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 the Director of Conversion Rate Optimization at Twilio, where he leads experimentation, personalization, and web strategy across the company's B2B web portfolio. His testing programs have driven more than $10M in tested annual revenue impact. His current research focus is Answer Engine Optimization (AEO) — how large language models select, structure, and cite web content — studied through first-party experiments published on this site.
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.