Guide
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AEO foundation playbook
Map the questions AI systems need to answer before buyers shortlist you.
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The Kojable Resource Library
Research, playbooks, and proof for improving how AI systems find and represent your brand.
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Research
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Reddit Myth in Fintech: A Research Note
A research note challenging the idea that Reddit is a universal AI visibility lever for fintech. The evidence points toward vertical media, analyst content, and review platforms as stronger sources for regulated financial topics.
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Case study
Stripe TVR case study
How Target Visibility Rate shows whether a brand appears when its ideal buyers ask AI systems high-intent questions.
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News
Competitive gap analysis update
Kojable now helps teams identify where competitors are winning in AI search, which queries they appear for, and where your brand is missing from the answer.
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Guide
Competitive gap audit guide
Find the prompts where competitors are cited before your brand.
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Research
AEO in SEO: Positional Bias Data
Data-backed analysis of how positional bias from search carries into AEO, influencing which brands are surfaced, cited, and recommended in AI-generated answers.
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Case study
Colosseum hackathon visibility study
How 80 real user questions revealed that brand visibility changes dramatically across Claude, Gemini, ChatGPT, and Perplexity.
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News
Source guidance controls update
Kojable now supports clearer source guidance, helping teams define which sources should shape AI visibility work — and which sources should be avoided.
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Research
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Citation Source Landscape: A Topic-First Map
Explore 250 high-coverage cited URLs across 13 technical topic neighborhoods and three executive citation systems.
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