The book
What ECHO covers
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 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.
A practical framework for visibility in the age of AI-generated answers is the line the cover carries under the title.
- 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
What is the book arguing?
There is no position one in an AI-generated answer. There is a binary question: is the brand in the answer or not. ECHO argues that four prerequisites decide it, that they have to be built in order, and that most failed AI visibility work starts in the middle.
The machine needs to know who you are (Entity). It needs to trust what it knows (Corroboration). It needs to find your content when answering a relevant question (Hooks). And you need to know whether any of this is working (Output). Miss any one of these and you have a gap that no amount of content, advertising, or traditional SEO can close.
The playbook that follows from that is ECHO: Entity, Corroboration, Hooks, Output.
Who is the book for?
ECHO: How brands get mentioned, recommended, and cited by AI is written for business owners, marketing directors, seo and search practitioners, in that order of assumed familiarity.
It assumes no prior knowledge of entity resolution or retrieval. Where a term is doing technical work, the book defines it, and all 33 definitions are published here.
How is the book structured?
11 chapters in 6 parts. Part 1 establishes what has changed, parts 2 to 5 build one ECHO pillar each, and part 6 turns the whole thing into a rollout plan with dates attached.
This book is arranged in the order the work has to happen, not in the order the ideas are most interesting.
- Part 1The Shift
- Part 2Entity the Entity pillar
- Part 3Corroboration the Corroboration pillar
- Part 4Hooks the Hooks pillar
- Part 5Output the Output pillar
- Part 6Applying It
How does the book handle evidence?
The book separates published research from its own framework explicitly, and says so on the page where it does it.
Where I am describing published research into how search and AI systems resolve entities, evaluate trust and retrieve content, I say so. Where I am presenting my own framework (ECHO itself, Entity Confidence, Share of Answer), I say that too. The distinction matters, because the research will outlast any particular platform's behaviour, and the platforms change without notice.
The three terms the book flags as its own coinage are ECHO, Entity Confidence, Share of Answer. The glossary marks each one.
What are the key facts?
The book runs to 76 pages and roughly 17,600 words of body text, with a 33 term glossary.
- Extent76 pages (Print proof PDF, 27 August 2026. 76 pages including front matter, glossary and about the author.)
- Body textabout 17,600 words
- Structure11 chapters, 6 parts
- Glossary33 terms
- Free extractchapter 3, 1,777 words
- Availability2026-08-28
Read chapter 3 in full
Becoming a Recognisable Entity (Not Just a Website) is published here free, all 1,777 words of it.