Document Type: Framework
Status: Active
Version: v1.0
Authority: MWMS HeadOffice
Parent: Research Brain Canon
Slug: research-brain-behavioural-intent-signal-framework
Purpose
Defines how MWMS interprets customer behaviour as probabilistic indicators of purchase intent, engagement likelihood, and conversion readiness.
Customer behaviour provides observable signals indicating decision stage progression.
Different behaviours signal different levels of intent strength.
Understanding intent strength improves:
traffic quality evaluation
CRO prioritisation decisions
lifecycle timing precision
personalisation relevance
acquisition optimisation decisions
Intent signals allow MWMS to allocate resources toward highest probability opportunities.
Core Principle
Not all behaviour signals equal purchase probability.
Different actions represent different levels of decision readiness.
Higher intent behaviours indicate greater likelihood of conversion.
Intent signal hierarchy improves prioritisation accuracy.
Prioritisation accuracy improves conversion efficiency.
Intent Signal Hierarchy
Customer behaviours can be structured into relative intent strength levels.
Low Intent Signals
indicate early stage awareness or curiosity.
examples:
content page visits
blog interaction
category browsing
informational page engagement
low intent signals indicate topic interest but not immediate purchase readiness.
low intent behaviours useful for education sequencing.
Moderate Intent Signals
indicate active evaluation behaviour.
examples:
product page views
repeated product interaction
feature comparison behaviour
review reading behaviour
evaluation signals indicate consideration phase entry.
consideration stage benefits from trust reinforcement and clarity messaging.
High Intent Signals
indicate strong purchase probability.
examples:
cart creation
checkout initiation
repeated cart interaction
shipping information review
high intent signals indicate decision proximity.
high intent signals justify prioritised intervention logic.
timely intervention improves conversion probability.
Post-Purchase Signals
indicate relationship progression strength.
examples:
second purchase behaviour
subscription enrolment
repeat engagement behaviour
repeat behaviour signals increased lifetime value probability.
relationship progression signals increase retention stability.
Behaviour Recency Principle
recent behaviour signals carry stronger predictive value than historical behaviour signals.
recent interactions indicate current decision context.
older signals may reflect outdated preferences.
recency weighting improves relevance accuracy.
recent intent signals justify prioritised messaging response.
Behaviour Frequency Principle
repeated behaviour indicates stronger interest stability.
example:
single product view indicates exploratory interest.
multiple product views indicate increased evaluation intensity.
repeated interaction increases confidence in intent classification.
frequency strengthens signal reliability.
Behaviour Depth Principle
interaction depth indicates engagement strength.
examples:
short page visits indicate low evaluation depth.
extended page interaction indicates deeper consideration.
content depth improves interpretation accuracy.
deeper interaction suggests stronger informational need.
Relationship to Segmentation Framework
intent signals may define segment boundaries.
example:
high intent segment
moderate intent segment
low intent segment
segment differentiation improves targeting precision.
targeting precision improves conversion efficiency.
Relationship to Behaviour-Based Automation Framework
intent signals determine trigger priority logic.
example:
cart abandonment triggers immediate intervention messaging.
product browsing may trigger delayed educational messaging.
intent classification improves timing accuracy.
timing accuracy improves lifecycle efficiency.
Relationship to CRO Prioritisation Framework
intent signals indicate friction location within funnel.
example:
high product views with low cart creation indicates product page friction.
high cart creation with low checkout completion indicates checkout friction.
intent behaviour improves CRO hypothesis precision.
precise hypotheses improve optimisation efficiency.
Relationship to Traffic Quality Framework
traffic sources producing higher intent signals often produce higher conversion efficiency.
example:
traffic producing high product interaction depth indicates stronger audience alignment.
traffic quality assessment should consider behavioural signals, not only click metrics.
intent signals improve channel evaluation accuracy.
Relationship to LTV Signal Framework
higher intent behaviours often correlate with stronger long-term value trajectories.
repeat purchase behaviour indicates stronger retention probability.
stronger retention probability increases expected lifetime value.
intent signals support value prediction accuracy.
Drift Protection
system must prevent:
treating all behavioural signals as equal strength indicators
ignoring recency weighting logic
over-interpreting single behavioural events
ignoring frequency reinforcement signals
applying identical messaging to different intent levels
intent strength must influence intervention priority.
priority alignment improves resource allocation efficiency.
Architectural Intent
Research Brain Behavioural Intent Signal Framework enables MWMS to interpret behavioural actions as structured indicators of decision readiness and value probability.
intent clarity improves prioritisation accuracy.
prioritisation accuracy improves conversion efficiency.
improved efficiency increases ecosystem performance stability.
Future Expansion
predictive intent scoring models
dynamic behavioural weighting algorithms
probabilistic intent clustering models
reinforcement learning prioritisation logic
cross-channel behavioural intent synchronisation
future models improve signal precision.
Final Rule
Behaviour indicates probability.
MWMS prioritises actions aligned with strongest intent signals.
Change Log
Version: v1.0
Date: 2026-04-12
Author: MWMS HeadOffice
Change:
Initial creation of behavioural intent classification framework defining hierarchy of signal strength improving prioritisation accuracy and lifecycle timing precision.
CHANGE IMPACT
Pages Created:
Research Brain Behavioural Intent Signal Framework
Pages Updated:
None
Pages Deprecated:
None
Registries Requiring Update:
MWMS Architecture Registry
MWMS Brain Registry
MWMS Intelligence Layer Map
MWMS Canon Hierarchy Map
Canon Version Update Required: No
Change Log Entry Required: Yes