How GeoPrompt Works
A proven framework to make your brand visible in AI search results
The GEO Optimization Cycle
Map intents, analyze logs, baseline prompts
Create pages, build authority, update llms.txt
Run prompts, measure KPIs, iterate
6-Step Framework
Define Recommendation Intents
What to do:
Identify the exact questions, prompts or queries your brand wants to appear in. Build a target list of intents with keywords, conversational phrasing, and variants.
Why it matters:
AI assistants respond to conversational queries. Aligning with user intents is the foundation of GEO strategy.
Action:
Maintain a database of intents → priorities → current status. Use prompt testing to validate each intent.
Publish Answer-First Pages
What to do:
Create web pages whose primary purpose is to answer target intents directly. Use clear headlines structured like questions, well-defined headings, bullet lists, FAQs, and structured data.
Why it matters:
AI engines synthesize answers from citable, structured content. Your pages must be machine-readable to get cited.
Action:
Add author metadata, timestamps, schema markup (FAQ, HowTo), and ensure fast, mobile-friendly performance.
Strengthen Authority Signals
What to do:
Use credible proof-points: case studies, expert quotes, author credentials, and third-party coverage. Ensure consistent brand descriptions across all sources.
Why it matters:
LLMs favor sources with strong authority and consistent signals. Trust is key to being recommended.
Action:
Create an About/Experts page with bios. Track external mentions and encourage authoritative guest posts.
Fill Answer Gaps & Comparisons
What to do:
Identify content gaps where competitors appear but you don't. Create comparison pages, buyer guides, and decision trees that map to your target intents.
Why it matters:
AI-driven search synthesizes from multiple sources. Missing key pieces means missing citations.
Action:
Use analytics to identify gaps. Create structured comparison content (X vs Y, When to choose A vs B).
Add llms.txt & Open Crawlers
What to do:
Publish /llms.txt listing your core pages for LLM indexing. Ensure robots.txt allows AI crawler bots (GPTBot, PerplexityBot, ClaudeBot).
Why it matters:
These files give AI systems clearer signals about your site structure and important pages, aiding crawling and citation.
Action:
Set up version control for llms.txt. Log AI bot requests and set alerts for blockages.
Measure, Iterate & Compete
What to do:
Track AI bot visits, run prompt tests across LLM providers, measure brand mentions and citation rates. Create KPIs for AI-driven traffic and competitor share of voice.
Why it matters:
GEO is continuous optimization. AI models evolve and discovery patterns change constantly.
Action:
Build dashboards for metrics. Set alerts for mention drops. Feed learnings back to content optimization.
How this helps your business
Increase Discoverability
Get recommended by AI assistants when users ask relevant questions. Reach customers at the moment they're looking for solutions.
Build Trust & Authority
Being cited by AI models signals credibility. Users trust brands that AI assistants recommend.
Drive Qualified Traffic
AI-driven visitors are highly targeted. They arrive with specific intent and context from their AI conversation.
Stay Ahead of Competition
Most brands aren't optimizing for AI search yet. Early adoption gives you a significant competitive advantage.
Ready to implement GEO?
Let Geoprompt guide you through the optimization process