How To Use Split Testing for Pricing Optimization: A Guide for Shopify Store Owners

In the competitive world of eCommerce, pricing can make or break your Shopify store. While great products, sleek design, and solid marketing are essential, the right price can dramatically influence conversions, revenue, and customer loyalty.

That’s where Split Testing for Pricing Optimization comes in.

If you’ve ever wondered whether pricing your product at $29.99 or $31.00 would make a difference, you're already thinking like a savvy eCommerce entrepreneur. In this comprehensive guide, we’ll walk you through everything you need to know about split testing (also called A/B testing) your prices to maximize conversions and profits—without losing your customer base.

What is Split Testing for Pricing Optimization?

Split testing for pricing optimization is a method where you present different pricing options to various segments of your audience and analyze which one performs better in terms of sales, revenue, or profit margin.

You’re essentially running a controlled experiment. Version A might offer your product at $25.00 while version B offers it at $29.99. After gathering sufficient data, you determine which pricing leads to better business outcomes.

Why Should Shopify Store Owners Use Split Testing?

Here’s why price split testing is critical:

• Price affects conversion rates: Even small changes can lead to significant sales variations.

• Different audiences respond differently: What works in the US might not work in the UK or India.

• Avoid guesswork: Data-backed decisions minimize risk and maximize returns.

✅ Stat to Consider: According to a study by Price Intelligently, even a 1% improvement in pricing can boost profits by 11.1% on average.

Benefits of Split Testing Your Prices

• Maximize profit margins

• Understand your customers’ willingness to pay

• Reduce cart abandonment

• Improve customer acquisition and lifetime value

• Avoid over-discounting

How to Set Up Split Testing for Pricing Optimization on Shopify

Let’s break this down step-by-step.

1. Define Your Pricing Goals

Before starting, ask:

• Do I want to increase conversions?

• Do I want to test pricing tiers for a new product?

• Am I focused on total revenue or per-transaction value?

Example: A DTC skincare brand might test if $35 vs $40 makes a difference in unit sales without hurting the profit margin.

2. Choose the Right Tools or Apps

Shopify does not have native support for price split testing, but you can use third-party apps and tools:

🔧 Recommended Tools:

• Intelligems (Shopify-specific for price A/B testing)

• Google Optimize (for experienced developers)

• Neat A/B Testing (for simpler tests)

• Optimizely (advanced solution for high-traffic stores)

Ensure whichever app you use can:

• Randomly segment traffic

• Track conversions by variant

• Offer reporting tools

3. Segment Your Audience

Split your Shopify traffic into test groups. For example:

• Group A sees the product at $29.99

• Group B sees it at $32.00

Ensure segmentation is random and consistent to avoid bias.

4. Run the Test Over a Sufficient Period

Your test should collect enough data to be statistically significant.

Best Practice:

• Duration: 2–4 weeks

• Minimum Sample Size: At least 1,000 visits per variant (adjust based on your average conversion rate)

📊 Example: If your store’s conversion rate is 2%, you’ll need ~5,000 visits per pricing group to draw meaningful conclusions.

5. Track Key Metrics

Keep a close eye on:

• Conversion Rate (CVR)

• Average Order Value (AOV)

• Revenue Per Visitor (RPV)

• Cart Abandonment Rate

• Bounce Rate

6. Analyze and Interpret the Data

Look beyond just sales volume. Sometimes, a higher price with slightly lower sales might yield more total profit.

Use metrics like:

• Revenue per user

• Gross margin comparisons

• Return customer rate

Example Insight: You might find that customers paying $40 are more likely to return and purchase again than those who paid $25 during a discount.

7. Implement Winning Price & Iterate

Once a clear winner emerges, update your pricing and monitor for a few weeks.

🧠 Pro Tip: Never assume it’s a one-and-done. Consumer behavior evolves—what works in Q1 may underperform in Q3. Always keep testing and iterating.

Real-World Examples of Split Testing for Pricing Optimization

1. Dollar Shave Club

They tested pricing bundles and found that a $1 starter kit increased customer acquisition by 30%, even if it meant a loss on the first order.

2. Apparel Store on Shopify

A clothing store ran a test between $49.99 and $59.99 for a new jacket. Even though fewer units sold at $59.99, total revenue increased by 14% and return rates dropped.

Tips for Global Shopify Stores

If you’re targeting customers worldwide, test pricing strategies by:

• Currency Localization: Prices like €29 vs €30 may perform differently in the EU.

• Psychological Pricing: In some markets, round numbers work better than charm pricing (e.g., $29.99).

• Cultural Sensitivity: Avoid pricing that might conflict with cultural or religious beliefs (e.g., pricing at $13 in some regions).

Actionable Tips to Improve Shopify Store Performance Using Pricing Split Tests

✅ Test Multiple Price Points

Don’t settle for one test—try a range like $25, $29.99, and $35.

✅ Bundle Testing

Try A/B testing product bundles vs individual product pricing.

✅ Subscription Pricing

Test between monthly vs quarterly billing or free trial vs discounted first month.

✅ Discount Strategy Testing

Experiment with "10% off" vs "Free Shipping" to see what resonates more.

✅ Track Mobile vs Desktop Behavior

Mobile users may react differently to prices than desktop users.

Common Mistakes to Avoid

• Running tests too short

• Not segmenting properly

• Ignoring statistical significance

• Focusing only on conversion rate, not profit

• Failing to retest after seasonal changes

SEO Tips for Product Pages During Pricing Tests

• Include keyword variations like “affordable,” “value,” “best price,” and “premium” in descriptions.

• Add price-related FAQs like “Why is this product priced at $X?” to reduce bounce rate.

• Use structured data (schema markup) to highlight dynamic pricing (where applicable).