One variable
Clean reads beat multi-change chaos.
Conversion rate optimization · CRO
Liberty Weblab
A/B testing that turns opinions into measured wins
Hypothesis design, clean experiment setup, and readouts you can trust - so you ship what actually lifts conversion.
Experiment board
A pipeline - not random page tweaks
Ideas move from backlog to live test to decision. You always know what’s running, what’s next, and what already won.
Backlog
- CTA wording on pricing
- Form field reduction
- Social proof placement
Running
- Hero offer clarity · Week 2
- Checkout button color · Week 1
Decided
- Headline rewrite · Winner B
- Trust bar · Inconclusive
What we test
Experiments matched to your funnel stage
We don’t test everything at once. One primary variable. Clear success metric. Enough traffic to call a real winner.
- Copy Headlines, offers, CTA labels
- Layout Fold order, proof blocks, nav noise
- Forms Fields, steps, error handling
- Pricing Plan tables, anchors, guarantees
- Checkout Steps, payment cues, cart friction
- Mobile Thumb reach, speed, sticky CTAs
Readouts you can trust
Significance before celebration
We set sample size, primary metric, and stop rules up front - so “looks better” never overrides “is better.”
- Primary metric
- One conversion event the business cares about
- Guardrails
- Revenue, lead quality, or bounce watched in parallel
- Call the test
- Winner, loser, or inconclusive - with next action
Ship the winner
From experiment to default experience
Winning variants get documented and rolled out. Learnings feed the next backlog so momentum compounds.
What’s included
A testing program - not a one-off tweak
- 01
Opportunity map
Where tests will move the needle fastest.
- 02
Hypothesis cards
Change, metric, and expected impact.
- 03
Experiment setup
Tracking, variants, and traffic split.
- 04
Live monitoring
Health checks while the test runs.
- 05
Decision brief
Winner call with charts and caveats.
- 06
Rollout notes
What to ship and what to test next.
Process
How experiments move from idea to insight
-
Frame
Pick the page, metric, and audience for the test.
-
Build
Design the variant and wire tracking correctly.
-
Run
Split traffic and protect data quality.
-
Decide
Call the result and schedule the next experiment.
Business metrics
We optimize for outcomes that matter - not vanity clicks.
Compounding backlog
Every test feeds a smarter queue.
FAQ
A/B testing questions
What is A/B testing?
A/B testing compares two versions of a page or element - a control and a variant - to see which performs better on a defined conversion metric with enough traffic for a reliable decision.
How much traffic do we need?
It depends on your baseline conversion rate and the lift you hope to detect. We’ll estimate sample size before launch so you know if a test is feasible now or should wait for more volume.
What tools do you use?
We work with common experimentation platforms and analytics stacks. Tool choice depends on your site, privacy needs, and whether engineering prefers native or third-party testing.
What if a test is inconclusive?
That’s a valid outcome. We document what we learned, avoid false winners, and redesign the next hypothesis instead of forcing a pick.
Ready to stop guessing and start testing?
Share your key landing pages - we’ll propose a first experiment backlog.