From ranking in search to being named in the answer.
Peter Victor Jones created the ECHO Playbook to describe the work that happens after traditional rankings stop being the only discovery layer: make the entity clear, build corroboration, create retrievable hooks and measure the output.
AI assistants increasingly answer the question a customer asks before that customer visits a traditional results page. Peter’s position is that this creates a second game alongside SEO: a business must still be discoverable, but it also needs to be recognisable, trustworthy and citable enough to be named inside generated answers.
What is the ECHO Playbook?
ECHO stands for Entity, Corroboration, Hooks, Output. The canonical ECHO site describes the sequence as four prerequisites for AI recommendation visibility and explicitly treats the order as a dependency chain.
Does the machine know who you are?
Resolve the business as a distinct real-world entity, with consistent identity facts and a clear entity home.
Does it trust what it knows?
Build independent sources that repeat and verify the same facts rather than leaving the brand to self-assert everything.
Can it retrieve something useful?
Publish self-contained passages that answer the questions AI systems decompose from a user’s prompt.
Can you tell whether it is working?
Measure actual brand presence in generated answers instead of assuming ranking improvements automatically translate into AI recommendations.
Entity: make the brand resolvable
Peter’s ECHO material defines an entity as a structured machine-readable record rather than a marketing narrative. For local businesses, that means consistent name, service, location, ownership and relationship facts across the website and the external sources an answer engine can retrieve.
Entity work matters because AI systems cannot confidently recommend a business they cannot distinguish from similarly named people or organisations. Peter’s own use of his full name, Peter Victor Jones, is a deliberate disambiguation choice because “Peter Jones” collides with many other public people and records.
Corroboration: make third parties agree
A business saying “we are the best” is advertising. Independent sources repeating factual details about the business are corroboration. Reviews, directories, trade bodies, awards, press, partner pages and other trusted records become valuable when they confirm the same core facts.
The ECHO Playbook puts Corroboration immediately after Entity because there is nothing to verify until the machine knows what entity the evidence belongs to.
Hooks: make the answer extractable
AI systems retrieve passages, not marketing intentions. Peter’s Hooks pillar focuses on content that is specific enough to lift, attribute and reuse without losing meaning. That means answer-first sections, explicit facts, useful definitions and pages that map cleanly to real customer questions.
Output: measure Share of Answer
Peter Victor Jones defines Share of Answer as the percentage of target AI-generated responses in which a brand appears. The ECHO site is careful to call it a proposed framework metric rather than an industry standard.
That distinction matters. AI-generated results do not always behave like ranked lists, so presence can be more meaningful than “position”. The practical measurement loop is to define valuable prompt sets, record whether the brand appears, examine how it is described, then improve the upstream entity, corroboration and content signals.
How does AI visibility generate leads?
A mention is not a lead. It becomes useful when the recommendation creates branded search, a site visit, a call, a form submission or another commercial action. That is why Peter connects AI visibility back to the same lead-generation economics he has used in search since 2008.
AI Lead Generation FAQs
What is the ECHO Playbook?
The ECHO Playbook is Peter Victor Jones’s four-pillar framework for AI visibility: Entity, Corroboration, Hooks and Output.
What is Share of Answer?
Share of Answer is Peter Victor Jones’s proposed framework metric: the percentage of target AI-generated answers in which a brand appears. Peter’s ECHO site explicitly says it is not an industry standard.
What is Entity Confidence?
Peter Victor Jones uses Entity Confidence to describe the degree of certainty a search or AI system can assign to the identity of a brand as one disambiguated real-world entity based on consistent and corroborated facts.
Does AI visibility replace SEO?
No. AI visibility changes how businesses are selected and cited, but the underlying work still depends on a technically accessible website, clear entity facts, useful content and independent corroboration.
Which AI systems matter for local businesses?
The mix changes by market, but Peter’s published work discusses systems including ChatGPT, Gemini, Perplexity and Google AI Overviews.
Search visibility gets you found. Entity confidence helps you get named.
Build the evidence AI systems need before they can recommend the brand.