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The Best A/B Testing & CRO Tools for Shopify in 2027
We compared Shopify fit, testing capabilities, analytics, ecommerce use cases, pricing, and real-world testing evidence.
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TL;DR
- Best for hypothesis prioritization: Signal Veritas. craftberry's proprietary CRO research tool for identifying and prioritizing conversion opportunities before you run A/B tests.
- Best for Shopify experimentation: Intelligems. It supports storefront, pricing, offer, shipping, and other ecommerce tests and is the platform behind craftberry's strongest first-hand testing evidence in 2026.
- Best native option: Shopify Rollouts. It provides built-in experimentation for supported Shopify theme, checkout, and customer account changes on Grow and higher plans.
- Best alternatives: Shoplift for Shopify-focused, low-flicker testing, VWO for experimentation and behavioral analytics, Kameleoon, AB Tasty, and Optimizely for larger enterprise programs.
- Best behavioral research layer: Microsoft Clarity. It helps identify customer friction and generate hypotheses but does not run A/B tests.
Our recommendation depends on the store, not the ranking alone. Done well, CRO can maximize the return from existing website traffic without additional marketing spend.
The right CRO stack depends on what you need to learn, what you need to test, your order volume, Shopify architecture, and your team's ability to implement winning changes.
If you need help with strategy, experimentation, and implementation, see our guide to the best Shopify CRO agencies.
What actually moves conversion on Shopify, based on our testing
- The quality of the hypothesis drives the value of the test. The strongest results in craftberry's client programs often came from changes to existing content, placement, or offer framing rather than new functionality.
- Testing needs enough volume to produce useful results. craftberry uses roughly 1,000 monthly orders as an internal qualification threshold for a structured A/B testing program. Below that level, research, UX, merchandising, and technical improvements often come first.
- Win rate is a program metric, not a universal benchmark. Across four client programs in 2026, craftberry recorded 26 winners, 5 losses, and 7 neutral results across 38 concluded tests.
- Shopify implementation affects what happens after the test. Theme architecture, Liquid, checkout extensibility, app conflicts, and performance can determine whether a winning variant can be shipped safely.
- A/B testing is one part of a CRO program. The effective workflow is: research → hypothesis generation → prioritization → run tests → analyze → implement → learn → repeat
How we evaluated these tools
As a consumer goods CRO agency, we evaluated each platform against the factors that matter when using conversion rate optimization tools and A/B testing for a Shopify or Shopify Plus store.
| Criterion | Weight | What we looked at |
|---|---|---|
| Shopify and Shopify Plus fit | 25% | How the tool integrates with Shopify, theme architecture, checkout extensibility, implementation requirements, and potential flicker or layout-shift issues |
| Testing and CRO capabilities | 25% | Whether the tool can identify opportunities, form hypotheses, run experiments, or support changes to content, layout, offers, shipping, themes, and other ecommerce variables, including multivariate testing where applicable |
| Statistical and reporting capabilities | 20% | How the tool measures test performance, supports statistical analysis, revenue and conversion metrics, and helps teams make decisions |
| Ecommerce business impact | 15% | Whether the tool supports metrics and use cases that matter to ecommerce teams, including conversion rate, AOV, revenue per visitor, profit, and merchandising |
| Cost and accessibility | 10% | Plan restrictions, testing limits, implementation requirements, accessibility for different store sizes, and learning curve |
| Evidence-quality | 5% | First-hand testing, documented client use, official product documentation, and other verifiable evidence |
Not every tool performs the same role in a CRO program.
Research and hypothesis-prioritization tools are evaluated for how effectively they identify and prioritize opportunities, while experimentation platforms are evaluated for their ability to run and measure controlled tests.
We do not treat a tool's inability to perform a function outside its intended category as a weakness.
How we applied the framework
We reviewed each tool's documentation, integrations, pricing, and published capabilities as of August 2026, evaluating them against practical Shopify ecommerce use cases and CRO requirements. All external sources reflect that same capture date.
Because capabilities, pricing, and integrations can change, this evaluation reflects the information available at the time of review. Where available, we supplemented vendor documentation with first-hand testing experience.
SignalVeritas appears first because it addresses the first steps in our CRO workflow: identifying and prioritizing what to test. The experimentation platforms that follow are ranked within the testing stage. This reflects each tool's role in the CRO workflow, not a claim that SignalVeritas is a better A/B testing platform.
Our strongest first-hand evidence among experimentation platforms is for Intelligems: in 2026, craftberry ran 38 concluded tests across four client accounts in live Shopify programs.
For other platforms, we distinguish between craftberry-tested and documented capabilities and do not claim first-hand experience where we have none.
How we define a CRO tool for Shopify
A Shopify CRO stack typically includes three layers: behavioral research, hypothesis prioritization, and experimentation.
- Behavioral research shows where customers encounter friction.
- Hypothesis prioritization determines which problems are worth addressing first.
- Experimentation tests whether a proposed change improves a measurable business outcome.
These layers solve different problems, so we do not treat them as interchangeable.
A tool does not need to run A/B tests to be a CRO tool. Its value can come from finding the right problem to test, prioritizing opportunities, or measuring customer behavior that informs the next experiment.
This guide lists SignalVeritas first because research, hypothesis generation and prioritization are the first steps in our CRO workflow.
We then rank experimentation platforms based on their Shopify fit, testing capabilities, measurement, ecommerce use cases, and evidence. Microsoft Clarity appears as a behavioral research tool because it helps surface the customer behavior that informs those hypotheses.
| Category | What it does | Examples |
|---|---|---|
| A/B testing | Runs controlled experiments | Intelligems, Rollouts, Shoplift |
| Behavioral research | Identifies friction through behavioral analytics | Clarity |
| Hypothesis prioritization | Turns data-driven insights into prioritized hypotheses | SignalVeritas |
Why the distinction matters for Shopify
Generic “best CRO software” lists often group experimentation, behavioral research, and hypothesis-prioritization tools together, even though they solve different problems. That makes comparison difficult for ecommerce teams.
For Shopify, you need to answer more specific questions:
Can the tool test PDP and theme changes without creating implementation issues?
Mobile-menu rebuilds tested through Intelligems have won on four separate accounts, including an 11.68% conversion lift on Enhance Auto.
“craftberry helped us build the website we always wanted. We have been working with them for about six months, and we are extremely pleased with the entire team. He and the whole team helped us refine our previous site while incorporating unique, fully integrated features connected to our ERP.”
Anton Stoichkov, Enhance Auto (Verified review, Google)
Can it test pricing, offers, or shipping thresholds?
On Shelly, offer framing alone (bundle labels, no price change) lifted conversion 11% and revenue per visitor 8%. On Moon Nude, a homepage bundle test lifted conversion 14.0% and revenue per visitor 17.1%.
Does it work with Shopify Plus and checkout extensibility?
On Enhance Auto we tested shipping costs and social proof directly on the checkout. It lost and we killed it, which is the point: the tool has to be able to run that test in the first place.
On Takomo, we added Microsoft Clarity as an approved pixel through the same checkout extensibility, to see checkout behavior directly at scale. Mobile carried most of Takomo's checkout traffic, and closing the mobile-to-desktop conversion gap was one of the opportunities the resulting data surfaced
Can your team connect test results to revenue, average order value, and other ecommerce metrics?
On Mi Amante, the product-page quantity-ladder test lifted conversion 11.1% and revenue per visitor 13.8%.
Can a winning variant be implemented safely in the production Shopify environment?
This is an implementation question as much as a tool question. On Pepper the product team ships an average feature release every 5 days without destabilizing the storefront.
The right CRO stack depends on what you need to learn, what you need to test, and how you implement the result.
Does Shopify have native A/B testing?
Yes. Shopify offers native A/B testing through Rollouts. Launched in 2026, Rollouts lets merchants experiment with supported theme, checkout, and customer account changes directly in Shopify admin. Experiments are available on the Grow plan and above.
Rollouts lets merchants:
- Compare a control with a treatment
- Allocate traffic to the treatment
- Review available experiment metrics without adding a third-party testing platform.
However, Rollouts is a native experimentation layer, not a full CRO platform.
What Shopify Rollouts can test
Rollouts supports experiments involving:
- Theme configurations and content
- Entire theme replacements
- Checkout and customer account configurations
- Localized theme content by market.
There are implementation limits. Liquid template changes are not supported as part of a rollout, and rollouts cannot be applied to vintage themes.
Where Rollouts falls short
Rollouts is focused on supported Shopify resources rather than broader ecommerce experimentation. It does not provide dedicated testing for:
- Pricing and pricing strategy
- Discounts and offers
- Advanced audience targeting, user segments, and personalization
- Cross-platform experimentation
Its available metrics also depend on the rollout type: theme experiments report conversion rate, bounce rate, and add-to-cart rate, while checkout experiments report only checkout conversion rate.
Neither reports statistical significance or revenue per visitor, and merchants cannot customize the metrics Shopify provides.
When should you use Rollouts?
Use Rollouts when your experiments fit Shopify's supported resources and you want native implementation without another testing platform.
Consider a dedicated CRO platform once your program needs pricing or offer testing, advanced targeting, broader experimentation capabilities, or a more flexible testing and analysis workflow.
The best A/B testing and CRO tools for Shopify in 2027
We evaluated each platform for Shopify compatibility, testing and CRO capabilities, measurement, ecommerce use cases, and available evidence, drawing on vendor documentation, our own testing experience, and recorded client test results where available.
Because these tools serve different roles, the ranking starts with the CRO research layer and then moves into experimentation and behavioral research.
1. SignalVeritas
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SignalVeritas helps Shopify brands find the CRO opportunities most likely to move revenue, without wasting weeks testing ideas based on guesswork.
Each hypothesis links back to the specific sessions, reviews, or data points it was drawn from.
It combines up to eight research sources per store, including analytics, session recordings, heatmaps, on-site polls, customer surveys, review mining, support chat, and email analysis.
It turns those signals into ranked, evidence-cited hypotheses, so your CRO team can prioritize tests based on observed customer behavior rather than a generic list of CRO best practices.
The workflow:
SignalVeritas supports the research and prioritization stage of the CRO process:
- It does not modify your Shopify storefront or run experiments automatically.
- It produces a prioritized test plan that your team or craftberry can implement and test.
craftberry use case
For Mi Amante, SignalVeritas turned Clarity session data and other research signals into a prioritized backlog of testable hypotheses. Those hypotheses then fed the A/B testing program run through Intelligems.
Best for: Shopify brands that need to identify, prioritize, and validate CRO opportunities before deciding what to test.
Limitations: Signal Veritas does not run experiments or implement changes automatically. Its purpose is to validate ideas with evidence and turn them into prioritized recommendations for the broader CRO workflow.
2. Intelligems: best for testing price, offers, and storefront changes
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Intelligems is a Shopify-focused experimentation platform for content, merchandising, pricing, shipping, checkout, and post-purchase testing. Its key advantage is testing commercial variables such as prices, offers, discounts, and shipping thresholds alongside storefront changes.
We have first-hand testing experience with this platform. We ran 38 concluded tests on it across four client accounts in 2026; the full account-by-account results, losses included, are further down this guide.
craftberry use case
On Carista, a subscription landing page redesign tested through Intelligems increased conversion 55% and revenue per visitor 42%.
Best for: Shopify and Shopify Plus brands that need to test pricing, offers, shipping, merchandising, and storefront changes in one experimentation platform.
Limitations: Price testing has additional requirements around themes, currencies, subscriptions, and page builders.
3. Shopify Rollouts: best for native Shopify experimentation
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Shopify Rollouts is Shopify's native solution for testing theme, checkout, and customer account configuration changes.
Experiments are available on Grow and higher plans and require no third-party testing app.
Its main advantage is native Shopify implementation. Its scope is narrower than dedicated CRO platforms and focuses on supported Shopify resources rather than broader pricing, targeting, or cross-platform experimentation.
Best for: Shopify merchants that want to run native experiments on supported theme, checkout, and customer account changes without a third-party testing platform.
Limitations: Rollouts has a narrower testing scope than dedicated CRO platforms. It does not support Liquid changes, pricing or offer testing, advanced targeting, or cross-platform experiments, and its available metrics vary by rollout type.
4. Shoplift: best for native, low-flicker Shopify testing
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Shoplift is a Shopify-native testing platform for themes and templates. It supports page, theme, and price experiments and uses an anti-flicker approach designed to prevent visible variant swaps.
Best for: Shopify and Shopify Plus brands that need native theme and storefront testing with low-flicker implementation.
Limitations: Price and offer testing is a secondary capability here, not the platform's core focus. For complex, multi-variable price experiments, a platform built specifically for commercial testing may be a better fit.
5. VWO: best for experimentation and behavioral research
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VWO (Visual Website Optimizer) combines A/B and multivariate testing with behavioral research through a no-code visual editor, including heatmaps, recordings, funnels, and targeting.
Unlike Shopify-native tools, it is designed for cross-platform experimentation.
Best for: Brands that want to combine A/B testing with behavioral research, targeting, and experimentation across digital properties.
Limitations: Its broader scope means a less Shopify-specific workflow.
6. Convert Experiences: best for cross-property experimentation
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Convert Experiences is a cross-platform experimentation tool for brands testing across multiple websites or digital properties.
Best for: Businesses that need to run experimentation across multiple websites or digital properties, including Shopify.
Limitations: Shopify-focused platforms may be simpler if most testing happens inside the store.
7. Kameleoon: best for enterprise experimentation
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Kameleoon combines experimentation with advanced audience segmentation, personalization, and web and server-side testing for enterprise teams.
Best for: Enterprise Shopify Plus teams that need experimentation, advanced segmentation, personalization, and server-side testing, and strict data governance.
Limitations: Its enterprise scope can add unnecessary complexity for smaller teams.
8. AB Tasty: best for experimentation and personalization
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AB Tasty combines A/B testing with personalization and feature management for mature experimentation programs.
Best for: Enterprise and marketing teams that want to combine experimentation, personalization, and feature management at scale.
Limitations: Its broader enterprise capabilities may be unnecessary for basic Shopify testing.
9. Optimizely: best for full-stack experimentation
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Optimizely supports web, product, and server-side experimentation, making it relevant when testing extends beyond the Shopify storefront.
Best for: Shopify Plus organizations with engineering teams that need web, product, and server-side experimentation beyond the storefront.
Limitations: It can provide more infrastructure than a Shopify-only CRO program requires.
10. Microsoft Clarity: best behavioral research layer
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Microsoft Clarity is not an A/B testing platform. We include it because behavioral research helps identify friction and generate the insights you turn into testable hypotheses.
Session recordings, scroll maps, heatmaps, and user interaction signals show you problems a dashboard alone would miss.
Best for: Shopify stores that need behavioral analytics to identify customer friction and generate hypotheses for CRO testing.
Limitations: No experimentation engine, so no statistical significance, conversion rate, or revenue reporting. It surfaces friction and behavior, not test results, so your team still has to turn what it shows into a testable hypothesis and run that through a testing platform.
Shopify CRO Tool Comparison
| Tool | Shopify fit | Pricing & offer testing | Best for |
|---|---|---|---|
| Signal Veritas | Shopify-compatible | No | Hypothesis prioritization (does not run tests) |
| Intelligems | Shopify-focused | Yes | Pricing, offers, shipping, storefront |
| Shopify Rollouts | Native | No | Theme, checkout, account changes |
| Shoplift | Shopify-focused | Yes, higher tiers | Low-flicker theme, storefront, price testing |
| VWO | Cross-platform | Limited | A/B testing + behavioral research |
| Convert | Cross-platform | Limited | Cross-property experimentation |
| Kameleoon | Cross-platform | Limited | Enterprise experimentation + personalization |
| AB Tasty | Cross-platform | Limited | Enterprise experimentation + personalization |
| Optimizely | Cross-platform | Limited | Full-stack experimentation |
| Microsoft Clarity | Shopify-compatible | No | Behavioral research + hypothesis generation |
What moves conversion from our experience, by tool and test
Test results depend on the hypothesis, the testing platform, and how the winning change is implemented.
Across craftberry client programs, some of the strongest results have come from changing how existing information is presented rather than adding new functionality:
craftberry use case
On Mi Amante, the existing upsell sat at a high-intent stage of the customer journey, where visitors were already considering a product, but it was not contributing as effectively as it could to the purchase experience.
We tested a revised version against the original using live store traffic.
The variant increased conversion rate by 11.1% and revenue per visitor by 13.8%
craftberry use case
On Moon Nude, we tested whether featuring bundles directly on the home page, rather than only on product pages, would frame a larger purchase as a natural option before customers narrowed their attention to a single item.
The variant increased conversion by 14.0% and revenue per visitor by 17.1% - one of the strongest lifts across the account's tests that year.
The common factor was a specific hypothesis based on customer behavior, tested against a measurable outcome.
craftberry's 2026 testing record, by account
| Account | Winners | Losers | Neutral | Win rate |
|---|---|---|---|---|
| Mi Amante | 4 | 0 | 1 | 80% |
| Enhance Auto | 6 | 2 | 0 | 75% |
| Carista | 8 | 2 | 1 | 73% |
| Moon Nude | 8 | 1 | 5 | ~56% |
| Combined | 26 | 5 | 7 | 68% |
26 of 38 tests produced a winning result, giving a 68% winner share across all concluded tests. Excluding neutral tests, the win rate was 84%.
Results varied substantially by account, from ~56% at Moon Nude to 80% at Mi Amante.
Both programs used Intelligems, so the variation cannot be attributed to the testing platform alone. It reflects differences in the stores, hypotheses tested, traffic, customer behavior, and stage of each CRO program.
Win rate is useful context, but it is not a standalone measure of CRO performance. Not all tests are winners, which is why we stop the losing ones early rather than let them run to prove a point. A mature program may test smaller or more uncertain opportunities after higher-confidence changes have already been implemented.
The more useful question is whether testing consistently identifies changes that improve measurable revenue growth, conversion rate, and revenue per visitor.
When we recommend paying for a CRO tool based on traffic
There is no universal traffic threshold for A/B testing. The sample size you need depends on your baseline conversion rate, expected uplift, traffic allocation, and the metric you are measuring. Lower traffic generally means longer test cycles or larger effects needed to reach a reliable result.
At craftberry, we use roughly 1,000 monthly orders as an internal qualification threshold before recommending a structured A/B testing program. It is a practical benchmark for deciding whether a store has enough traffic volume to run tests at a useful pace.
Below that level, we often prioritize customer research, UX improvements, merchandising, and technical fixes before adding a paid testing platform.
These changes can address clear sources of friction without waiting for an experiment to reach a reliable result.
We also generally recommend waiting 1.5 to 2 months after a launch or major redesign before starting structured testing.
This gives the store time to accumulate post-launch behavioral data and allows the team to identify real friction points rather than testing assumptions created by the previous experience.
When we recommend strategy over another CRO tool
A/B testing can validate a solution to a conversion problem. It cannot replace diagnosing the problem itself.
If a 6,000-SKU catalog has poor filtering, an app conflict is breaking checkout, or third-party scripts are slowing the PDP, testing a button or headline will not address the underlying constraint.
This matters especially for larger Shopify stores. A navigation or filtering issue can affect product discovery across the entire catalog, while a checkout conflict can affect every transaction. These problems require traffic analysis, behavioral research, technical analysis, and Shopify expertise before you decide whether an A/B test is the right intervention.
The same applies after a test produces a winner. The winning variant still needs to be implemented safely in the production storefront and monitored after launch.
On Shopify Plus, that can mean updating Liquid and theme logic, checking app interactions, validating checkout behavior, and making sure the change does not break Google Analytics or other tracking.
The practical takeaway is simple: use A/B testing to validate high-value hypotheses, not as a substitute for CRO research, UX analysis, or Shopify development.
When we recommend working with a CRO team
An A/B testing platform is useful when you have a clear hypothesis, enough traffic to test it, and the resources to act on the result.
Consider bringing in a Shopify CRO agency when:
- The problem is structural. Navigation, filtering, checkout, site speed, or information architecture may require a broader solution than an isolated A/B test.
- You have a winner but cannot safely ship it. Implementing a winning variant may require theme development, Liquid changes, app troubleshooting, checkout work, or tracking validation.
- Your store does not have enough testing volume yet. If you are below roughly 1,000 monthly orders, research, UX improvements, merchandising, and technical fixes may create more value before you invest in a formal testing program.
- You need the full experimentation workflow instead of juggling multiple tools. A team can connect research to testing, build variants, interpret commercial impact, and implement validated changes across your existing tech stack.
- Testing has become an ongoing growth function. At higher testing volumes, the challenge shifts from running individual experiments to maintaining a consistent pipeline of research, hypotheses, experiments, implementation, and measurement.
How craftberry approaches CRO
craftberry runs CRO as an outcome-focused service, not a standalone testing engagement. We own the full cycle in-house, from research and hypothesis development through UX and design, development, testing, and implementation.
Our commercial model is tied to measurable impact: we target at least 4x the client's investment in added revenue. If that target is not met, we continue working at no extra cost.
The right setup depends on where your current constraint sits. Sometimes that is testing software. Sometimes it is the research, strategy, or Shopify engineering required to turn a test result into a measurable business improvement.
FAQ
Does Shopify have a built-in A/B testing tool?
Yes. Shopify Rollouts lets merchants on the Grow plan or higher run experiments that compare a control with a treatment across supported theme, checkout, and customer account changes.
Rollouts is useful for native Shopify experimentation, but its testing and analytics scope is narrower than dedicated CRO platforms. Shopify also does not let you customize the metrics available for a rollout.
What is the best free CRO tool for Shopify?
There is no single best CRO tool for every Shopify store. The right CRO stack depends on what you need to learn, what you need to test, your order volume, Shopify architecture, and your team's ability to implement winning changes.
For specific needs, we recommend:
- Signal Veritas for identifying and prioritizing CRO opportunities.
- Microsoft Clarity for behavioral research and finding customer friction.
- Intelligems for testing pricing, offers, shipping, and storefront changes.
- Shopify Rollouts for native Shopify theme, checkout, and customer account experiments.
- Shoplift for Shopify-focused, low-flicker testing.
- VWO for experimentation combined with behavioral research.
- Kameleoon, AB Tasty, and Optimizely for larger enterprise experimentation programs.
If you need a free starting point, Microsoft Clarity can surface behavioral insights through session recordings, heatmaps, and scroll maps. Signal Veritas is better suited to turning research signals into prioritized CRO opportunities before you invest resources in experimentation.
How much traffic do I need before A/B testing is worth it?
There is no universal traffic threshold. Required sample size depends on factors such as baseline conversion rate, expected effect size, traffic allocation, and the metric you are testing.
At craftberry, we use roughly 1,000 monthly orders as an internal qualification threshold before recommending a structured A/B testing program. Below that level, research, UX, merchandising, and technical improvements may produce more value than running formal tests at a low cadence.
Can I test product pricing on Shopify?
Yes, but the available options depend on how you want to run the experiment.
Shopify Rollouts does not test product pricing, while Shopify's Smart Pricing currently offers A/B pricing experiments in early access to eligible stores.
Dedicated Shopify experimentation platforms such as Intelligems also support price testing, including product, subscription, and multi-currency pricing.
Do A/B testing apps slow down my Shopify store?
They can, depending on how the platform delivers test variations.
Client-side testing swaps the variation in on the same page after the initial render, which is what causes visible flicker. Other platforms use theme-level, server-side, or split-URL testing, sending traffic to a separate page instead, to reduce this risk.
For example, Shoplift says its theme-level rendering prevents visitors from seeing the original experience before the test variation loads.
What is the difference between a CRO tool and a CRO agency?
A CRO tool helps you analyze user behavior, run experiments, or measure results.
An ecommerce conversion rate optimization agency decides what to test, why it matters, how to implement the variant, and what to do with the result.
On Shopify, that can also involve theme development, app troubleshooting, checkout work, analytics validation, and safely shipping the winning change into production.
Which tool does craftberry use for client testing?
craftberry uses Signal Veritas to identify and prioritize CRO opportunities, then runs experiments through Intelligems in client Shopify programs. This connects research and hypothesis generation directly to testing and implementation.
In 2026, craftberry ran 38 concluded Intelligems tests across four client accounts: 26 winners, 5 losses, and 7 neutral results. That represents a 68% overall winner share, or 84% when neutral results are excluded. These are craftberry's own client-program results, not an industry benchmark.
Want to know which of these tools fits your store's traffic, catalog, and Shopify setup?
Share your monthly order volume, current testing setup, and Shopify plan.
As an ecommerce conversion rate optimisation agency, craftberry can help you determine whether you need a dedicated testing platform, which tool fits your use case, or whether Shopify Rollouts is enough for now.
At craftberry, we own the full CRO cycle in-house, from research and hypothesis generation to testing and implementation. Our team handles the UX, design, development, tracking, and analysis needed to safely ship and measure winning changes.
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Preslav Nikov is the Founder and CEO of craftberry, Shopify Premier agency. A developer turned enterprise strategist, he has guided 800+ successful digital storefront launches and migrations since 2015, driving over $450M in client sales. Recognized by Forbes 30 Under 30, his frameworks power global leaders like vivo, Shelly Group, Pepper, and Midi Health. Find Preslav on LinkedIn to stay connected.
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