AI Search Optimization Tool for LLMs | Goodie

Optimization Actions for AI Search Growth

Identify which pages your site needs to update, which outreach targets matter, and which technical fixes will improve your citations—then execute improvements directly in the platform.

Turn Visibility Gap Insights Into Optimizations

01

Target specific content and technical gaps

See exactly which pages lack the authority signals AI requires, which schema markup is missing, which competitor sources you need to match, and which entities need stronger definitional content.

02

Prioritize by measurable impact potential

Each recommendation shows estimated visibility lift based on competitive gap size, current mention frequency, and prompt volume. Focus on optimizations projected to improve citation rates by 15-40% so you actually move the needle.

03

Execute in one comprehensive workflow

Update meta descriptions and structured data for owned content. Identify specific publications and journalists for earned coverage. Optimize social profiles with entity clarity and credential signals.

How Goodie Identifies & Prioritizes AI Optimizations

01

Map your content against what AI actually cites

The platform compares your owned assets to the sources AI references when citing competitors, identifying missing topic coverage, weak authority signals, unclear entity definitions, and technical gaps.

02

Generate specific, actionable recommendations

You receive targeted improvements with difficulty level, estimated timeline, and projected impact on citation rate.

03

Execute, track, and measure results

Implement changes directly for owned content, track outreach status for earned opportunities, and monitor how visibility metrics change following implementation.

Tracking all major AI models:

FAQ

What types of optimizations does the platform recommend?

Owned content: Add missing topic coverage, strengthen author credentials, implement schema markup (Article, FAQPage, Organization, Product), improve entity clarity, add citation sources.

How does impact estimation work?

The platform calculates potential visibility lift by analyzing competitive gap size (how often competitors get cited for prompts you miss), current baseline mention rate, prompt volume for the topic, and difficulty of the fix. A recommendation to add FAQ schema on a high-volume topic where three competitors have it shows higher estimated impact than minor wording changes.

How do enterprise teams coordinate AEO workflows across distributed teams?

Optimization Actions gives distributed teams a shared, prioritized playbook rather than a fragmented list of to-dos. Each recommendation includes difficulty level, estimated timeline, and projected impact on citation rate, all so that Content, SEO, PR, and Technical teams all know what to tackle first and why. Owned content updates, earned media outreach, technical fixes, and social optimizations are organized by type and effort level, making it straightforward to assign work across functions and track progress as visibility metrics shift.

Can I filter recommendations by type or effort level?

Yes. Filter by action type (content, technical, earned, social), difficulty (quick wins vs. major projects), estimated impact (high/medium/low), or affected prompt clusters.

Learn More About Optimizing for AI Engines

AI as the New Homepage: How Brands Must Rethink Marketing Distribution

Goodie vs. Semrush: Built for AI Search Or Adapting to It?

Travel AI Optimization: How to Get Cited in AI Searches

Complete Your AEO Workflow

Gain Your Edge in AI Discoverability