Document Type: Framework
Status: Active
Version: v1.0
Authority: Customer Brain
Applies To: All MWMS environments where user behaviour can be influenced within a journey
Parent: Customer Brain Canon
Last Reviewed: 2026-04-26
Purpose
The Customer Brain Next Best Action Framework defines how MWMS determines the optimal intervention to move a user forward in their journey toward conversion or deeper engagement.
Traditional analysis focuses on:
- what happened
- what converted
- what did not convert
This framework shifts focus to:
→ what should happen next
The goal is to reduce friction, accelerate journeys, and increase conversion probability by guiding behaviour in real time.
Core Principle
Every user interaction represents a decision opportunity.
At any point in a journey:
→ there is a next best action
The system must identify and influence that action.
🔴 Next Best Action Rule
For every user state, MWMS must define:
- current behavioural position
- likely next actions
- optimal next action
The optimal action is defined as:
→ the action most likely to move the user closer to conversion
🔴 Journey Compression Rule
The objective of optimisation is not more interactions.
The objective is fewer interactions to conversion.
Example:
5 touchpoint journey → compressed to 4
Compression improves:
- conversion rate
- speed to revenue
- user experience
🔴 Behavioural Intervention Rule
MWMS must actively influence behaviour through:
- messaging
- UX changes
- content exposure
- offer presentation
- timing adjustments
Intervention must be:
→ intentional
→ context-aware
→ behaviour-driven
🔴 State Based Action Rule
Next best action must be based on user state.
States may include:
- unaware
- researching
- comparing
- high intent
- ready to convert
- post-conversion
Each state requires different actions.
🔴 Micro Signal Utilisation Rule
Next best action must use micro conversions.
Examples:
- product view
- scroll depth
- CTA interaction
- form start
Micro signals indicate:
→ readiness
→ hesitation
→ interest level
Actions must respond to these signals.
🔴 Lag Awareness Rule
Time between interactions must be considered.
Examples:
- immediate action → high intent
- delayed return → hesitation
- long gap → reactivation required
Next best action must adjust based on timing.
🔴 Journey Pattern Recognition Rule
MWMS must analyse aggregated journeys to identify:
- common successful paths
- common failure points
- high-conversion sequences
Next best actions must be derived from:
→ proven behavioural patterns
🔴 Friction Reduction Rule
Next best action must reduce friction.
Examples:
- simplify decisions
- remove unnecessary steps
- clarify value
- reduce cognitive load
Friction slows progression.
Reduced friction accelerates conversion.
🔴 Content Alignment Rule
Content must match user intent.
Examples:
Early stage:
- education
- comparison
- exploration
Late stage:
- pricing
- urgency
- reassurance
Mismatch reduces conversion probability.
🔴 Channel Coordination Rule
Next best action must consider channel context.
Examples:
- PPC traffic → high intent
- SEO traffic → mixed intent
- email → relationship-driven
Actions must align with:
→ entry channel
→ expected intent level
🔴 Real Time Adaptation Rule
Next best action must adapt dynamically.
As new events occur:
→ action strategy must update
Static journeys reduce effectiveness.
Dynamic journeys improve outcomes.
🔴 Segmentation Rule
Next best action must operate at segment level.
Segments may include:
- traffic source
- behaviour type
- device
- engagement depth
- customer history
Different segments require different actions.
🔴 Attribution Integration Rule
Next best action must be informed by attribution.
Attribution identifies:
- high-value touchpoints
- influential interactions
- effective sequences
Next best action uses this to:
→ prioritise impactful interventions
🔴 Decision Usage Rule
Next best action must influence:
- UX decisions
- campaign strategy
- remarketing logic
- content prioritisation
- offer positioning
It must not remain theoretical.
Failure Modes Prevented
- analysing journeys without acting
- long inefficient conversion paths
- mismatched messaging
- ignoring behavioural signals
- static user experiences
- delayed conversions
Drift Protection
The system must prevent:
- treating all users the same
- ignoring behavioural state
- ignoring timing between interactions
- failing to adapt journeys dynamically
- over-reliance on historical averages
Architectural Intent
The Customer Brain Next Best Action Framework transforms MWMS from:
→ passive analysis system
into:
→ active behavioural optimisation system
It ensures MWMS:
- understands behaviour
- predicts progression
- influences outcomes
Final Rule
If MWMS does not influence the next action:
→ it is not optimising behaviour
Change Log
Version: v1.0
Date: 2026-04-26
Author: Customer Brain
Change:
Created new framework introducing next best action logic for behavioural optimisation.
Introduces:
- journey compression
- behavioural intervention
- state-based action logic
- micro signal usage
- real-time adaptation
Change Impact Declaration
Pages Created:
Customer Brain Next Best Action Framework
Pages Updated:
None
Pages Deprecated:
None
Registries Requiring Update:
Customer Brain Page Registry
Canon Version Update Required:
No
Change Log Entry Required:
Yes
End of Framework