Viclaro field notes
How AI assistants decide who to recommend.
Research from Viclaro Atlas on AI recommendations, prompt shape, and the website fixes that make service firms easier for ChatGPT, Claude, Gemini, and Perplexity to cite.
How to Read AI Search Rankings (Beyond Vanity Metrics)
AI search rankings measure how often assistants like ChatGPT, Claude, Gemini, and Perplexity name a business when a buyer asks who to hire. Read for share of voice, model coverage, and the gap between positions — not the rank number alone.
The State of AI SEO Tools in 2026: What Actually Works
AI SEO tools measure how brands show up inside AI assistants like ChatGPT, Claude, Gemini, and Perplexity. In 2026 the mature ones can reliably measure per-model citation rate, share of answer, and category shape. They still cannot measure assistant usage share, conversion attribution, or click-through when no URL is returned. This guide walks through what the category can honestly do, what it cannot, and how to evaluate a tool.
How to Optimize Your Site for AI Search: A Step-by-Step Playbook
Optimizing for AI search means increasing how often AI assistants like ChatGPT, Claude, Gemini, and Perplexity name your brand in their answers. The workflow is a loop: measure your baseline citation rate on a defined prompt panel, diagnose which buyer prompts you lose and on which models, ship targeted content changes with structured data, and re-measure to prove the delta. This piece walks through each step with the numbers, sample sizes, and pitfalls that separate a real result from a lucky snapshot.
AI Share of Voice: The Metric That Replaces Market Share in AI Search
AI share of voice is the portion of AI-generated recommendations in a category that name your brand. It is measured across a fixed prompt library, a fixed panel of assistants, and a fixed sampling protocol. It is not market share — a firm can be a category leader by revenue and hold near-zero AI share of voice, or vice versa. A good number depends entirely on the shape of the category: a monopoly might hit 60%, a competitive leader 20%, a fragmented market 8%. This piece defines the metric, walks through how to calculate it, and shows what different share levels actually mean.
How to Measure AI Visibility (Without Fooling Yourself with One Screenshot)
To measure AI visibility, you need a panel — multiple assistants, multiple samples per prompt, per-model breakdowns preserved. Not a screenshot. Not a single-model score. The four major assistants disagree with each other by 5x or more on the same firm in the same category, so any measurement built on one model at one moment is roughly that far off from the actual market. This piece walks through the sample size, model coverage, and reporting design that make AI visibility measurement defensible.
Why Schema and llms.txt Will Not Fix Vague Positioning
Technical signals can make evidence easier to discover and parse. They cannot manufacture the evidence an assistant needs to recommend your firm.
How to Read AI Search Rankings (Beyond Vanity Metrics)
AI search rankings measure how often assistants like ChatGPT, Claude, Gemini, and Perplexity name a business when a buyer asks who to hire. Read for share of voice, model coverage, and the gap between positions — not the rank number alone.
The State of AI SEO Tools in 2026: What Actually Works
AI SEO tools measure how brands show up inside AI assistants like ChatGPT, Claude, Gemini, and Perplexity. In 2026 the mature ones can reliably measure per-model citation rate, share of answer, and category shape. They still cannot measure assistant usage share, conversion attribution, or click-through when no URL is returned. This guide walks through what the category can honestly do, what it cannot, and how to evaluate a tool.
How to Optimize Your Site for AI Search: A Step-by-Step Playbook
Optimizing for AI search means increasing how often AI assistants like ChatGPT, Claude, Gemini, and Perplexity name your brand in their answers. The workflow is a loop: measure your baseline citation rate on a defined prompt panel, diagnose which buyer prompts you lose and on which models, ship targeted content changes with structured data, and re-measure to prove the delta. This piece walks through each step with the numbers, sample sizes, and pitfalls that separate a real result from a lucky snapshot.
AI Share of Voice: The Metric That Replaces Market Share in AI Search
AI share of voice is the portion of AI-generated recommendations in a category that name your brand. It is measured across a fixed prompt library, a fixed panel of assistants, and a fixed sampling protocol. It is not market share — a firm can be a category leader by revenue and hold near-zero AI share of voice, or vice versa. A good number depends entirely on the shape of the category: a monopoly might hit 60%, a competitive leader 20%, a fragmented market 8%. This piece defines the metric, walks through how to calculate it, and shows what different share levels actually mean.
How to Measure AI Visibility (Without Fooling Yourself with One Screenshot)
To measure AI visibility, you need a panel — multiple assistants, multiple samples per prompt, per-model breakdowns preserved. Not a screenshot. Not a single-model score. The four major assistants disagree with each other by 5x or more on the same firm in the same category, so any measurement built on one model at one moment is roughly that far off from the actual market. This piece walks through the sample size, model coverage, and reporting design that make AI visibility measurement defensible.
Why Schema and llms.txt Will Not Fix Vague Positioning
Technical signals can make evidence easier to discover and parse. They cannot manufacture the evidence an assistant needs to recommend your firm.
AI SEO for Personal Injury Lawyers: Why the Market Is Still Open
AI SEO for personal injury lawyers looks different from AI SEO in other legal verticals because the market is still fragmented. In our NYC audit, the top PI firm holds only 8.0% share of AI recommendations, only two of four major assistants cite it, and the entire corpus is 15x smaller than NYC divorce. That combination — no dominant firm, partial model coverage, thin overall citations — describes an unusually cheap window for a mid-market or boutique firm to break into the top five before consolidation closes it.
How ChatGPT (and Other AI Assistants) Choose Which Businesses to Recommend
ChatGPT and other AI assistants pick businesses by combining training data, live web retrieval, and their own citation preferences. The result is not one answer but a probability distribution across a handful of firms, and it varies by assistant. Here is how the mechanism works, how to check where your business sits, and why the answer differs across models.
GEO vs SEO: What Changes When Buyers Ask AI Instead of Google
Generative engine optimization (GEO) is the practice of getting a business named by AI assistants like ChatGPT, Claude, Gemini, and Perplexity. It shares foundations with SEO — authority, structure, evidence — but the retrieval unit is a citation in a generated answer, not a link on a SERP. Here is what actually changes.
How to Write Content That AI Assistants Actually Cite
Content that AI assistants cite looks different from content designed for humans or Google. It answers the buyer's exact question in a single quotable sentence, in the buyer's vocabulary, marked up with FAQPage schema, and reachable without a login. Get those four things right and ChatGPT, Claude, Gemini, and Perplexity can lift your page verbatim into a recommendation. Miss them and even a well-written site stays invisible.
How ChatGPT Recommends Divorce Lawyers: What We Learned Auditing NYC
ChatGPT recommends divorce lawyers by retrieving named firms from a shortlist that its training data and retrieval layer have built up over months of web crawling — not from lawyer directories, and not from Google search rankings. In NYC divorce, three firms hold 53.5% of every AI recommendation. This piece walks through how AI actually decides which lawyer to name, using data from 7,485 citations across four assistants, and what a firm outside the top ten can do about it.
Why Your Law Firm Can Rank in Google and Still Be Invisible to ChatGPT
Google rankings reward pages built for keywords. AI recommendations reward pages that answer a buyer situation clearly enough to be reused in an answer.
AI SEO for Personal Injury Lawyers: Why the Market Is Still Open
AI SEO for personal injury lawyers looks different from AI SEO in other legal verticals because the market is still fragmented. In our NYC audit, the top PI firm holds only 8.0% share of AI recommendations, only two of four major assistants cite it, and the entire corpus is 15x smaller than NYC divorce. That combination — no dominant firm, partial model coverage, thin overall citations — describes an unusually cheap window for a mid-market or boutique firm to break into the top five before consolidation closes it.
How ChatGPT (and Other AI Assistants) Choose Which Businesses to Recommend
ChatGPT and other AI assistants pick businesses by combining training data, live web retrieval, and their own citation preferences. The result is not one answer but a probability distribution across a handful of firms, and it varies by assistant. Here is how the mechanism works, how to check where your business sits, and why the answer differs across models.
GEO vs SEO: What Changes When Buyers Ask AI Instead of Google
Generative engine optimization (GEO) is the practice of getting a business named by AI assistants like ChatGPT, Claude, Gemini, and Perplexity. It shares foundations with SEO — authority, structure, evidence — but the retrieval unit is a citation in a generated answer, not a link on a SERP. Here is what actually changes.
How to Write Content That AI Assistants Actually Cite
Content that AI assistants cite looks different from content designed for humans or Google. It answers the buyer's exact question in a single quotable sentence, in the buyer's vocabulary, marked up with FAQPage schema, and reachable without a login. Get those four things right and ChatGPT, Claude, Gemini, and Perplexity can lift your page verbatim into a recommendation. Miss them and even a well-written site stays invisible.
How ChatGPT Recommends Divorce Lawyers: What We Learned Auditing NYC
ChatGPT recommends divorce lawyers by retrieving named firms from a shortlist that its training data and retrieval layer have built up over months of web crawling — not from lawyer directories, and not from Google search rankings. In NYC divorce, three firms hold 53.5% of every AI recommendation. This piece walks through how AI actually decides which lawyer to name, using data from 7,485 citations across four assistants, and what a firm outside the top ten can do about it.
Why Your Law Firm Can Rank in Google and Still Be Invisible to ChatGPT
Google rankings reward pages built for keywords. AI recommendations reward pages that answer a buyer situation clearly enough to be reused in an answer.