Document Type: Taxonomy
Status: Intelligence Taxonomy
Version: v1.1
Authority: Ads Brain (governed by MWMS HeadOffice)
Applies To: Ads Brain classification system for advertising hook patterns and creative signal categories
Parent: Ads Brain Canon
Last Reviewed: 2026-03-15
Purpose
The Hook Pattern Taxonomy defines the structural classification system used to organise advertising hooks within the MWMS ecosystem.
Advertising hooks are the primary mechanism used to capture audience attention.
The taxonomy groups hooks according to their psychological structure so that creative testing can occur systematically.
This system allows Ads Brain to:
• classify hook types
• analyse hook performance patterns
• reuse proven hook structures
• accelerate creative experimentation
Hooks should not be treated as random ideas.
Hooks should be classified into repeatable structural patterns.
Scope
This taxonomy applies to:
• hook-type classification inside Ads Brain
• creative signal categorisation
• structural grouping of attention mechanisms
• reusable hook-pattern analysis
• standardised hook labelling for testing and storage
This document governs the classification logic used to organise hook patterns.
It does not govern:
• hook-testing procedures by itself
• experiment-launch authority
• campaign budget decisions
• statistical validation standards
• final creative approval
• capital allocation decisions
Those remain governed by Ads Brain systems, Experimentation Brain, Finance Brain, HeadOffice, and related protocols.
Definition / Rules
Difference From Hook Intelligence Database
Hook Pattern Taxonomy
Defines how hooks are classified.
Hook Intelligence Database
Stores individual hooks and their observed results.
Both systems work together to improve long-term creative learning.
Core Principle
Hooks must be analysed structurally.
Advertising experimentation must prioritise repeatable hook patterns rather than random creative ideation.
Primary Hook Categories
The taxonomy defines several core hook categories commonly used in high-performing advertising creatives.
Pattern Interrupt Hooks
Purpose:
Break the viewer’s expectation of what they normally see.
Examples include:
• unexpected visuals
• contrarian statements
• surprising opening lines
These hooks interrupt scrolling behaviour and capture immediate attention.
Curiosity Hooks
Purpose:
Create a knowledge gap that encourages viewers to continue watching.
Examples include:
• mystery statements
• incomplete explanations
• unexpected discoveries
These hooks rely on unresolved questions.
Problem Recognition Hooks
Purpose:
Identify a pain point experienced by the viewer.
Examples include:
• “Most people don’t realise this mistake…”
• “This common problem affects millions…”
These hooks activate audience relevance through immediate recognition.
Contrarian Hooks
Purpose:
Challenge widely accepted beliefs.
Examples include:
• “Everything you know about this is wrong”
• “This popular advice is misleading”
These hooks trigger cognitive friction and further attention.
Demonstration Hooks
Purpose:
Show immediate visual proof or action.
Examples include:
• product demonstrations
• before and after visuals
• live testing
These hooks leverage visual credibility.
Shock or Surprise Hooks
Purpose:
Capture attention through unexpected or emotionally striking information.
Examples include:
• surprising statistics
• dramatic statements
• unexpected outcomes
These hooks rely on emotional intensity.
Authority Hooks
Purpose:
Introduce expertise or credible sources.
Examples include:
• expert testimony
• scientific references
• industry authority figures
These hooks build immediate credibility.
Identity Hooks
Purpose:
Appeal to a specific group or self-image.
Examples include:
• “Entrepreneurs need to know this…”
• “If you’re over 40…”
These hooks activate group belonging and personal relevance.
Hook Classification Process
When a hook is tested, Ads Brain should classify it according to this taxonomy.
Each hook should include:
• Hook Text
• Hook Category
• Psychological Trigger
• Audience Context
• Platform Tested
• Performance Signals
Performance Signals
Performance signals may include:
• engagement rate
• viewer retention
• click-through rate
• conversion behaviour
These signals help Ads Brain compare which hook structures perform best across different contexts.
Relationship to Hook Testing Framework
The Hook Testing Framework governs how hooks are tested.
The Hook Pattern Taxonomy defines how hooks are classified.
Together these systems allow Ads Brain to identify which hook structures perform best.
Relationship to Hook Intelligence Database
The Hook Intelligence Database stores individual hooks.
Each stored hook should reference its taxonomy classification.
This allows pattern-level learning to build over time.
Future Expansion
The taxonomy may evolve as more advertising experiments are conducted.
Possible expansions include:
• sub-categories of hook types
• platform-specific hook behaviour
• audience-specific hook preferences
• AI-assisted hook classification
Final Rule
Hooks must be analysed structurally.
Advertising experimentation must prioritise repeatable hook patterns rather than random creative ideation.
Drift Protection
The system must prevent:
• hooks being treated as unstructured creative ideas
• inconsistent hook naming across Ads Brain documents
• hook records being stored without category reference
• confusion between hook classification and hook testing
• structural hook learning being lost inside general creative notes
Hook taxonomy must remain structured, consistent, and reusable.
Architectural Intent
Ads Brain – Hook Pattern Taxonomy exists to create a stable classification layer for advertising hook structures across the MWMS ecosystem.
Its role is to help Ads Brain understand which types of opening attention mechanisms work best, how they differ psychologically, and how they should be grouped for repeatable experimentation and long-term creative intelligence.
Change Log
Version: v1.1
Date: 2026-03-15
Author: MWMS HeadOffice / Ads Brain
Change: Rebuilt page to align with MWMS document standards. Added standardised document header, introduced Purpose / Scope / Definition / Rules structure, normalised hook-category and relationship sections, and preserved the original hook classification logic, classification process, and structural experimentation principle.
Version: v1.0
Date: 2026-03-13
Author: Ads Brain / MWMS HeadOffice
Change: Initial creation of Ads Brain – Hook Pattern Taxonomy defining the structural classification system for advertising hook patterns and creative signal categories.
END – ADS BRAIN – HOOK PATTERN TAXONOMY v1.1