BigCommerce doesn't have native A/B testing. To run controlled experiments on your BigCommerce store, you need a third-party testing tool installed via JavaScript. This guide walks through how to set up A/B testing on BigCommerce, what to test for maximum impact, the platform-specific limitations you'll encounter, and which tools work best for different team setups.
BigCommerce's native capabilities for conversion optimization are limited to:
- Promotions and discount codes: You can create conditional promotions but can't test them in a controlled experiment natively
- Page Builder: Drag-and-drop content editor for creating page variations, but not for testing them against each other
- Analytics integration: Native Google Analytics integration and a built-in analytics dashboard, but no experiment layer
For actual A/B testing β where traffic is randomly split between a control and variant, and results are measured with statistical significance β you need an external tool.
How to Set Up A/B Testing on BigCommerce
For BigCommerce, these tools install cleanly:
VWO: Install via JavaScript snippet in BigCommerce's Script Manager. Supports visual editor, code editor, and heatmaps. Good for teams that want behavioral analytics alongside testing.
Convert: Privacy-first alternative. Install via Script Manager. Supports visual and code variants. Unlimited tests on higher plans. Good for agencies and privacy-sensitive brands.
Optimizely: Enterprise option with full-stack testing. Higher implementation complexity and cost.
Google Optimize: Discontinued in September 2023. Not available.
Step 2: Install the Tracking Snippet
- Log in to BigCommerce admin
- Navigate to Storefront β Script Manager
- Click "Create a Script"
- Name: [Tool Name] Testing Script
- Location: Head
- Script Category: Analytics
- Paste your testing tool's JavaScript snippet
- Save and apply to all pages
Verify installation using your testing tool's debugger (most offer a browser extension or debug panel).
BigCommerce checkout fires standard ecommerce events, but you need to confirm your testing tool captures them. The key events to track:
Purchase (primary): Fires on the order confirmation page. In BigCommerce, this is typically /order-confirmation or a similar URL. Configure your testing tool to track purchases when this URL loads.
Add to Cart: BigCommerce fires a cart addition when the Add to Cart button is clicked. This can be tracked via a JavaScript event listener or via BigCommerce's Stencil event system.
Checkout Initiated: Fires when a user navigates to /checkout. Configure as a secondary conversion goal.
Step 4: QA Your Setup
Before launching any test:
- Browse your store with the testing tool's debug mode on
- Add a product to cart and confirm the event fires
- Complete a test transaction (or use your testing tool's conversion simulation)
- Verify that your test is splitting traffic correctly (equal distribution between control and variant)
Step 5: Launch Your First Test
Start with a high-traffic, high-impact element:
- Product page headline or hero copy
- CTA button text ("Add to Cart" vs. "Buy Now" vs. "Get Yours Today")
- Product page image order
- Trust signals placement (reviews, certifications, guarantees)
Keep your first test simple: one change, one primary metric, run for 2β4 weeks minimum.
What to Test on BigCommerce
Product Detail Pages (Highest Priority)
The PDP is where buying decisions are made. High-impact tests:
Headline and product name framing: "Premium Stainless Steel Water Bottle" vs. "Stay Hydrated All Day β 24-Hour Insulation" β benefit-led vs. feature-led copy.
Image order: Hero product shot first vs. lifestyle shot first. Lifestyle images often convert better for fashion and home categories; product detail shots win for technical/functional categories.
Price anchoring: Showing MSRP crossed out vs. not. Showing per-unit price for bundles vs. total. Testing these is particularly valuable for Indian D2C brands where price sensitivity is high.
Reviews placement: Reviews at the top of the page vs. below the fold vs. highlighted in a sticky sidebar.
Scarcity and urgency signals: "Only 8 left in stock" vs. no stock indicator. "Order within 3 hours for same-day dispatch" vs. generic shipping messaging.
Category Pages
Filter interface: Sidebar filters vs. top filter bar. Mobile users often engage more with collapsed, expandable filters than sidebars that take up half the screen.
Product card layout: 2-column vs. 3-column grid on mobile. Image size ratio. Whether to show price prominently or less so.
Sort order default: "Most Popular" vs. "New Arrivals" vs. "Best Rated" as the default sort often changes conversion significantly.
Homepage
Hero banner: Headline, subheadline, CTA text, and image all affect homepage click-through to product pages. Test one element at a time.
Category featured: Which product category do you feature prominently? Test which category driver produces the most downstream conversions.
Trust signals above the fold: Showing "10,000+ happy customers" or delivery promise in the hero section vs. further down.
Checkout
BigCommerce's checkout is partially locked down β some changes require the BigCommerce Checkout SDK or developer involvement. What's typically testable:
- Checkout page headline text
- Order summary formatting
- Trust badge placement
- Progress indicator style (steps vs. percentage vs. none)
Full checkout redesigns typically require BigCommerce's custom checkout solution (available on higher plans) and developer involvement.
BigCommerce-Specific A/B Testing Limitations
Checkout restrictions: BigCommerce's standard checkout has limited customization without the Optimized One-Page Checkout or custom checkout API. You can't freely restructure the checkout layout without a developer.
Theme-level limitations: Unlike Shopify, BigCommerce doesn't have a visual theme editor with sectioned layouts. Testing structural layout changes often requires code-level variant building.
Script conflicts: BigCommerce stores often have multiple third-party scripts (analytics, chat, reviews, etc.). Heavy script loads can slow page rendering and cause testing tools to flicker (showing the original page momentarily before the variant loads). Minimize script conflicts by checking load order in Script Manager.
Stencil theme architecture: BigCommerce uses the Stencil theme framework. A/B testing variants built in a visual editor may not perfectly respect Stencil's template inheritance, especially for complex layout changes. Developers familiar with Stencil are recommended for non-trivial structural tests.
Sample Size and Timing on BigCommerce
Use a sample size calculator before starting tests:
- Current conversion rate on the page you're testing: e.g., 2.5%
- Minimum detectable effect: e.g., 0.5% improvement (bringing CVR to 3.0%)
- Statistical confidence: 95%
For this example, you need approximately 6,800 visitors per variant (13,600 total) to detect a 0.5% improvement reliably.
If your product page gets 500 sessions per week, this test needs 27 weeks to conclude. This is why low-traffic page tests are rarely worth running β start with your highest-traffic pages.
| Tool | Best For | Price | Setup Complexity |
|---|
| VWO | Mid-market, needs behavioral analytics | $199+/mo | Medium |
| Convert | Privacy-focused, agency use | $99+/mo | Medium |
| Optimizely | Enterprise programs | $1,500+/mo | High |
| AB Tasty | Enterprise, personalization | $800+/mo | High |
| Hotjar (analytics only) | Behavioral research only | $32+/mo | Low |
For BigCommerce brands looking for a combined A/B testing and personalization solution at accessible price points, VWO or Convert are the most practical starting points.
Note on CustomFit.ai: CustomFit.ai is currently purpose-built for Shopify. If you're evaluating a platform migration from BigCommerce to Shopify, CustomFit.ai's Shopify-native no-code testing is a strong argument for the migration.
Tips and Best Practices for BigCommerce CRO
- Start with behavioral research. Before testing, use a heatmap tool (Hotjar, Microsoft Clarity) to identify where visitors are clicking, scrolling, and exiting. This ensures your hypotheses are data-backed.
- Test one change at a time. BigCommerce's page architecture makes it tempting to test multiple changes at once. Don't. You won't know which change drove the result.
- Plan for Stencil compatibility. Before building a complex variant in a visual editor, have your developer verify the test won't break Stencil's template rendering.
- Set up custom events for BigCommerce-specific actions. ATC events in BigCommerce can behave differently than standard JavaScript events depending on how your theme is built. Verify with your developer that events fire correctly for your specific implementation.
- Monitor performance impact. Testing scripts add JavaScript load to every page. Run a Lighthouse performance audit before and after installing your testing tool; address any significant regressions.
Key Takeaways
- BigCommerce has no native A/B testing β a third-party tool installed via Script Manager is required
- VWO and Convert are the most practical testing tools for BigCommerce at mid-market price points
- Product detail pages, category pages, and homepage elements are the highest-impact testing areas
- BigCommerce's checkout has limited customization for testing without developer involvement and higher-tier plan access
- Always calculate required sample size before starting; many BigCommerce stores have limited traffic that makes low-impact tests infeasible within a reasonable timeframe
- Behavioral research (heatmaps, session recordings) should precede experimentation to build a hypothesis backlog
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