Compare

CarbonCopies AI vs. A/B Testing

Both aim to lift conversion. They answer different questions. At very different timelines.

A woman looking into her laptop and smiling as she does not have to manually UI test her products

CarbonCopies vs. A/B testing
side-by-side comparison

for enterprise eCommerce and consumer focused digital teams

Traditional A/B testing, aka randomized multi-variate testing, tells you which variant wins in production by splitting real users and measuring impact with statistical analysis. Optimizely and Adobe Target are common enterprise platforms for running these experiments.  

‍CarbonCopies simulates distinct customer personas moving through your journey to find why they struggle and what to change next.

Try Now

When A/B testing is best

  • You can split users reliably so Variant A and B don’t bleed into each other AND enough traffic to reach significance in a reasonable time
  • You trust your tracking and attribution
  • You already know what will improve conversion and for which user segment

Tradeoff: A/B testing is often slow to develop and run: low-volume flows, heavy governance, localization complexity, and “too many moving parts” releases.

Learn more

When CarbonCopies is best

  • When you need variant ideas by persona impact and build a clear experiment backlog
  • If you see conversion dropping in specific demographics and you need to pinpoint the issue(s)
  • If you have plenty of data but still can’t explain the “why” behind drop-offs with analytics alone

Tradeoff: simulation is NOT a replacement for live-user validation. It’s strongest at finding friction and generating targeted fixes, not declaring final lift.

Learn more

Recommended workflow that wins in enterprise consumer teams

If A/B testing is your “court ruling,” CarbonCopies is your “investigation.” Use both, in that order, to move faster without guessing.

  • CarbonCopies first: identify persona-specific friction, generate 2–3 tight variant directions, define expected impact and guardrails.
  • A/B testing second: validate the best variants in production, ship winners, and feed results back into your experimentation program.
Find frictions today