Did you know there’s a price your customers secretly prefer, and it may not be the one you’re currently charging?

According to eMarketer, nearly 48% of online shoppers abandon their carts at checkout because extra costs like high shipping fees, taxes, or unexpected charges  are too high. This shows how sensitive buyers are to pricing and how easily an untested price point can push them away.

Split testing for pricing is what helps to uncover that hidden sweet spot, letting real customer behavior, not guesses, dictate your most profitable price. When done right, even a small adjustment can drastically increase revenue without losing conversions.

What Is Split Testing for Pricing?

Split testing for pricing, also known as A/B pricing testing, involves showing different price points to separate groups of visitors to identify which generates the most revenue, conversions, or profit.

Unlike simple discounts or intuition-based pricing, this approach relies on data-backed experimentation. It allows brands to:

• Identify the price that maximizes revenue per visitor (RPV)
• Understand how pricing affects purchase decisions
• Reduce guesswork and optimize profit without turning away customers

Pricing is the single most effective profit lever for retailers, more impactful than cutting costs or increasing volume. 

How to Run Split Tests for Pricing (Step-by-Step)

A successful pricing test isn’t about adding random numbers. It’s a structured process that requires careful planning and analysis. Here’s a deep dive into each step:

1. Define Your Goal Clearly

Before testing, decide what “success” looks like. Are you optimizing for:

• Revenue per visitor (RPV) – total revenue divided by traffic
• Conversion rate – percentage of visitors who buy
• Average order value (AOV) – how much each customer spends

Focusing on one metric keeps your experiment clean and ensures actionable insights. For example, increasing conversions alone might reduce revenue if the price is too low. Tracking RPV ensures you balance both sales and profit.

2. Formulate a Pricing Hypothesis

Every test starts with a hypothesis. Think of it as a question your experiment will answer. Examples include:

• “Raising the price by 5% will increase total revenue without hurting conversions.”
• “Customers respond better to $29.99 than $30 because of psychological pricing.”
• “Bundling two products at $49 will increase revenue compared to selling separately.”

Hypotheses give your test structure and prevent you from misinterpreting results.

3. Select Price Variations Thoughtfully

Pick variations that are meaningful but not extreme. Consider:

• Small percentage changes like ±5–10%
• Rounded vs psychological pricing (e.g., $30 vs $29.99)
• Bundled pricing or tiered plans

Each variation should test a specific aspect of pricing psychology. Extreme changes can distort results or confuse customers.

4. Split Your Traffic Properly

Ensure each price variant is shown to an equal portion of your audience. Unequal distribution can bias results and invalidate conclusions.  Run your test until you reach 95% statistical confidence to ensure results aren’t due to random chance.

5. Monitor for Sufficient Time and Sample Size

Early spikes in data are misleading. Run tests long enough to capture a full purchasing cycle and a meaningful sample size. Use these benchmarks:

• Minimum of 2 weeks
• 1,000+ visitors per price variation
• Account for day-of-week and seasonal effects

This ensures your insights reflect real customer behavior, not temporary anomalies.

6. Analyze the Right Metrics

Revenue per visitor (RPV) is your gold standard, not just conversions. A lower price might increase sales but reduce total revenue. Track:

• RPV: Revenue ÷ Visitors
• AOV: Average order value
• Profit margin: Ensure gains aren’t eroded by costs

Segment results by traffic source, device, and returning vs new customers. This uncovers hidden insights, like whether mobile buyers respond differently from desktop users.

7. Implement the Winning Price Gradually

Don’t roll out all winning tweaks to all customers at once. Instead:

• Start with one category or segment
• Monitor performance for 1–2 weeks
• Watch competitor activity
• Ensure no negative impact on repeat customer behavior

Gradual rollout protects revenue and brand trust.

Common Pricing Test Mistakes And How They Hurt Revenue

Many brands fail not because their price was wrong, but because their test was flawed.

It’s easy to sabotage results by trying too many variations at once, ignoring seasonality, or using discount codes instead of genuine price tests. Ending the experiment too early or neglecting segmentation often leads to false conclusions, costing thousands in lost revenue.

Therefore, pricing tests must be intentional, patient, and data-driven to reveal the real profit sweet spot.

Conclusion

Split testing transforms your pricing from a guess into a revenue-maximizing strategy. With careful experimentation, you uncover the price that resonates with customers, balances perceived value, and maximizes total revenue. Revvy can help automate these pricing experiments, track results, and guide you to the most profitable price points effortlessly.