Lesson
Funnels and micro-conversions
Lesson 3: map a conversion funnel step by step and choose micro-conversions that genuinely signal progress towards the business outcome.
The method behind Mentorele
WXM: the Wave Experimentation Model
A repeatable cycle that turns behaviour data into better decisions, and better decisions into conversion growth. Four phases: Wonder, Architect, Validate, Expand.
Phase 1 of 4
Wonder: First, ask better questions.
Look before touching anything: analytics and tag audits, session recordings, heatmaps and funnel baselines show who arrives, what they do, where they hesitate and when they leave.
What moves forward
- A measurement baseline you can trust
- A map of the highest-value conversion journey
- Clear questions for the next phase
WhoWhatWhereWhen
Phase 2 of 4
Architect: Turn the "why" into a plan worth building.
Diagnose why people do not convert, then translate the evidence into a structured program. Each hypothesis earns its place through impact, evidence, effort and test feasibility.
What moves forward
- Evidence-backed conversion hypotheses
- A prioritized experimentation roadmap
- A scoped CRO program tied to business goals
HypothesisPrioritizationCRO program
Phase 3 of 4
Validate: Build the variation. Let the evidence decide.
Design and build variations, QA the experience and tracking, and launch with defined success metrics. Tests run to an appropriate decision point with guardrails and statistical rigor.
What moves forward
- Variations built and quality-checked
- A/B tests with defined metrics and decision rules
- A documented result, including inconclusive tests
A/B testingQAMeasure
Phase 4 of 4
Expand: Roll out what works. Build on what you learn.
Roll winners out wherever the learning applies, raise testing velocity and feed new questions back into Wonder, with senior review at every step.
What moves forward
- Validated improvements shipped
- Learning shared across relevant journeys
- New questions for the next Wonder phase
Scale winnersRaise velocityShare learning
Each cycle makes the next one smarter: what Expand learns becomes the starting point for Wonder. WXM is the Wave Experimentation Model by Wavesy.
Why a cycle and not a checklist
Most CRO advice is a list of tactics. WXM is a loop. You look before you change anything (Wonder), you turn evidence into ranked hypotheses (Architect), you test with defined metrics and decision rules (Validate), and you roll out what works while carrying new questions into the next round (Expand). Each cycle starts smarter than the last.
Where PXL prioritization fits
The Architect phase needs a way to rank ideas that rewards evidence over opinion. Mentorele uses PXL, a prioritization framework created by CXL: mostly yes/no questions about noticeability, traffic, research evidence and effort. In WXM terms, PXL asks “what did Wonder actually show us?” before a test is scheduled.
WXM across the Academy
- Module 1: Foundations Overview of the whole cycle
- Module 2: Research Wonder
- Module 3: Analytics Wonder
- Module 4: Strategy Architect
- Module 5: Experiment science Validate
- Module 6: Implementation Validate
- Module 7: Applied CRO Expand
- Module 8: Practitioner practice Expand
Wonder resources
Lesson
What CRO is and is not
Lesson 1 of the free CRO course: define conversion rate optimization, separate it from hacks and redesigns, and see why it starts with understanding people.
Guide
CRO research: How to find out why visitors don't convert
CRO research methods for the WXM Wonder phase: analytics, recordings, heatmaps, surveys, interviews, usability tests and reviews, and what each can tell you.
Guide
Funnel analysis: How to find the step where visitors leave
How to build and read a conversion funnel, find the steps with the biggest absolute losses, segment without fooling yourself, and turn drop-offs into research questions.
Guide
What is CRO? Conversion rate optimization in plain English
CRO (conversion rate optimization) is the evidence-led practice of finding why visitors don't act and testing changes that help them. Definition, process and limits.
Template
CRO audit checklist: Find what's wrong with your page in 30 minutes
A free CRO audit checklist for the WXM Wonder phase: measurement, funnel, clarity, trust, friction, mobile and accessibility. Tick it in your browser or print it.
Architect resources
Lesson
Business outcomes versus conversion metrics
Lesson 2: why a higher conversion rate isn't always a better business, and how to pair conversion metrics with revenue, margin, retention and guardrails.
Guide
CRO hypothesis: How to write one that teaches you something
Write CRO hypotheses that link evidence, change, audience and expected effect, so every A/B test teaches you something. Includes a template and good and bad examples.
Guide
CRO prioritization: How to pick which test to run first
How to prioritize A/B test ideas with the PXL framework: the ten criteria, a worked example, how it compares with ICE, PIE and RICE, and where any scoring model breaks.
Guide
CRO strategy: How to build a program that doesn't fizzle out
A practical CRO strategy: tie optimization to business outcomes, run repeating WXM cycles, prioritize with PXL, and set the governance that keeps a program honest.
Psychology
Loss aversion: Why surprise costs feel so bad
Loss aversion explained for CRO: what prospect theory found, why recent research questions how general it is, ethical uses in ecommerce and SaaS, and how to test it.
Psychology
Social proof: Why we copy what people like us do
What social proof is, what the research does and doesn't show, how to use reviews and testimonials honestly in ecommerce and SaaS, and how to test it.
Validate resources
Guide
A/B testing: How to run tests you can actually trust
What A/B testing is, when to use it, and how to run a trustworthy test: hypothesis, metrics, sample size, QA, analysis and rollout, following the WXM cycle.
Guide
CRO tools: The A/B testing, heatmap and analytics tools we recommend
A buyer's guide to the CRO tools we recommend: A/B testing, heatmaps and recordings, analytics and tag management. Which to pick, what's free and what each is best for.
Guide
A/B test sample size: How long should your test run?
How to calculate A/B test sample size and duration from baseline rate, MDE, significance and power, why to run full weeks, and when to stop. Free calculator.
Guide
Statistical power and MDE: Will your test even notice a win?
How statistical power and minimum detectable effect (MDE) decide whether an A/B test can find a real lift, with a worked example and a practical way to choose your MDE.
Guide
Statistical significance: What it really means (and what it doesn't)
What statistical significance and p-values really mean in A/B testing, what they don't mean, and how to report results honestly with confidence intervals.
Tool
A/B test sample size calculator: How long should my test run?
Free A/B test sample size calculator: enter baseline rate, MDE, significance and power to get visitors per variant and duration. Method and assumptions shown.
Expand resources
Guide
Checkout optimization: Why shoppers bail at the last step
How to optimize ecommerce checkout: show total costs early, allow guest checkout, simplify forms, build payment trust and fix mobile issues, using research and A/B tests.
Guide
Ecommerce CRO: How to turn more browsers into buyers
Ecommerce CRO from research to rollout: the metrics that matter, where stores lose shoppers (search, product page, cart, checkout) and how to fix it with WXM.
Guide
Landing page optimization: How to make the first 5 seconds count
How to optimize a landing page: match the visitor's intent, make the value clear in seconds, answer objections, reduce form friction and test changes with WXM and PXL.
Guide
SaaS CRO: How to turn sign-ups into paying customers
SaaS conversion optimization across the funnel: sign-up, activation, trial-to-paid, pricing and retention. Which metrics to use and how to apply WXM and PXL to a product.
Frequently asked questions
What does WXM stand for?
WXM is the Wave Experimentation Model, created by Wavesy. Its four phases spell WAVE: Wonder, Architect, Validate, Expand.
How is WXM different from a generic CRO process?
It treats optimization as a loop rather than a list: every Expand phase produces new questions for the next Wonder phase, and inconclusive tests are documented as learning, not discarded.
Where does PXL fit in WXM?
In the Architect phase. After Wonder produces evidence, hypotheses are scored with PXL so that ideas backed by research, noticeable changes and low effort rise to the top of the roadmap.
Do I need special tools to use WXM?
No. Analytics, a way to watch real behaviour, a backlog, and a testing tool are enough to start. Mentorele’s templates cover each phase.
Sources
- WXM: the Wave Experimentation Model. Wavesy. Accessed 4 November 2026.
- PXL: A Better Way to Prioritize Your A/B Tests. CXL. Accessed 4 November 2026.