Document Type: Framework
Status: Active
Authority: Experimentation Brain
Applies To: Affiliate Brain, Ads Brain, Conversion Brain, Research Brain, Content Brain, AIBS Brain
Parent: Experimentation Brain Canon
Version: v1.0
Last Reviewed: 2026-04-18
Purpose
The Experimentation Brain Loop KPI Mapping Framework defines how MWMS measures performance across growth loops.
Growth loops generate compounding impact.
However, loops can only be optimised when each stage of the loop is measurable.
This framework ensures loop performance can be diagnosed and improved through structured measurement.
Without loop-level KPIs:
constraints cannot be identified
experiments cannot be prioritised
growth mechanisms cannot be improved
loop effectiveness cannot be validated
This framework enables MWMS to transform abstract growth models into measurable systems.
Scope
This framework applies to:
Affiliate Brain growth loops
Ads Brain optimisation loops
Conversion Brain behaviour loops
Content Brain authority loops
Research Brain insight loops
AIBS Brain product loops
This framework governs:
loop stage measurement logic
conversion step KPI definition
loop bottleneck identification
loop optimisation prioritisation
This framework does not govern:
individual experiment design
traffic allocation decisions
creative strategy choices
These remain governed by Brain-level experimentation frameworks.
Definition
A Growth Loop is a reinforcing system where output from one cycle contributes to future input.
Loops create compounding growth effects.
Example loop:
user acquisition → user value → user sharing → new users → repeat cycle
Each stage within the loop influences total loop performance.
Loop optimisation requires measurement of transitions between stages.
Core Loop Structure
MWMS uses a four-stage loop structure:
Trigger
Action
Value Experience
Reinforcement
These stages allow structured KPI assignment.
Stage 1 — Trigger
A trigger initiates user movement into the loop.
Triggers may include:
advert exposure
search discovery
email prompt
referral recommendation
notification
content discovery
Trigger effectiveness influences entry volume into loop.
Example KPIs:
click-through rate
open rate
impression-to-click ratio
traffic volume
engagement initiation rate
Stage 2 — Action
Action represents the behaviour taken by the user after trigger exposure.
Examples:
clicking advertisement
opening landing page
starting trial
signing up
watching video
reading content
Action effectiveness influences loop continuation probability.
Example KPIs:
landing page engagement rate
signup rate
video completion rate
page interaction depth
initial conversion rate
Stage 3 — Value Experience
Value experience represents successful delivery of perceived benefit.
User must recognise value in order to continue loop progression.
Examples:
product usefulness
information satisfaction
problem resolution
entertainment value
perceived advantage
Value experience strongly influences retention probability.
Example KPIs:
return visit rate
time on platform
product usage frequency
engagement depth
repeat interaction frequency
Stage 4 — Reinforcement
Reinforcement creates loop continuation or expansion.
User contributes new input into loop.
Examples:
referral sharing
repeat purchase
content sharing
email subscription continuation
community participation
Reinforcement determines loop strength.
Example KPIs:
referral rate
repeat purchase frequency
subscription renewal rate
content sharing frequency
community participation rate
Loop Conversion Mapping
Each transition between loop stages has a measurable conversion rate.
Example:
Trigger → Action conversion rate
Action → Value conversion rate
Value → Reinforcement conversion rate
Weak transitions indicate optimisation opportunity.
Loop Bottleneck Identification
Loop bottlenecks occur when one stage significantly underperforms relative to others.
Example:
strong traffic volume
low activation rate
indicates constraint in Action stage.
Example:
strong usage
low referral behaviour
indicates constraint in Reinforcement stage.
Bottleneck identification informs Growth Lever selection.
Loop Measurement Granularity
Loops may be measured at different levels:
macro loop level
micro step level
Example macro loop:
acquisition → retention → referral
Example micro loop:
ad click → page view → scroll depth → CTA click → purchase
Granularity selection depends on:
traffic volume
data availability
optimisation priority
Loop Measurement Limitations
Some loop stages may not be directly measurable.
Example:
word-of-mouth referrals
offline sharing
private sharing environments
Proxy metrics may be used when direct measurement is unavailable.
Example:
survey responses
traffic source inference
post-purchase attribution surveys
Relationship to Growth Model Architecture
Growth Model Architecture identifies loop structures.
Loop KPI Mapping Framework defines how loops are measured.
Together they enable structured optimisation.
Relationship to Growth Lever Framework
Growth Levers often correspond to weak loop stages.
Example:
increase referral participation rate
increase onboarding completion rate
increase repeat purchase frequency
Loop measurement identifies leverage opportunities.
Governance Rule
Loops must have defined measurable KPIs before optimisation begins.
Unmeasured loops cannot be systematically improved.
Loop assumptions must be validated through observable signals where possible.
Version Control
v1.0
Initial definition of loop KPI mapping structure within Experimentation Brain.