Thinking · AEO
Why answer engines reward structure, not keywords
The move from keyword targeting to citation-worthy structure, in one framework.
John Jordan
I run the CRO program at Twilio. Nights and weekends, I study how answer engines select and cite web content — and publish the experiments here, including the ones that flop.
Role
Director of Conversion Rate Optimization at Twilio. Experimentation, personalization, and web strategy across the B2B portfolio.
Impact
More than $10M in tested annual revenue impact from experimentation and personalization programs.
Research
Runs first-party AEO experiments on this domain and publishes the results — including the null ones.
Published
Optimization work published as case studies by MECLABS Institute and MarketingSherpa.
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.
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%
Field notes from someone who tests things for a living.