Entity, Corroboration, Hooks, Output
ECHO: How brands get mentioned, recommended, and cited by AI
ECHO: How brands get mentioned, recommended, and cited by AI is a practical playbook by Peter Victor Jones for winning brand visibility in AI-generated answers, built on four pillars: Entity, Corroboration, Hooks and Output.
What is the ECHO Playbook?
ECHO is a four-pillar framework for making AI answer engines recommend a brand. The pillars are Entity, Corroboration, Hooks and Output, and they are the four prerequisites every answer engine imposes before it will name a brand in an answer.
Set out by Peter Victor Jones in ECHO: How brands get mentioned, recommended, and cited by AI, and defined in full on the playbook page.
Why the order of the pillars matters
The pillar sequence is not a matter of preference. Corroboration has nothing to confirm until an entity exists to be confirmed. Hooks are content a machine will not retrieve if it does not yet trust the source. Measurement tells you very little when the thing being measured has not been built.
Each pillar also names a failure mode, which turns the playbook into a diagnostic once the work is underway.
- EntityIf the machine does not know you exist, the problem is Entity.
- CorroborationIf it knows you exist but will not repeat what it knows, the problem is Corroboration.
- HooksIf it trusts you but never surfaces your content for the question being asked, the problem is Hooks.
- OutputIf you cannot tell which of these is happening, the problem is Output, and that is where to start.
Read the playbook in full, including the 30/60/90 day rollout plan.
What is ECHO: How brands get mentioned, recommended, and cited by AI?
ECHO: How brands get mentioned, recommended, and cited by AI is a practical playbook by Peter Victor Jones for winning brand visibility in AI-generated answers, built on four pillars: Entity, Corroboration, Hooks and Output. The four pillars are the prerequisites every answer engine imposes before it will name a brand: it has to know who you are, trust what it knows, and find your content when the question is asked, and you have to be able to tell whether any of it is working. The book sets the work out in the order it has to happen.
- Title
- ECHO: How brands get mentioned, recommended, and cited by AI
- Author
- Peter Victor Jones
- Playbook
- ECHO: Entity, Corroboration, Hooks, Output
- Edition
- First edition
- Published
- 2026-08-28
- Publisher
- to supply
- ISBN-13
- not applicable
- ASIN
- B0HGYGSZF9
- Pages
- 76
- Chapters
- 11 across 6 parts
- Language
- en-GB
- Copyright
- 2026 Peter Victor Jones
Who wrote ECHO: How brands get mentioned, recommended, and cited by AI?
Peter Victor Jones wrote ECHO: How brands get mentioned, recommended, and cited by AI. Peter Victor Jones has worked in search since 2008, building organic and paid lead generation systems for businesses whose growth depends on being found.
He is the originator of the ECHO Playbook and of the ECHO, Entity Confidence, Share of Answer terms defined in it.
Chapter 3 is published here in full
Becoming a Recognisable Entity (Not Just a Website) is the chapter that defines what an entity means to a machine. It is free to read, and it is the argument the rest of the playbook rests on.