99% of Founders Don't Track AI Mentions. The 1% Who Do Are Winning.

You can’t improve what you don’t measure.

Most companies investing in GEO have no idea whether it’s working. They’re optimizing blind, hoping mentions increase without any way to verify. If you’re just getting started, our complete guide to GEO covers the strategy before you set up measurement.

Building a measurement system is the difference between guessing and knowing.

Why Measurement Matters

Without measurement, you can’t:

• Know if your GEO efforts are working
• Compare performance against competitors
• Identify which strategies produce results
• Justify continued investment to stakeholders
• Catch problems before they compound

The Manual Testing Method

Start with manual testing. It’s free, requires no tools, and gives you ground truth.

Building a Tracking Spreadsheet

Create a spreadsheet with these columns:

Over time, this spreadsheet becomes your GEO performance dashboard.

Automated Monitoring Options

Manual testing doesn’t scale. For ongoing monitoring, consider:

API-Based Testing

Build scripts that query LLM APIs with your test queries and parse responses for brand mentions.

# Conceptual example
queries = ["best project management tool", "asana vs monday"]
for query in queries:
    response = openai_client.chat.completions.create(
        model="gpt-4",
        messages=[{"role": "user", "content": query}]
    )
    mentions = check_for_brand_mention(response)
    log_result(query, mentions)

This requires API costs and development time but enables daily or weekly automated tracking.

Third-Party Tools

Several tools are emerging for GEO monitoring:

• Otterly.ai - Tracks AI recommendations across multiple LLMs
• Profound - AI brand monitoring and competitive intelligence
• Brand Monitor tools - Some traditional brand monitoring tools are adding AI tracking

What to Track Beyond Mentions

Mentions are the primary metric, but track these secondary signals:

Description Accuracy

When you are mentioned, is the description accurate? Inaccurate descriptions can be worse than no mention. If descriptions are inaccurate, optimizing your landing page for LLM comprehension can help correct what AI says about you.

Track accuracy on a 1-5 scale:

• 5: Completely accurate
• 4: Mostly accurate, minor issues
• 3: Partially accurate
• 2: Mostly inaccurate
• 1: Completely wrong or harmful

Competitive Positioning

When you’re mentioned alongside competitors, how do you compare? Are you positioned favorably, neutrally, or unfavorably?

Query Coverage

What percentage of relevant queries result in your mention? Expanding coverage over time indicates improving GEO presence.

Trend Analysis

Month-over-month and quarter-over-quarter trends matter more than any single snapshot. Are you gaining ground or losing it?

Connecting to Source Metrics

AI mentions come from source material. Track the inputs too:

Reddit Metrics

• Monthly brand mention volume
• Sentiment of mentions (positive/negative/neutral)
• Karma on brand-related comments
• Thread visibility for category searches

Review Site Metrics

• Review volume and velocity
• Average rating
• Recency of reviews
• Featured review content

Content Metrics

• Ranking for relevant queries
• Backlinks to key pages
• Social shares of content

These inputs predict future AI mention changes. For the Reddit component specifically, the Reddit marketing playbook for B2B SaaS covers what to track and how to build presence in the subreddits that feed LLM training data.

Building Reports for Stakeholders

If you’re reporting GEO progress to leadership:

Monthly reports should include:

• Overall mention score vs. previous month
• Competitor mention comparison
• Top performing/underperforming queries
• Notable changes in AI descriptions

Quarterly reports should add:

• Trend analysis
• Source metric changes (Reddit, reviews)
• Strategic recommendations

Keep it simple. Executives want to know: Are we getting mentioned more? Are we gaining on competitors?