Document Type: Framework
Status: Active
Version: v1.0
Authority: MWMS HeadOffice
Applies To: automated lifecycle communication triggered by customer behaviour signals
Parent: Ecommerce Brain Canon
Last Reviewed: 2026-04-12
Purpose
The Ecommerce Brain Behaviour Triggered Messaging Framework defines how customer behaviour signals activate lifecycle communication designed to improve conversion probability, retention strength, and customer lifetime value.
Behaviour-triggered messaging ensures communication relevance by responding to observable customer actions rather than relying solely on fixed campaign schedules.
The purpose of this framework is to:
• increase lifecycle messaging relevance
• improve repeat purchase probability
• reduce customer churn risk
• improve onboarding completion rates
• increase customer engagement depth
• strengthen behavioural habit formation
• improve customer experience continuity
• improve lifecycle revenue efficiency
Behaviour-triggered messaging aligns communication timing with customer readiness.
Improved timing increases conversion probability.
Scope
This framework applies to:
• automated lifecycle communication triggers
• onboarding sequence triggers
• repeat purchase triggers
• reactivation triggers
• abandonment triggers
• engagement-based communication triggers
• inactivity-based communication triggers
• behavioural progression messaging triggers
This framework governs behaviour-triggered communication logic inside Ecommerce Brain.
It does not govern:
• creative message production
• copywriting execution
• CRM technical configuration
• platform automation implementation
Those remain governed by Infrastructure Brain systems.
Definition / Rules
Core Principle
Customer behaviour provides signals regarding readiness, intent, and engagement level.
Communication timing must respond to these signals.
Behaviour-triggered communication improves:
message relevance
engagement probability
conversion probability
customer satisfaction
Irrelevant communication reduces engagement reliability.
Behavioural signals provide guidance for communication timing decisions.
Behaviour Signal Categories
Behaviour-triggered messaging may activate based on multiple signal types.
Engagement Signals
Customer interaction with brand assets.
Examples include:
product page views
content engagement
email interaction behaviour
site revisit frequency
feature interaction behaviour
Engagement behaviour indicates active interest.
Active interest increases conversion probability.
Transaction Signals
Customer purchase activity.
Examples include:
first purchase completion
repeat purchase behaviour
order frequency patterns
average order value behaviour
Transaction signals indicate value development.
Transaction patterns inform lifecycle progression decisions.
Abandonment Signals
Customer interruption of conversion process.
Examples include:
cart abandonment
checkout abandonment
product page exit behaviour
form abandonment
Abandonment signals indicate friction or hesitation.
Communication may reduce uncertainty.
Inactivity Signals
Customer disengagement behaviour.
Examples include:
declining engagement frequency
extended time since last purchase
reduced interaction behaviour
Inactivity signals indicate retention risk.
Retention interventions may improve reactivation probability.
Progression Signals
Customer advancement through lifecycle stages.
Examples include:
repeat purchase achievement
subscription adoption
product ecosystem exploration
loyalty programme participation
Progression signals indicate increasing brand alignment.
Messaging may reinforce behavioural momentum.
Timing Sensitivity
Behaviour-triggered messaging must consider timing relevance.
Examples:
abandonment communication should occur shortly after interruption.
onboarding communication should occur shortly after first purchase.
reactivation communication should consider engagement decay patterns.
Timing influences communication effectiveness.
Delayed communication may reduce behavioural relevance.
Relationship to Lifecycle Messaging Architecture
Behaviour-triggered communication functions within lifecycle structure.
Lifecycle architecture defines stage progression logic.
Behaviour signals determine timing of messaging within lifecycle stages.
Together they improve communication relevance.
Improved relevance increases engagement probability.
Relationship to Segmentation Frameworks
Customer segments demonstrate different behavioural patterns.
Examples:
high-value customers may require different messaging frequency.
new customers may require stronger onboarding support.
at-risk customers may require retention-focused messaging.
Segment-aware triggers improve communication precision.
Relationship to Attribution Framework
Triggered messaging may influence revenue indirectly.
Examples:
behaviour-triggered communication may increase repeat purchase likelihood.
communication may increase brand recall.
communication may increase product awareness.
Attribution interpretation must consider behavioural influence effects.
Relationship to Zero Party Data Signals
Declared preference signals may refine behaviour-triggered messaging relevance.
Examples:
topic interest signals influence content relevance.
problem signals influence solution messaging relevance.
intent signals influence offer relevance.
Signal integration improves communication precision.
Behaviour Trigger Constraints
Trigger volume must remain balanced.
Excessive triggers may create communication fatigue.
Insufficient triggers may reduce lifecycle influence.
Trigger logic must maintain relevance discipline.
Communication must remain purposeful.
Drift Protection
The system must prevent:
triggering communication without behavioural relevance
excessive automation complexity reducing interpretability
excessive communication frequency
ignoring customer lifecycle stage differences
relying solely on time-based communication schedules
ignoring behavioural signal context
Behaviour-triggered messaging must remain behaviour-driven.
Architectural Intent
Ecommerce Brain Behaviour Triggered Messaging Framework exists to ensure lifecycle communication responds to customer behaviour signals rather than arbitrary timing assumptions.
Its role is to improve lifecycle relevance precision and strengthen behavioural progression across customer journey stages.
Relevant communication improves engagement reliability.
Improved engagement strengthens customer relationships.
Future Expansion
Behaviour-triggered messaging may integrate:
predictive behaviour modelling
adaptive trigger calibration
engagement probability scoring
trigger priority weighting
dynamic communication sequencing
signal confidence scoring
Future development may improve trigger precision.
Final Rule
Communication timing must align with behavioural readiness signals.
Behaviour-triggered messaging must improve relevance rather than increase communication volume.
Ecommerce Brain must prioritise signal interpretation discipline.
Change Log
Version: v1.0
Date: 2026-04-12
Author: MWMS HeadOffice
Change: Initial creation of Ecommerce Brain Behaviour Triggered Messaging Framework defining behavioural trigger categories, lifecycle integration logic, segmentation relationships, drift protection requirements, and architectural intent aligned with MWMS Canon standards.
CHANGE IMPACT
Pages Created:
• Ecommerce Brain Behaviour Triggered Messaging Framework
Pages Updated:
None
Pages Deprecated:
None
Registries Requiring Update:
• MWMS Architecture Registry
• MWMS Brain Registry
• MWMS Brain Interaction Map
• MWMS Canon Hierarchy Map
Canon Version Update Required: No
Change Log Entry Required: Yes
END – ECOMMERCE BRAIN BEHAVIOUR TRIGGERED MESSAGING FRAMEWORK v1.0