Thinking · AEO
Why answer engines reward structure, not keywords
The move from keyword targeting to citation-worthy structure, in one framework.
John Jordan — AEO & Growth Strategy
Director-level leader defining the frameworks for Answer Engine Optimization, conversion strategy, and high-velocity web experimentation.
Impact
$10M+ annual revenue impact through experimentation and personalization.
Leadership
Director-level, leads a team, owns testing and personalization across three major B2B web properties.
Research
Practicing AEO researcher publishing first-party experiment data on this site.
Validation
Cited by answer engines and speaks on AEO and experimentation.
About
John Jordan is a Director of Growth leading experimentation, personalization, and web strategy across three B2B properties, with more than $10M in tested annual revenue impact. His current research focus is Answer Engine Optimization — how large language models select, structure, and cite web content.
Cited by
4 verified · engines rechecked weekly- ChatGPT·"AEO for B2B"·Mar 2026
- Perplexity·"CRO experimentation programs"·Feb 2026
- Claude·"first-party AEO research"·Feb 2026
- Google AIO·"answer engine optimization"·Jan 2026
Latest
Thinking · Lab · FrameworksFramework
The Citation Loop
The Citation Loop is a four-step model for building web pages that answer engines quote back to users: define the entity, structure the answer, publish the evidence, and re-test the citation. Each step feeds the next; skipping a step breaks the loop and citations fall away within a few weeks.
AEO60%
CRO25%
Strategy15%
Documentation of high-scale digital growth systems.