Practitioner stories from the AI marketing transition.
Every subject Marketing Signal Journal covers. Each topic page lists all of its articles.
AI visibility describes how often, and how accurately, a brand appears in answers produced by AI assistants and AI search engines.
Generative Engine Optimization (GEO) is the practice of structuring content, evidence and entities so AI answer engines can find, trust and cite a brand.
Schema markup, entity consistency and technical SEO practices that make a brand legible to AI crawlers.
AI brand monitoring tracks how ChatGPT, Gemini, Perplexity, Claude and other assistants mention, describe and recommend a brand over time.
Reviews and reputation signals (G2, Trustpilot, Yelp, Capterra and similar) feed the evidence AI systems use when they compare and recommend brands.
Share of Model is the percentage of AI-generated answers that cite or recommend a brand across a tracked set of prompts.
How CMOs and enterprise marketing teams budget for, staff and govern AI visibility programs.
Marketing measurement covers how teams attribute pipeline, awareness and revenue to AI-era visibility and prove the change was caused by their work.
Creative intelligence evaluates ads and marketing assets before launch and links creative choices to AI discoverability and media-planning decisions.
Brand intelligence turns monitoring data into decisions: where a brand is misrepresented, omitted or outranked in AI answers, and what to fix first.
Citation analysis examines which sources AI systems cite when they answer buyer questions, and what separates cited sources from ignored ones.
Competitive intelligence compares how rival brands are recommended, cited and described by AI systems against your own.
Marketing Signal Journal