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 search query data as an intelligence and control surface inside paid search environments.
Its purpose is to convert search query reports from a routine cleanup activity into a structured decision system for:
query governance
negative keyword discipline
new keyword discovery
match quality review
brand leakage prevention
campaign structure refinement
Search query data is one of the most important live feedback systems inside Google Ads because it reveals what users actually searched, how Google matched that query, and where waste or opportunity exists.
Scope
This framework applies to:
Google Ads search campaigns
brand campaigns
non-brand campaigns
broad match campaigns
phrase match campaigns
exact match campaigns
audience-filtered search campaigns
search expansion experiments
This framework governs how search query data is reviewed, interpreted, classified, and acted on.
It does not govern:
bidding strategy by itself
landing page design by itself
auction competition review by itself
full keyword research by itself
canonical account structure by itself
Those remain governed by the relevant Ads Brain and Research Brain pages.
Definition / Rules
Core Principle
Keywords are what the operator tells Google.
Search queries are what users actually type.
Those are not the same thing.
Therefore search query review is required to understand:
how Google interprets relevance
where money is being wasted
where hidden demand exists
where account structure is helping or hurting performance
Search Query Intelligence Role
Search query review must be treated as an ongoing intelligence loop, not a one-time optimization task.
The role of the search query report is to reveal:
actual user language
Google matching behaviour
irrelevant traffic
high-potential expansion terms
routing mistakes
negative keyword opportunities
brand and non-brand contamination
Primary Questions
When reviewing search query data, Ads Brain must ask:
What did the user actually search?
Where did Google match this query?
Was that match structurally correct?
Did the query produce useful performance?
Should this query be excluded?
Should this query be promoted into the account?
Should this query live in a different campaign or ad group?
These questions must be answered before action is taken.
Query Classification Model
Each meaningful query should be classified as one of the following:
Relevant and Correctly Routed
The query is useful and already matched to the correct campaign or ad group.
Relevant but Misrouted
The query is useful but Google matched it to the wrong campaign or ad group.
Irrelevant Waste
The query should not trigger ads and requires negative keyword action.
New Expansion Opportunity
The query reveals new demand or wording that should be added intentionally.
Brand Leakage
A brand query is being captured by a non-brand campaign or non-brand structure.
Ambiguous Monitor State
The query is not yet clearly useful or harmful and should be observed further before structural change.
Negative Keyword Rule
Negative keywords must be used to stop one of two things:
irrelevant queries
relevant queries matching in the wrong place
If a query should never show anywhere, add a broader negative at the highest sensible level.
If a query is useful but should not show in its current location, add a negative at the campaign or ad group level that blocks the current routing while allowing the intended routing elsewhere.
Negative Keyword Hierarchy
Negative keyword decisions should be made at the correct control level:
Account Level
Use when the query or word should never trigger any campaign.
Campaign Level
Use when the query is wrong for the campaign theme but may still belong elsewhere.
Ad Group Level
Use when the query is wrong for the ad group but belongs within the wider campaign.
The highest correct control level should be preferred to reduce repeated maintenance.
Brand Leakage Rule
Brand traffic must not be allowed to inflate non-brand performance visibility.
If brand queries are being captured by non-brand campaigns, those terms must be identified and controlled using negative keyword governance or structural routing changes.
New Keyword Promotion Rule
Not every good query should be directly added to the exact place where it first appeared.
Before adding a query as a keyword, the operator must assess:
Does it belong in the current ad group?
Does it deserve its own ad group?
Does it need different ad copy?
Does it need a different landing page?
Does it belong in a different campaign entirely?
Search query discovery must improve structure, not create clutter.
Account Structure Feedback Rule
Search query data is a live test of account structure.
Repeated misrouting may indicate:
campaign themes are too broad
ad groups are too loose
match-type handling is weak
negative keyword discipline is insufficient
brand separation is incomplete
When repeated patterns appear, structural fixes should be preferred over endless patching.
Broad Match Governance
Broad match can be useful for discovery, but it must be governed through:
search query review
negative keyword refinement
audience filtering where appropriate
controlled experimentation
Broad match without search query intelligence becomes waste expansion.
Search Query Review Cadence
At minimum, search query reports should be reviewed weekly.
Higher-spend or higher-risk campaigns may require more frequent review.
The review cadence must reflect:
traffic volume
spend velocity
match-type looseness
experiment activity
brand-defense sensitivity
Performance Interpretation Rule
Search query review must not rely only on one metric.
Useful evaluation signals include:
cost
clicks
conversions
conversion rate
cost per conversion
return on ad spend
match location
campaign context
A query may look good in isolation but still be harmful if it is inflating the wrong part of the account.
Governance Role
This framework gives Ads Brain a repeatable system for turning raw query data into structural learning and spend control.
It also supports Affiliate Brain and Experimentation Brain by improving the reliability of traffic inputs and reducing waste caused by uncontrolled matching.
Relationship to Other MWMS Standards
This framework operates alongside:
Ads Brain Google Ads Experimentation Framework
Ads Brain Campaign Review Protocol
Ads Brain Campaign Structure Signal Integrity Framework
Affiliate Brain Ad Testing Framework
Experimentation Brain Structured Testing Protocol
Drift Protection
The system must prevent:
search query reports being ignored after launch
negative keyword work being treated as optional cleanup
relevant queries being added blindly without structural fit review
brand traffic contaminating non-brand learning
broad match expansion without governance
repeated misrouting being patched endlessly instead of structurally corrected
Search query intelligence must remain active, structured, and decision-oriented.
Architectural Intent
Ads Brain Search Query Intelligence Framework exists to make live user-language data usable as a governed optimization system inside MWMS.
Its role is to show what users actually search, how Google actually matches, where budget is being wasted, and where controlled expansion opportunities exist so paid search can improve through evidence rather than assumption.
Change Log
Version: v1.0
Date: 2026-04-18
Author: HeadOffice
Change: Initial creation based on Google Ads search query report discipline, negative keyword governance, keyword promotion logic, and modern match-quality interpretation.
Change Impact Declaration
Pages Created:
Ads Brain Search Query Intelligence Framework
Pages Updated:
None
Pages Deprecated:
None
Registries Requiring Update:
MWMS Architecture Registry
Canon Version Update Required:
No
Change Log Entry Required:
No