague service copy. There is no trick to it: state the service, show the proof, mark up the page properly and keep the information consistent across the site.
AI Overviews, ChatGPT and Perplexity can summarise options before the user visits a website. That does not make traditional SEO irrelevant, but it does mean the source page has to be useful when its answer is lifted into a shorter format. Clear definitions, process detail and service limits matter more than a generic headline.
Many sites already have enough pages. The problem is that the important details are scattered, unmarked or written for a broad brochure rather than a specific buyer question. The guides show where to look first: core service pages, schema, internal links, FAQs, review signals and crawl access.
Suggested reading order
If you are new to AI visibility, follow this sequence. It moves from the basic concept to strategy, platform-specific questions, technical files and local-business implementation.
Understand the shift from traditional search to AI-generated answers.
Learn what changed, what didn't, and how to cover both.
See how the biggest AI platform selects sources to recommend.
Technical: tell AI crawlers exactly how to read your site.
Apply everything to your specific business, step by step.
Figure 3
If you are new to AI visibility, this sequence moves from the basic concept to strategy, platform questions, technical files and local implementation.
Many AI visibility guides stop at platform announcements. The QBiz resources add practical checks from commercial queries, visible citations, documented crawler behaviour and page-level audits. That does not mean every platform decision is knowable. It means the guidance stays close to what can be observed, checked or implemented on the site.
For example, the Google AI Overview guide separates organic ranking overlap from page-readiness work. The ChatGPT explainer distinguishes source selection from a traditional ranking position. The llms.txt guide covers the file's limits as well as its use cases, so the reader does not treat it as a shortcut.
When behaviour changes between platform updates, the resources should be reviewed rather than stretched beyond the evidence. AI visibility is easier to manage when the work is documented and the claims remain modest.
"Create high-quality content" is not advice. It is not advice you can act on. The useful question is what to change on the page: the service definition, the FAQ, the schema, the internal links, the review proof or the technical access.
The local-business checklist, for example, turns Google Business Profile advice into fields, categories, review patterns and page connections a business can inspect. The Google AI Overview guide shows how a roofing page might answer roof type, process and cost-context questions in a way that is easier to quote.
The AEO vs SEO comparison lists what carries over from traditional SEO and what needs a different treatment. The aim is that a reader can leave each guide with one or two concrete checks, even if they later ask QBiz Leads to handle the implementation.
Figure 4
Two commitments the library holds itself to, and what each one rules out.
Not platform mythology
Practical checks from commercial queries, visible citations, documented crawler behaviour and page-level audits. Not every platform decision is knowable, so the guidance stays close to what can be observed, checked or implemented.
Not vague principles
"Create high-quality content" is not something you can act on. The useful question is what to change: the service definition, the FAQ, the schema, the internal links, the review proof or the technical access.
Most sites already have enough pages
The important details are scattered, unmarked or written for a broad brochure rather than a specific buyer question. The guides show where to look first: core service pages, schema, internal links, FAQs, review signals and crawl access.
FAQs
A free AI visibility check shows exactly what AI platforms can and cannot see about your business. It takes two minutes and carries no obligation.