Ecommerce Brain Behaviour-Based Automation Framework

Document Type: Framework
Status: Active
Version: v1.0
Authority: MWMS HeadOffice
Parent: Ecommerce Brain Canon
Slug: ecommerce-brain-behaviour-based-automation-framework


Purpose

Defines how MWMS uses customer behaviour signals to trigger automated lifecycle communications that increase conversion efficiency, retention durability, and customer lifetime value.

Automation allows communication to respond to behaviour in near real time.

Behaviour-responsive communication increases:

message relevance
timing accuracy
lifecycle progression speed
repeat purchase probability
engagement persistence

Higher behavioural alignment improves conversion probability without increasing acquisition costs.


Core Principle

Customer behaviour reveals intent.

Intent-aligned communication increases decision probability.

Automation allows MWMS to deliver communication at moments of highest behavioural relevance.

Relevant communication delivered at correct time increases lifecycle efficiency.


Behaviour Trigger Categories

Entry Triggers

occur when a customer enters the ecosystem.

examples:

email signup
SMS subscription
account creation
lead capture completion

entry triggers initiate onboarding sequence logic.

onboarding improves first purchase probability.


Evaluation Triggers

occur when customers demonstrate product interest behaviour.

examples:

product page viewing
category browsing
repeat product interaction
search activity patterns

evaluation triggers indicate active consideration phase.

timely messaging may reduce decision friction.


Cart Activity Triggers

occur when customers demonstrate purchase intent.

examples:

cart creation
checkout initiation
cart abandonment

cart triggers indicate strong purchase probability.

intervention messaging may recover otherwise lost conversions.


Purchase Triggers

occur when transaction is completed.

examples:

order confirmation
first purchase completion
repeat purchase completion

purchase triggers initiate post purchase lifecycle sequence.

post purchase communication improves second purchase probability.


Engagement Triggers

occur when customers interact with brand communication.

examples:

email click behaviour
SMS response behaviour
content interaction behaviour

engagement triggers indicate communication receptivity.

high engagement segments may tolerate higher message frequency.

low engagement segments may require reduced frequency.


Inactivity Triggers

occur when expected behaviour does not occur.

examples:

absence of repeat purchase
declining engagement frequency
prolonged inactivity period

inactivity triggers indicate churn risk.

reactivation messaging may restore engagement probability.


Automation Sequencing Logic

automation flows should align with behavioural progression patterns.

example progression:

entry behaviour → onboarding messaging
product interest → evaluation support messaging
purchase → reassurance messaging
inactivity → reactivation messaging

sequence structure should reflect decision journey progression.

aligned sequencing improves lifecycle progression efficiency.


Behaviour Sensitivity Principle

different behaviours carry different predictive strength.

example:

cart abandonment indicates higher purchase intent than product page view.

repeat purchase behaviour indicates higher retention probability than single purchase behaviour.

behaviour weight should influence trigger prioritisation logic.

stronger signals justify higher intervention priority.


Relationship to Lifecycle Messaging Framework

behaviour triggers determine when lifecycle messaging should be delivered.

lifecycle messaging determines what content should be delivered.

trigger accuracy improves message timing relevance.

message relevance improves conversion probability.


Relationship to List Growth Asset Framework

larger subscriber base increases number of behaviour-triggered communication opportunities.

larger audience increases automation leverage surface area.

automation effectiveness scales with audience size.

owned audience infrastructure enables behaviour-triggered communication deployment.


Relationship to Zero Party Data Protocol

behaviour triggers may be combined with declared preference signals.

combined signals improve relevance precision.

improved precision increases engagement probability.

greater relevance improves lifecycle efficiency.


Relationship to Cohort Behaviour Framework

behaviour-triggered messaging influences cohort retention curves.

improved retention increases cohort stability.

stable cohorts improve forecasting reliability.

automation improves lifecycle progression consistency.


Automation Frequency Considerations

over-triggering communication may reduce engagement quality.

under-triggering communication may reduce lifecycle progression speed.

balanced trigger frequency improves long-term engagement persistence.

frequency optimisation should consider engagement sensitivity patterns.


Drift Protection

system must prevent:

triggering communication without behavioural relevance
excessive messaging frequency
ignoring engagement fatigue signals
failing to respond to high intent behaviour signals
applying identical automation logic across all segments

automation must remain behaviour-responsive.

behaviour responsiveness improves lifecycle efficiency.


Architectural Intent

Ecommerce Brain Behaviour-Based Automation Framework enables MWMS to deploy lifecycle communication in response to observed customer behaviour signals.

behaviour-responsive messaging increases lifecycle progression probability.

improved lifecycle progression increases realised customer value.

higher realised value improves growth sustainability.


Future Expansion

predictive trigger modelling
dynamic behavioural weighting logic
adaptive automation sequencing
reinforcement learning messaging triggers
cross-channel behavioural trigger coordination

future models improve automation precision.


Final Rule

Behaviour reveals timing opportunity.

MWMS aligns communication timing with behavioural signals to improve lifecycle efficiency.


Change Log

Version: v1.0
Date: 2026-04-12
Author: MWMS HeadOffice

Change:
Initial creation of framework defining behaviour-triggered lifecycle automation structure improving relevance, timing accuracy, and retention durability.


CHANGE IMPACT

Pages Created:

Ecommerce Brain Behaviour-Based Automation Framework

Pages Updated:

None

Pages Deprecated:

None

Registries Requiring Update:

MWMS Architecture Registry
MWMS Brain Registry
MWMS Lifecycle Map
MWMS Canon Hierarchy Map

Canon Version Update Required: No
Change Log Entry Required: Yes