Proven Shopify A/B Tests You Can Learn From
Exposed Search Bar on Desktop
Could you improve Conversion Rates by exposing the Search Bar on Desktop?
Words with Icons in Navigation
Could Adding Words to Icons in the Mobile Nav Improve Conversion Rate?
Optimise USP Section on the Home Page
Does Moving USPs Higher on the Homepage Improve Conversion Rate?
66.18% Increase in Revenue per Visitor
Express Checkout buttons are often a CRO essential. Yet dropping them in this experiment cleared the path and unlocked a surprising jump in revenue per visitor.
32% Increase in Subscription Orders per Visitor
Adding a clear bullet-list of subscription perks nudged hesitant shoppers, lifting subscription orders per visit on desktop and 15% on mobile.
30.33% Increase in Conversion Rate
Placing a “No Reaction Money Back Guarantee” below the Add to Cart button drove trust and measurable uplifts in conversion for this wellness brand.
22% Increase in Conversion Rate
Find out how exposing the mobile search bar improved product discoverability and drove measurable uplifts in user engagement for this DTC casket brand.
19.71% Increase in Checkout Visits
User Testing unveiled an interesting, previously unseen, friction point in the User Journey. A small change to filtering options led to a quicker path to purchase.
14.81% Increase in Conversion Rate
Adding “Popular” badges to subscription options nudged users toward Autoship and improved conversion, proving social proof outperforms brand recommendation when it comes to retention-focused PDP design.
32% Increase in Conversion Rate for Desktop Devices
A full PDP redesign helped users find the info they needed faster, leading to more confident purchases, especially on desktop, where conversion rate jumped by over 30%.
17.76% Increase in Revenue per Visitor
A subtle shift in how price was framed had a major impact. By highlighting cost per capsule, Blend helped users make faster decisions, leading to higher conversions, and more subscribers.
24% Increase in Conversion Rate
Find out how replacing tabbed options with open radio buttons improved clarity, reduced friction, and drove measurable uplifts in revenue for this DTC brand.
The Blend CRO Lens
How do you run A/B tests on Shopify?
A/B testing on Shopify involves showing two versions of a page, element, or feature to different segments of your visitors at the same time. We use Intelligems to split traffic accurately, track performance, and measure statistically significant differences in conversion rate, AOV, revenue per user, and other key metrics.
Every test follows a clear process:
- Analyse data to identify a problem
- Create a hypothesis
- Design the variant (UI, UX, copy, layout, pricing, etc.)
- Code and QA the test
- Split traffic accurately
- Run until statistical significance
- Review results, insights, and recommendations
When a test wins, we help you publish the variant to your live theme quickly and safely.
What makes a good A/B test hypothesis?
A strong hypothesis clearly states what you’re changing, who it affects, and what outcome you expect based on data.
For example:
“Because users aren’t seeing product benefits above the fold on PDPs, adding a benefit bar will help visitors understand value faster and increase add-to-cart rate.”
Good hypotheses come from real behavioural data, not guesswork and they connect the opportunity to a measurable outcome.
How long should a Shopify A/B test run?
Most Shopify tests run for 2–4 weeks, depending on traffic volume, seasonality, and how quickly each variant collects enough conversions.
We always run tests until they reach statistical significance, not just a fixed number of days.
If significance isn’t reached in two weeks, we extend the test.
If one variant is consistently leading and the data is strong, we may call a winner earlier.
We avoid running tests during major promotional periods (like BFCM), because spikes in traffic and buyer intent can distort the results.
What's the best A/B testing tool for Shopify?
Intelligems is our preferred A/B testing platform for Shopify because it’s accurate, fast, and built specifically for testing things like pricing, free shipping thresholds, subscriptions, and revenue-based metrics. It also integrates seamlessly with Shopify, which keeps the testing experience stable and reliable.
That said, several tools work well depending on what you want to test:
- Intelligems → best for pricing, thresholds, subscriptions, and revenue-driven Shopify tests
- Convert → solid for UX and design tests
- Shoplift → Shopify-native and quick to deploy UI experiments
- Omniconvert → strong for surveys, segmentation, and personalisation
- VWO (Visual Website Optimizer) → flexible enterprise-level testing
Do A/B tests work with low traffic.
A/B tests need a minimum level of traffic and conversions to reach statistical significance. The exact requirement depends on what you’re testing, but as a general guideline, most agencies recommend at least 50,000 monthly visitors before running reliable A/B tests.
Below this threshold, tests can take too long to run or fail to reach significance, meaning the results may not be trustworthy.
If your store is under the recommended traffic level, we typically shift to other data-driven optimisation methods, such as:
- User testing
- Heatmap and behavioural analysis
- Heuristic CRO reviews
- Iterative UX improvements without split testing
These approaches still uncover meaningful opportunities to improve conversion, even when full A/B testing isn’t feasible.
What metrics should I track during A/B testing?
Metrics depend on what the test is designed to improve. Common primary metrics include:
- eCommerce conversion rate
- Average order value (AOV)
- Revenue per visitor
- Subscription rate (if applicable)
- We also track supporting metrics like:
- Add to cart rate
- Bounce rate
- PDP visits
- Filter usag
- Interaction rates
This gives a full picture of why a variant won, not just whether it won.