Field notes Research, essays, and reports from the practice

The Blog.

Original research on how AI engines pick which brands to surface — and the methodology we use to engineer that outcome for our clients.

How to Report AI Visibility to Executives and Stakeholders

One of the most common failure points in AI visibility work has almost nothing to do with the quality of your measurement.…

How to Measure AI Search Visibility: Metrics, Methods & Tools

Citation Rate measures how often an AI platform visibly attributes an answer to your website or content, across a defined set of…

Best AI Visibility Tracking Tools Compared (2026 Buyer’s Guide)

An AI visibility tracking tool runs a library of prompts against AI answer engines ChatGPT, Google AI Overviews and AI Mode, Perplexity,…

The Four Metrics That Define AI Visibility

Many teams look for a single AI visibility score that summarizes how well their brand performs across ChatGPT, Gemini, Microsoft Copilot, Perplexity,…

Why One AI Visibility Check Misleads You

A single AI visibility check one prompt, run once, on one platform only captures a snapshot of a system that’s constantly changing.…

Share of Voice in AI Answers: How to Calculate and Benchmark It

AI Share of Voice (AI SOV) measures how often your brand shows up in AI-generated answers compared to your competitors, across a…

AI Answer Sentiment: How AI Assistants Frame Your Brand

Ask ChatGPT and Gemini the same question about your brand and you can get two different answers not because one is wrong,…

Page-Intent Segmentation: Tag Pages for Better GA4 Reports

Page-intent segmentation is the practice of tagging every page on a site by the search intent it serves, informational, commercial, transactional, or…

Wikipedia and Wikidata: Unlock AI Citation Success

AI search systems are moving beyond simple keyword matching and focusing more on understanding entities, relationships, and context. To provide accurate answers,…