Blog — BrandGEO

SEO Market Research Mar 24, 2026

How Google's AI Overviews Changed CTR Curves — What Published Data Tells Us

For twenty years, the SEO click-through-rate curve was stable enough to plan against. Position one got roughly 28% of clicks. Position two got 14%. Positions three through ten declined in a predictable pattern. Content and SEO teams built campaign models on top of that curve and, broadly, the curve held. Then Google launched AI Overviews, and the curve changed shape. The published research from Ahrefs, Similarweb, and several independent SEO teams lets us look at the new curve with reasonable confidence. The new curve is not a small deviation from the old one. It is a different curve.

#For SEO Managers #AI Overviews #CTR Decline

SEO Tutorials Mar 23, 2026

G2, Capterra, Trustpilot: Which Review Platform Actually Affects Your AI Visibility?

Most B2B SaaS brands try to maintain presence on G2, Capterra, Trustpilot, and a scatter of smaller review sites simultaneously. That is a mistake. For AI visibility purposes, one of those platforms almost always dominates the others in your category — and the effort spent thinly across all of them produces weaker results than the same effort concentrated on the right one. This post is the framework for picking the primary platform, setting up the review-acquisition flow, and deciding what to do about the others.

#For Founders #Citations #Reviews

AI Visibility Tutorials Mar 22, 2026

Five Lenses for Reading an AI Visibility Report Your PM Will Miss

When a product manager reads an AI visibility report, they read it through the lens they have — the product lens. How does this relate to activation? Retention? Feature adoption? Funnel conversion? Those are reasonable questions. They are also the wrong first questions. An AI visibility report rewards a different set of lenses, most of which are standard in marketing thinking and unfamiliar to product. This post walks through the five lenses a marketing practitioner uses to read the same report, with notes on why each matters and where a PM's default reading falls short.

#For SEO Managers #AI Visibility #Framework

Brand Strategy Strategy & ROI Mar 21, 2026

The 18-Month Category Window: Why AI Visibility Share Is Being Locked In Now

In most marketing channels, a late start is a fixable problem. In AI visibility, the evidence suggests otherwise. The brands that establish category authority inside the next 18 months — the period when training windows, retrieval corpora, and citation graphs are still forming around each vertical — will be disproportionately represented in the answers LLMs compose for years. This is not vendor narrative; it is a structural property of how these systems learn. This post explains why, and what a responsible first-mover strategy looks like.

#For CMOs #GEO #Framework

Industry Insights Mar 20, 2026

GEO for Healthtech: Visibility Under Regulatory Constraints

Healthtech marketing operates under constraints that most industries do not face. Efficacy claims require evidence. Competitor mentions are tightly regulated. Patient-facing content is reviewed through a compliance lens before it is published. None of that changes because users are now asking language models for healthcare recommendations. What does change is where the Generative Engine Optimization (GEO) leverage points sit. Healthtech brands that succeed at AI visibility tend to have specific patterns in common, none of which involve loosening compliance. This piece walks through what those patterns are, where the real opportunity sits, and what signals move AI visibility within the lines of regulated marketing.

#For CMOs #Healthtech #Playbook

AI Visibility Mar 19, 2026

"Free Graders Are Enough" — What They Show You, and the Bigger Thing They Hide

Free AI visibility graders multiplied quickly in 2025–2026 — HubSpot, Semrush, Mangools, Profound, Neil Patel, and a dozen more ship them. They share two properties: they are marketed as serious diagnostic tools, and they are built as lead magnets for larger marketing platforms. The two properties are in tension. A tool designed to capture email addresses has to return a number quickly; a tool designed to actually move that number has to surface diagnostic depth the lead-magnet format does not support. This post is about the difference — what the free graders honestly show you, what they structurally cannot, and how to tell when a grader is enough and when it is not.

#For Founders #AI Visibility #Myth-Busting

AI Visibility Tutorials Mar 18, 2026

The Six Dimensions of AI Brand Visibility: A Practitioner's Explainer

A single AI visibility score is a tempting shortcut. It is also a lossy one. "Your brand scores 63/100 on ChatGPT" does not tell you what to fix, or whether to fix anything at all. A useful audit breaks the score into dimensions — component questions, each with its own diagnostic and its own remedy. BrandGEO scores on six dimensions across a 150-point scale, normalized to 0–100. This post is a practitioner's explainer of each dimension: what it measures, why it matters, and what moves it.

#AI Visibility #Knowledge Depth #Recognition

Market Research Mar 17, 2026

The State of the GEO Category: Funding, Tooling, and Where It's Heading

In March 2024, the phrase Generative Engine Optimization was a whitepaper term used by a handful of researchers. By April 2026, it is a category name with a Wikipedia entry, dedicated tracks at BrightonSEO and SMX, more than twenty pure-play tools, over $500 million in disclosed venture capital, and at least one company valued at $1 billion. Eighteen months. Most MarTech categories take five to seven years to reach comparable maturity. This post maps the state of the category — what is funded, what is tooled, where it is heading — without naming specific competitors, because the naming is not the point. The shape is the point.

#For Founders #For CMOs #GEO

SEO Tutorials Mar 16, 2026

Digital PR for LLMs: How to Get Quoted in AI Answers (Not Just Google News)

Digital PR was originally optimized for two audiences: human journalists looking for stories, and Google's news indexing system looking for fresh authoritative content. In 2026 a third audience has become the dominant one — language models building their summaries of your category. The craft of PR has to shift accordingly. This post lays out how the discipline is changing, what still matters from the old playbook, and what specifically you should write differently when the goal is to be quoted in AI answers.

#For CMOs #Citations #Digital PR

AI Visibility Mar 15, 2026

The Confidence Score: What It Means, Why It Matters, When to Ignore It

Many AI visibility tools publish per-dimension confidence scores alongside the main 0–100 scores. The confidence number typically indicates how consistent or certain the model was when generating the answer. Used correctly, it is a genuinely useful signal — it helps separate stable findings from noisy ones. Used incorrectly, it is worse than useless. It can lead a team to trust a high-confidence-but-wrong answer and dismiss a low-confidence-but-correct one. This post unpacks what the confidence score actually measures, how to read it alongside the main score, and — importantly — when to ignore it.

#AI Visibility #LLM Monitoring #Framework

Strategy & ROI Mar 14, 2026

Translating AI Visibility Gains Into Revenue: The Attribution Problem and How to Approach It

AI visibility work produces outcomes the existing marketing attribution stack cannot see. ChatGPT does not send UTM parameters. Claude does not appear in GA4 as a referrer. Gemini's referrals often decay by the time the click reaches your analytics. This is the attribution problem that almost derails GEO programs in the CFO meeting — and it is solvable, in pragmatic ways, without pretending the problem does not exist. This post lays out the working attribution model B2B teams have been converging on, the survey instruments that ground it, and the three metrics that functionally replace what UTMs used to deliver.

#For CMOs #Framework #Data Analysis

Industry Insights Mar 13, 2026

GEO for Fintech: Earning LLM Trust in a Category Full of Scam Warnings

Fintech founders running their first AI visibility audit are often caught off-guard by a specific finding: the major language models describe their legitimate, regulated company with a level of skepticism they would not apply to a similarly-aged B2B SaaS in another category. That skepticism is not arbitrary. It is the product of how models are trained to handle financial topics — a category that is saturated with scam warnings, regulatory disclaimers, and fraud-adjacent content. Young fintech brands inherit that category-level caution by default. This piece unpacks why, what specifically the caution looks like in a fintech audit, and what legitimate fintech brands can do to push past the category-level skepticism into accurate, trust-weighted description.

#Sentiment & Authority #Fintech #Playbook