CSV template / Free resource
CRO experiment backlog for evidence-led website improvements
Organise conversion research, hypotheses, page changes, evidence, effort, risk, metrics and learning without treating every redesign as an experiment.
Download the CRO backlogNo email gate · Editable CSV · No tracking claims
Purpose
Use the file to improve the decision—not complete paperwork.
Use this backlog to connect observed friction with a proposed change and a validation method. It supports A/B tests where volume permits and safer before-and-after checks elsewhere.
01Page and audience segment
02Evidence source and observed friction
03Hypothesis and proposed change
04Primary and guardrail metrics
05Impact, confidence, effort and risk
06Owner, status and dates
07Outcome, learning and follow-up
How to use it
Four steps from template to working system.
- 01
Capture evidence
Link analytics, interviews, recordings, usability findings or sales feedback to a specific journey problem.
- 02
Write a causal hypothesis
Describe why a defined change may affect a meaningful behaviour for a defined audience.
- 03
Choose validation
Use an experiment only when traffic, implementation and decision conditions support it.
- 04
Preserve learning
Record the result, limitations and next action even when the change did not win.
Working guidance
Use the template with context, evidence and ownership.
Open each note when that decision becomes relevant. The complete guidance remains available without turning the page into a wall of copy.
01Conversion rate needs a denominator
Keep the audience, event definition, period and traffic mix visible. A percentage can change while qualified volume or profitability declines.
02Protect guardrails
Monitor lead quality, revenue, accessibility, performance and user trust so one local metric does not damage the wider journey.
Resource questions
Scope, use and validation—answered.
01Is every website change an A/B test?
No. A valid controlled experiment requires a testable hypothesis, appropriate allocation, stable measurement and enough evidence for the decision.
02What if traffic is low?
Use qualitative research, usability checks, message testing and carefully documented sequential evidence without pretending it has experimental certainty.
Download and continue