GEO Insights for Brand Marketers
How Google AI Mode Decides Which Brands to Recommend (and Why It Cites Your Competitor)
Google AI Mode gives only about three sources per answer, the fewest of any engine, and its top source is Amazon. Where AI Overviews rewards being everywhere, AI Mode rewards being the obvious answer, the same company playing almost the reverse game. Here is how it picks the few brands that make the cut.
How Google AI Overviews Decides Which Brands to Recommend (and Why It Cites Your Competitor)
Google AI Overviews casts the widest net of any engine, about ten sources per answer, and it leans hard on social. In the Cited Index its top source is Instagram, then YouTube, then Amazon. It rewards being present everywhere. Here is how it picks brands, and why breadth beats depth for it.
How Gemini Decides Which Brands to Recommend (and Why It Cites Your Competitor)
Gemini is the one AI engine that mostly reads your own website. In the Cited Index, 72% of its citations are brand sites and just 2% are community, the opposite of ChatGPT. If you have only optimized your own pages, Gemini is the engine you are already playing. Here is how it picks brands.
How Perplexity Decides Which Brands to Recommend (and Why It Cites Your Competitor)
Perplexity shows its work: every answer comes with its sources. In the Cited Index it reaches deepest into niche and long-tail sources, led by YouTube, then Reddit, then publishers you have probably never optimized for. Here is how it picks brands, and why your competitor keeps appearing in the citations.
How ChatGPT Decides Which Brands to Recommend (and Why It Cites Your Competitor)
When ChatGPT recommends a brand, it is repeating what its sources said, and its single largest source is Reddit. In the Cited Index, ChatGPT is the least likely of the five engines to just read your website. Here is how it builds a shortlist, and why your competitor keeps making it.
Why Every AI Visibility Tool Gives You a Different Share-of-Voice Number
Run your brand through two AI visibility tools and you will get two different Share-of-Voice numbers. Neither is wrong. Each tool quietly makes three decisions that move the number, and once you know what they are, you can finally read the metric instead of trusting it.
The Understandability Gap: Why Indian Brands Get Crawled But Not Cited
Across 186 Indian brand scans, Accessibility scores 79.3%. Understandability scores 49.7%. The 30-point gap is the reason your GEO scan looks fine and AI engines still pick someone else. Here's the data, the diagnosis, and the three page-template patterns that close it.
The Cited 8: 8 Metrics That Actually Measure AI Visibility (And How to Track Them)
A single AI Visibility Score hides more than it reveals. The Cited 8 framework maps 8 measurable dimensions across 3 layers, giving your team a complete diagnostic rather than a dashboard number.
The 3-Layer AI Visibility Stack: Why Fixing Your Website Doesn't Fix Your AI Visibility
18 brands with above-median GEO Scores still have below-median AI Visibility Scores. The gap is structural, not technical. Here's the framework that explains why.
What Narrative Is AI Building About My Brand? (And How to Find Out)
When ChatGPT ignores your brand in category recommendations, it reflects an AI narrative that's either weak, absent, or working against you. Here's how to diagnose it and what to do next.
If llms.txt Doesn't Drive Citations, Why Did Anthropic, Cloudflare, and Stripe Implement It?
Trakkr says zero correlation. Anthropic and Stripe implemented it anyway. Both sides are right. They're measuring different things.