Gold by MangoMagic

CMO · Framework · Intermediate · Saves 20+ hours

A/B Testing Prioritization Framework

A framework for prioritizing what to test based on potential impact and effort required. Ensures you run tests that actually matter.

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What's included

  • PIE Framework Calculator
    • Potential impact scoring
    • Importance scoring
    • Ease scoring
    • Prioritization matrix
  • Test Idea Generator
    • High-impact test ideas by channel
    • Test hypothesis templates
    • Success criteria framework
  • Test Documentation
    • Test brief template
    • Results documentation
    • Learning repository template
  • Statistical Framework
    • Sample size calculator
    • Significance threshold guidelines
    • Test duration estimator

Best used when

  • Planning testing roadmap
  • Allocating testing resources
  • Improving testing program ROI
  • Training testing team
  • Quarterly test planning

Why this is Gold

Most teams run random tests. This framework ensures you test the things that will have the biggest impact, with proper documentation to capture learnings.

The template

The Template

PIE FRAMEWORK CALCULATOR

Scoring Criteria

Factor Score 1 Score 5 Score 10
Potential <5% lift 10-20% lift >30% lift
Importance Low traffic page Medium traffic High traffic
Ease >2 weeks 1-2 weeks <1 week

Test Prioritization Matrix

Test Idea P (1-10) I (1-10) E (1-10) PIE Score Rank
/30
/30
/30
/30
/30

Priority Rule: Run tests with PIE score >20 first


HIGH-IMPACT TEST IDEAS

Landing Page Tests

Test Potential Impact Best For
Headline A vs B 20-40% Low conversion pages
Long form vs short form 15-30% Lead gen pages
Form fields (fewer) 10-25% High-friction forms
Social proof placement 10-20% Low-trust industries
CTA color/text 10-25% High-traffic pages

Email Tests

Test Potential Impact Best For
Subject line 15-30% open rate Any email
Send time 5-15% open rate Large lists
Personalization 10-25% CTR Nurture sequences
CTA button vs text 10-20% CTR Promo emails

TEST HYPOTHESIS TEMPLATE

Hypothesis Format:

If we [change], then [metric] will [improve/decrease] because [reason].

Example:

If we reduce form fields from 7 to 4, then conversion rate will increase by 15-25% because shorter forms reduce friction.


STATISTICAL FRAMEWORK

Sample Size Calculator

Baseline Conv. Minimum Detectable Effect Sample Needed (per variant)
1% 20% relative (1.0% → 1.2%) 39,000
2% 20% relative (2.0% → 2.4%) 19,000
5% 20% relative (5.0% → 6.0%) 7,400
10% 20% relative (10% → 12%) 3,600

Test Duration Guidelines

Daily Visitors Baseline Conv. Min Duration
500 2% 8 weeks
1,000 2% 4 weeks
5,000 2% 1 week
10,000 2% 3-4 days

Rules:

  • Run tests for minimum 1 full business cycle
  • Reach 95% statistical significance
  • Document ALL results, including losers

TEST DOCUMENTATION TEMPLATE

Field Entry
Test name
Hypothesis
Primary metric
Start date
End date
Sample size
Control result
Variant result
Lift %
Significance %
Winner
Key learning
Next action

Frequently asked questions

What is the A/B Testing Prioritization Framework?

A framework for prioritizing what to test based on potential impact and effort required. Ensures you run tests that actually matter.

Who is the A/B Testing Prioritization Framework for?

It is built for CMOs and their teams working on Demand Generation. The AI coach adapts it to your company, stage, and goals.

How long does the A/B Testing Prioritization Framework take to use?

It saves roughly 20+ hours versus building from scratch. Our AI coach can tailor the framework to your situation in minutes, then hand you a step-by-step plan.

Is the A/B Testing Prioritization Framework free?

Yes. You can read the full framework and start getting coached through it for free. Sign in to save your tailored version and track your next steps.

How does the AI coach help with the A/B Testing Prioritization Framework?

The coach teaches you the framework, asks a few questions about your business, tailors the framework to you, and gives you measurable next steps to execute.