Case Studies
Methodology walkthroughs that show exactly how we work: the approach, the measurement, and what a program works toward for SaaS, consumer apps, and B2B brands.
AI Visibility for a Productivity SaaS
Goal: cited for category prompts
LLM Visibility for a Health & Wellness App
Goal: AI mentions + efficient CAC
AI Authority Building for B2B Cybersecurity
Goal: cited expertise + inbound lift
Technical GEO Setup for a SaaS Platform
Goal: AI-crawlable, answer-ready site
Reddit Marketing for a B2B SaaS
Goal: durable threads AI retrieves
AI Visibility Audit for a SaaS Brand
Goal: defensible baseline + playbook
AI Visibility Consulting for an In-House Team
Goal: a team that runs the loop
What a Program Works Toward
Each walkthrough shows our real methodology and how we measure - transparency about method over dressed-up numbers. We publish client results only with written permission and supporting data. The directional signals every program is managed against:
Citation share of voice
How often you are mentioned in AI answers to a fixed panel of category prompts, versus competitors - sampled repeatedly with variance notes.
Branded search interest
Branded query impressions in Search Console - the most reliable downstream proxy for being seen in AI answers.
Qualified inbound signals
Assistant referral sessions where visible, plus "how did you hear about us" responses naming AI tools.
Ready to Understand Your AI Visibility?
Start with an AI Visibility Risk Audit to see how AI systems currently represent your brand.