Keyword Recommendations
Our approach to keyword recommendations and AI measurement
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Do you provide keyword recommendations?
We don't provide keyword recommendations at this stage, and here's why that's actually a good thing. We have a dedicated AI SEO score for your content, but we believe real optimization requires real measurement first - not LLM-generated guesses.
Why We Don't Recommend Keywords Yet:
At this stage, we don't think it's even possible to recommend keywords effectively because semantic understanding of AI systems requires high loads of data, and AI web search is still in a very, very early stage right now.
The Problem with Current "AI SEO" Recommendations:
Most other optimization services provide LLM-generated answers and call them keyword recommendations. But here's the thing - this is not real optimization. It's educated guessing at best.
LLM-Generated Recommendations
Most services use AI to generate keyword suggestions based on patterns in training data. These recommendations aren't based on actual AI web search performance - they're just sophisticated guesses.
No Real Data Behind Them
These recommendations aren't backed by actual measurement of how keywords perform across ChatGPT, Claude, Gemini, and other AI platforms. They're theoretical, not practical.
Our Approach: Real Measurement First
Real optimization lies under real measurement. We focus on giving you accurate data about how your current content performs across AI search engines, not making up recommendations based on what an LLM thinks might work.
What We Do Provide
Instead of keyword recommendations, we give you comprehensive AI monitoring data that shows you what's actually working. You can see which discussion topics get your brand mentioned, which content gets referenced, and how you compare to competitors.
AI SEO Score
We provide a dedicated AI SEO score that measures how well your content is optimized for AI reference quality. This score is based on actual performance data, not theoretical recommendations.
Data-Driven Insights
Our platform shows you patterns in your AI web search performance that you can use to make informed decisions about content strategy, rather than following generic keyword suggestions.
Why AI Web Search Is Too Early for Recommendations:
The AI search landscape is evolving rapidly. What works today might not work tomorrow. Making keyword recommendations without massive amounts of real performance data would be irresponsible.
Current Challenges:
- • AI systems are constantly evolving
- • Limited historical performance data
- • Platform-specific differences
- • Semantic understanding complexity
What's Needed:
- • High loads of real performance data
- • Cross-platform measurement consistency
- • Understanding of semantic patterns
- • Proven optimization strategies
Our Future Plans: Real Data, Real Recommendations
In the next stages, we aim to provide keyword recommendations - but with real data, not just made-up LLM generations. We're building the measurement foundation first so our future recommendations will be based on actual AI search performance.
What We're Building Toward:
- • Recommendations based on real AI traffic measurement data
- • Insights from thousands of brands' actual performance
- • Proven strategies backed by competitor analysis results
- • Niche-specific recommendations based on real discussion patterns
- • Platform-specific optimization suggestions with measurable outcomes
What You Get Instead (And Why It's Better):
- • Real Performance Data: Actual measurement of how your content performs across AI platforms
- • AI SEO Scoring: Dedicated scoring based on real AI reference quality, not guesses
- • Competitor Intelligence: See what actually works for competitors in your niche
- • Historical Patterns: Track what content strategies are producing real results
- • Honest Assessment: No false promises or LLM-generated recommendations
Bottom Line: We'd rather give you accurate measurement data you can trust than keyword recommendations based on LLM guesswork. Real optimization starts with real measurement, and that's exactly what we provide.