A mid-market SaaS company sees steady organic traffic in traditional search, but when buyers ask AI assistants for the best tools in its category, competitors are recommended and the company is missing or described with outdated positioning. Sales hears prospects say “ChatGPT suggested…” on discovery calls.
Goals
- Appear in AI answers for the category’s highest-intent buyer questions
- Correct outdated or inaccurate descriptions of the product in LLM responses
- Build a repeatable way to measure AI visibility against competitors
- 01
Benchmark
Run 150+ buyer-intent prompts across ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews to record mention rate, position, sentiment and cited sources versus top competitors.
- 02
Diagnose
Map which pages and third-party sources models rely on, identify entity inconsistencies across the web, and find the questions where no clear answer exists yet.
- 03
Restructure
Rewrite key pages answer-first, add comparison and use-case pages, deploy Organization, Product, FAQPage and HowTo schema, and publish an llms.txt file.
- 04
Amplify
Align descriptions across review sites, directories and profiles, and publish original, citation-worthy content that models can reference.
- AI visibility benchmark across five answer engines
- Answer-first rewrites of product, pricing and comparison pages
- Structured data across the site, validated and monitored
- Entity consistency program across third-party profiles
- Monthly share-of-voice report with prompt-level detail
Visible where buyers ask
The brand is mentioned and cited for priority category questions across the major AI assistants.
Accurate positioning
Models describe the product with current features, pricing model and ideal customer.
Measurable progress
Leadership sees AI share of voice versus competitors move month over month.