Document Type: Framework
Status: Active
Authority: HeadOffice
Applies To: Experimentation Brain, Ads Brain, Conversion Brain, Affiliate Brain, Content Brain, Data Brain, AIBS Brain
Parent: Experimentation Brain Canon
Version: v1.0
Last Reviewed: 2026-05-03
Purpose
The Creative Variation Backlog Framework defines how MWMS captures, structures, prioritises, and manages all testing ideas, campaigns, experiences, and variations.
Testing without a backlog leads to:
- random testing
- repeated ideas
- lost learnings
- poor prioritisation
- inconsistent execution
This framework ensures all testing is:
- organised
- traceable
- prioritised
- actionable
Scope
This framework applies to:
- A/B testing campaigns
- personalization experiments
- ad creative testing
- funnel testing
- landing page experiments
- ecommerce testing
- affiliate offer testing
It governs:
- idea capture
- variation tracking
- campaign structure
- testing workflow
- prioritisation
Definition
Creative Variation Backlog
A structured system that stores:
- all test ideas
- all campaigns
- all experiences
- all variations
- all hypotheses
- all results
Core Principle
If a test is not captured in the backlog, it does not exist.
Backlog Structure
1. Campaign Level
Represents the objective of testing
Fields
- Campaign Name
- Objective
- Optimization Target
- Funnel Stage
- Owner
- Status
2. Experience Level
Represents different approaches to solving the objective
Fields
- Experience Name
- Description
- Segment (if applicable)
- Personalization Method (A/B / Rules / Predictive)
3. Variation Level
Represents specific changes being tested
Fields
- Variation Name
- Hypothesis
- Change Description
- Creative Asset
- CTA / Message Change
- Page/Location
Hypothesis Requirement
Every variation must include:
- what is being changed
- why it should improve performance
- expected outcome
Rule
No hypothesis:
→ no test
Backlog Workflow
Step 1 — Idea Capture
Capture ideas from:
- data insights
- previous tests
- customer behaviour
- competitor analysis
- team input
Step 2 — Structuring
Convert idea into:
- campaign
- experience
- variation
- hypothesis
Step 3 — Prioritisation
Rank based on:
- impact potential
- ease of implementation
- traffic availability
- strategic importance
Step 4 — Execution
- build variation
- launch test
- assign traffic
Step 5 — Measurement
- track results
- validate performance
Step 6 — Learning
Record:
- results
- insights
- conclusions
Step 7 — Iteration
- refine idea
- expand winners
- create new variations
Status System
Each campaign must have a status:
- Idea
- Planned
- In Build
- Live
- Completed
- Scaled
- Archived
Prioritisation Model
High Priority
- strong data-backed ideas
- high-impact funnel stages
- high-traffic areas
Medium Priority
- moderate impact ideas
- supporting tests
Low Priority
- speculative ideas
- low traffic areas
Tracking Requirements
Each test must record:
- start date
- end date
- traffic allocation
- segments tested
- results
- winning variation
Learning Repository Rule
All results must be stored.
Required Output
- what worked
- what failed
- why
- what to test next
Rule
No recorded learning:
→ test is wasted
Cross Brain Integration
Experimentation Brain
→ owns backlog
Ads Brain
→ feeds creative ideas
Conversion Brain
→ feeds funnel improvements
Affiliate Brain
→ feeds offer variations
Content Brain
→ feeds messaging
Data Brain
→ feeds insights
Failure Modes Prevented
- random testing
- duplicated tests
- lost ideas
- poor prioritisation
- lack of learning
- disconnected experiments
Governance Role
This framework ensures:
- structured testing execution
- consistent workflow
- visibility of all experiments
- repeatable optimization
Relationship To Other MWMS Standards
- Experimentation Brain Optimization Target Selection Framework
- Experimentation Brain Personalization Testing Framework
- Data Brain Measurement Integrity Framework
- Conversion Brain Behaviour Trigger Framework
Drift Protection
The system must prevent:
- running tests without backlog entry
- missing hypothesis
- untracked variations
- lost results
- repeated failed ideas
Architectural Intent
This framework ensures:
- MWMS operates as a testing system
- ideas compound over time
- learnings are retained
- execution becomes scalable
It transforms testing from:
→ random actions
into:
→ controlled system execution
Final Rule
If it is not in the backlog:
→ it must not be tested
Change Log
Version: v1.0
Date: 2026-05-03
Author: HeadOffice
Change:
Created Creative Variation Backlog Framework defining structured capture, prioritisation, execution, and learning system for all MWMS testing activities based on CXL experimentation workflow.
Change Impact Declaration
Pages Created:
Experimentation Brain Creative Variation Backlog Framework
Pages Updated:
None
Pages Deprecated:
None
Registries Requiring Update:
Experimentation Brain Page Registry
Canon Version Update Required:
No
Change Log Entry Required:
Yes