A/B testing
Test every personalization, prove every gain
Ecommerce A/B testing tells you whether a change made money or just looked good. In Skubl, every personalized experience can run against a holdout group of shoppers who see your default store, so you can see the real lift in conversion rate and revenue per visitor.
Testing is built into Skubl’s ecommerce personalization, not bolted on.
Illustrative example · sample store
The problem
Personalization without a control group is guesswork
Revenue went up after you launched a new experience. Was it the experience, the season or the sale that started the same week? Without a holdout, you can’t tell.
- 01
Correlation dressed up as results
“Revenue influenced” counts sales that would have happened anyway.
- 02
Tests that stop too early
A good first week is called a win before the result is reliable.
- 03
Separate testing tools
A split testing tool that can’t see your personalization can’t measure it.
How Skubl solves it
How ecommerce A/B testing works in Skubl
01
Holdout groups by default
A share of shoppers sees your default experience, so every result is measured against a real control.
02
Multivariate testing
Test several variants of an experience at once and see which combination performs best.
03
Shopify A/B testing without theme copies
Tests run inside your live theme, without duplicating it.
04
AI-assisted allocation
Optionally shift traffic toward winning variants while a test runs.
Statistical significance, in plain language
What the numbers on a test result actually mean.
- Lift
- How much better or worse the variant did than the control, such as +4% conversion rate.
- Confidence interval
- The range the true lift probably falls in. If the range includes zero, you haven’t proven a difference yet.
- Statistical significance
- A sign the difference is unlikely to be chance. It says nothing about whether the lift is big enough to matter.
- When to stop
- Decide the sample size before you start, and run for at least one or two full weekly cycles.
Multivariate testing vs. split testing
- Split test
- Two or more complete versions of an experience, with traffic divided between them.
- Multivariate testing
- Several elements changed at once, such as headline, image and offer, to find the best combination. Needs more traffic.
- Holdout
- A group that sees no personalization at all, used to measure the total value of personalizing.
What to test first
Good first tests for most ecommerce stores. Illustrative, not customer results.
Personalized homepage vs. default
The simplest way to measure the value of website personalization.
Recommendation strategy
Similar items vs. frequently bought together on the product page.
Recovery incentive
Free shipping vs. a percentage discount for high-risk carts.
Lift you can defend
We’ll add verified customer results here.
Metric to watch
Measured lift in revenue per visitor
The headline number, against a true control.
Metric to watch
Tests completed per quarter
How quickly your team learns what works.
Metric to watch
Share of experiences proven
How much of your personalization has evidence behind it.
Measured on your real orders
Results are based on orders from the native Shopify connector, not on modeled conversions.
All integrations- ShopifyNative Shopify connector for products, customers and orders. The data foundation for every prediction and personalized experience.Available
- Google Analytics 4Session and traffic-source context to target by acquisition channel.Available
Ecommerce A/B testing FAQ
What is A/B testing?
What is multivariate testing?
Keep exploring
- Ecommerce personalizationHow Skubl personalizes the whole store.
- Website personalizationAdapt the homepage, collections and landing pages to each shopper.
- Customer segmentation toolsReal-time segments built on predicted value and churn.
- Dynamic Yield alternativesCore capabilities without the enterprise implementation.
Know what’s working, and prove it
Connect your store to see holdout-based results on your store.
Prefer a walkthrough? Book a demo