Document Type: Framework
Status: Structural
Authority: HeadOffice
Applies To: Ads Brain, Affiliate Brain, Experimentation Brain
Parent: Ads Brain Canon
Version: v1.0
Last Reviewed: 2026-04-18
Purpose
This framework defines how MWMS uses Dynamic Search Ads (DSA) as a controlled discovery and expansion mechanism.
Dynamic Search Ads allow Google to match user queries to website content automatically rather than relying exclusively on predefined keywords.
DSA provides a structured method for:
discovering new search demand
identifying new keyword opportunities
identifying new landing page opportunities
expanding reach beyond predefined keyword sets
testing search coverage gaps
learning how Google interprets site structure
DSA must be used as a governed discovery tool rather than an uncontrolled automation channel.
Scope
This framework applies to:
Google Ads Dynamic Search Ads campaigns
search demand discovery environments
large product catalog environments
expansion-stage search campaigns
landing page coverage analysis
keyword gap identification
structured automation-assisted search expansion
This framework governs how DSA is deployed, constrained, and interpreted.
It does not govern:
core keyword campaign structure
creative testing logic
offer viability validation
capital allocation decisions
final scaling authority
Those remain governed by Ads Brain, Affiliate Brain, Experimentation Brain, Finance Brain, and HeadOffice.
Definition / Rules
Core Principle
Dynamic Search Ads are a discovery system.
They allow Google to:
crawl site content
interpret page relevance
match queries to pages
generate headlines dynamically
This enables identification of search behaviour patterns that may not have been anticipated through manual keyword research.
DSA expands coverage but reduces manual control.
Therefore governance constraints are required.
Role Inside MWMS
DSA functions as a controlled exploration layer.
Its primary roles include:
search term discovery
landing page relevance testing
site taxonomy validation
keyword expansion identification
automation signal interpretation
DSA is not intended to replace structured keyword campaigns.
It complements structured campaigns by identifying additional demand signals.
Appropriate Use Conditions
DSA is most useful when:
site structure is stable
site content is clearly organised
product taxonomy is consistent
landing pages are relevant to user intent
content accurately reflects offer structure
DSA performance depends heavily on site clarity.
Poorly structured sites produce unreliable matching behaviour.
Discovery Objectives
DSA may reveal:
new keyword clusters
unexpected user language patterns
new product demand signals
misalignment between search intent and site structure
content gaps
navigation clarity issues
DSA may also reveal:
unexpected traffic waste patterns
misinterpreted page relevance
low-quality query patterns
All signals must be interpreted through experiment discipline.
Control Variables Available
Although DSA automates keyword matching, several control mechanisms exist.
Operators may control:
targeting scope
page inclusion rules
page exclusion rules
negative keywords
bidding strategy
budget allocation
audience filters
landing page eligibility
Google controls:
headline generation
query matching behaviour
final URL selection logic
Control must be applied to reduce noise while preserving discovery value.
Targeting Structure Options
DSA targeting may be structured using:
entire website scope
selected categories
specific page groups
URL pattern rules
page feed inputs
Targeting scope should reflect experiment objectives.
Broad targeting produces more discovery but higher noise.
Narrow targeting produces cleaner signals but slower discovery.
Page Feed Strategy
Page feeds allow operators to specify which URLs should be included in discovery scope.
Page feeds may be used to:
prioritise high-value pages
exclude low-intent pages
group pages by theme
separate product categories
restrict automation exposure
Page feeds improve signal clarity by reducing irrelevant matching behaviour.
Negative Target Governance
Negative targets act as exclusion rules for pages or content groups.
Examples include:
blog content
support pages
policy pages
low-value pages
non-commercial pages
temporary pages
Negative targets prevent automation from generating low-intent traffic.
Negative targets improve discovery signal quality.
Search Term Evaluation Layer
DSA must be monitored through search query review.
Key evaluation questions include:
Which queries are appearing?
Which pages are matched?
Are those matches logical?
Are queries commercially relevant?
Are queries misinterpreting site content?
Which queries indicate expansion opportunity?
Which queries indicate waste?
Search query intelligence must integrate with:
Ads Brain Search Query Intelligence Framework.
Landing Page Performance Interpretation
DSA allows evaluation of:
which pages Google interprets as relevant
which pages attract search demand
which pages convert effectively
which pages fail to convert
DSA may reveal:
content structure weaknesses
misaligned messaging
insufficient page clarity
missing commercial context
Landing page mismatches may indicate:
content gaps
taxonomy confusion
navigation friction
Landing page performance should be interpreted as site intelligence, not only traffic intelligence.
Start Small Rule
DSA should initially operate under constrained exposure conditions.
Recommended starting conditions:
remarketing audiences
limited URL sets
restricted page feeds
low budget allocation
controlled experiment environment
Gradual expansion should occur only after signal reliability is confirmed.
Unrestricted DSA deployment may produce noisy or misleading signals.
Relationship to Other MWMS Standards
This framework operates alongside:
Ads Brain Search Query Intelligence Framework
Ads Brain Google Ads Experimentation Framework
Experimentation Brain Structured Testing Protocol
Affiliate Brain Ad Testing Framework
Governance Role
This framework ensures DSA remains:
interpretable
constrained
experiment-driven
signal-oriented
DSA must not become an uncontrolled traffic expansion mechanism.
It must remain a structured discovery tool.
Drift Protection
The system must prevent:
DSA being deployed as uncontrolled automation
site structure weaknesses producing distorted signals
irrelevant pages being used for matching
search term noise being mistaken for opportunity
DSA replacing structured keyword architecture
automation being mistaken for strategic direction
Discovery must remain structured and evidence-led.
Architectural Intent
Ads Brain Dynamic Search Ads Discovery Framework exists to allow MWMS to benefit from automated search discovery while maintaining governance discipline.
Its role is to provide controlled visibility into how Google interprets site content and user intent so new demand signals can be identified without exposing the system to uncontrolled traffic risk.
Change Log
Version: v1.0
Date: 2026-04-18
Author: HeadOffice
Change:
Initial creation of DSA framework defining controlled use of Dynamic Search Ads as a discovery-layer mechanism inside Ads Brain.
Framework defines:
discovery role of automation
page feed control logic
negative target governance
landing page intelligence use
signal interpretation discipline
Based on modern Google Ads automation behaviour and structured expansion logic.
Change Impact Declaration
Pages Created:
Ads Brain Dynamic Search Ads Discovery Framework
Pages Updated:
None
Pages Deprecated:
None
Registries Requiring Update:
MWMS Architecture Registry
Canon Version Update Required:
No
Change Log Entry Required:
No