How To Properly Implement Pricing Split Testing

When it comes to pricing, small changes can have significant impacts. Imagine buying concert tickets: the difference between $50 and $60 might not seem like much until you’re on the checkout page, deciding whether to hit “buy.” That little price jump could mean the difference between buying now or waiting for a deal.

For businesses, determining these ideal price points requires a careful approach. This is where split testing for pricing comes into play.

Whether in e-commerce or brick-and-mortar settings, split testing takes a data-driven approach to help you identify which price point will increase your revenue while enhancing customer satisfaction.

In this article, discover everything you need to know about split testing for pricing, including its implementation and key components.

Understanding the Basics of Split Testing for Pricing

Split testing, or A/B testing, involves comparing two versions of something—like a webpage, ad, or price point—to see which performs better.

Implementing a split test for pricing involves businesses experimenting with different price points to determine which price maximizes revenue, conversions, or customer satisfaction.

The goal is to optimize price by identifying how your customers will react to the increase in price. Will they be willing to pay more? Are they receptive to the new price bundling? It can also reveal how prices, like purchase volume or churn rate, impact customer behavior.

In split testing, you divide your audience into two or more groups: a control group and one or more test groups.

The control group will be your current or standard price, while the test group(s) will be assigned a different price (higher or lower).

By comparing how each group responds to their price point, you can measure which price drives better results. Is it leading to more purchases or higher average order values?

For example, if you're running an e-commerce business and want to test how a $10 increase affects sales, your control group sees the original price (say, $50), while your test group sees the new price ($60).

After running the test, you can analyze whether the higher price decreases the number of orders but increases overall revenue or if the price hike causes too much customer drop-off.

Designing a Split Test for Pricing

Split testing for pricing is a stellar way to find what price point will help you acquire more customers and retain most of your existing ones.

Here’s a step-by-step process of designing a split test for pricing:

Select pricing strategies for testing

When setting up a pricing split test, there are a few pricing strategies you can experiment with:

• Base price adjustments: This is the most straightforward approach. You adjust the core price of your product or service and test different price points. For example, if you run an online subscription service, you could test a $20/month plan against a $25/month plan to see which brings in more revenue without losing too many customers.

• Discounts: Offering discounts can drive purchases, but you have to find a sweet spot for your discount. It should boost sales and satisfy your customers without hurting profits. You can test various discount amounts (e.g., 10% off vs. 20% off) to see which strikes the right balance.

• Bundling: Bundling involves selling multiple products or services at a lower total price than if bought separately. For example, McDonald’s routinely tests bundling with meal deals, where customers might be more likely to buy a combo of fries, drinks, and burgers at a discount rather than buying each item separately.

Segment the customer base

Not all customers respond the same way to price changes. One solution to identify how different types of audiences react is by segmenting your audience to get accurate test results.

1. Geographic Segmentation

Prices that work in one region might not work the same way in another due to differences in buying power and preferences. For example, customers in urban areas might be more willing to pay higher prices than rural customers. You can test different discount levels or promotional offers instead of altering the base price.

2. Customer Loyalty or Spending Habits

Test prices with new customers versus returning customers. For example, loyal customers may be less price-sensitive, so they may appreciate rewards or perks for their continued business rather than discounts. On the other hand, new customers might find introductory discounts more encouraging when making their first purchase.

Shaun Bettman, Mortgage Broker at Eden Emerald Mortgages, shares a similar approach from the mortgage industry. He explains, "Pricing in the mortgage industry is balancing fees and interest rates. Split testing helps us determine which combinations work best for our clients."

Shaun and his team segmented customers into first-time buyers and seasoned investors. They didn’t alter base rates but offered different value-added incentives. For first-time buyers, they reduced closing fees from $2,000 to $1,500 while keeping interest rates consistent. For investors, they offered a loyalty-based interest rate reduction with standard fees.

The results were compelling: “Over a 60-day period, first-time buyers responded positively to lower upfront costs, leading to a 15% increase in new applications.”

This example shows how dividing customers based on spending habits and needs—and adjusting incentives—can reveal the best strategies to drive conversions and build loyalty.

3. Demographics

Age, income, and other demographic factors will also decide how your audience reacts to the price change. For example, younger audiences might be less receptive to the price change than older audiences. You could offer small discounts or bundle products together to make prices more receptive to them. This way, you can make prices more affordable without changing the base price.

4. Buying Behavior

Customers who buy in bulk or frequently may react differently to price changes than occasional buyers. You can try offering volume-based discounts or loyalty rewards to make purchases more attractive to high-frequency buyers, which can help maximize customer lifetime value.

Set clear objectives and key performance indicators (KPIs)

Another important step in designing your split test for pricing is to set clear objectives and KPIs so that you do not experiment without a plan or end goal.

Start with clear, measurable objectives that sufficiently answer the question, “What are we hoping to learn or achieve from this split test?”

For example, are you aiming to increase conversion rates and turn more visitors into full-time buyers? Or is the goal to increase revenue from existing users? Or do you want to extract a long-term commitment from current buyers?

At the same time, ensure your objectives align with overall business goals—for instance, are you aiming for short-term profits, or is building a loyal customer base your priority?

Once you set a clear objective, select your KPIs to measure the success of the pricing test.

The most common KPIs for pricing experiments include:

• Conversion rates: It measures how many potential customers who saw the price offering made the purchase.
• Average order value (AOV): It tells whether driving up prices or offering bundled pricing shows any impact on average spending per customer.
• Customer lifetime value (CLV): It measures how long a customer is likely to continue doing business with you. It’s especially crucial for subscription-based businesses, like those in the SaaS industry.
• Churn rate: It measures how many customers are discontinuing their business with you. The lower the churn rate, the more chances your customers will be satisfied with your price and product quality.

As Rhett Crites, Founder of Theme Park Brochures—the world’s largest database of theme park, zoo, and water park maps—states, “Pricing is vital for niche products like ours, and we rely heavily on split testing to refine it.”

In a recent test, the team experimented with two pricing strategies for their exclusive vintage maps: a $9.99 digital download versus a $14.99 print version with limited stock.

He segmented the customer base into casual visitors and hardcore collectors. Collectors were more willing to pay for the physical maps due to their rarity, while casual visitors leaned toward the cheaper digital option.

Rhett tested these price points for 45 days, aligning the test with major theme park holidays when engagement is highest. He used Google Analytics to track each group's conversion rates, average order value, and customer lifetime value. Rhett says, “This helped us understand not only immediate sales but also long-term customer retention based on price sensitivity and purchasing habits.”

Setting up clear objectives and KPIs helps businesses better navigate the complexities of pricing strategy, ensuring their test leads to meaningful results and aligns with their business goals.

Implementing A/B Testing in Different Environments

Now that you’ve segmented your customer base, selected the pricing strategy, and know the objectives and KPIs you need to measure, it’s time to implement the split testing.

Online split testing for pricing

To begin, pick the technique you want to employ to determine which price structure works best for you.

A/B testing is the most common method, where you show two versions to different segments of visitors.

For example, an online retailer might test two price points for a popular product: $49.99 versus $39.99. You can make data-driven decisions by tracking which price leads to more sales.

Other techniques include:

1. Multivariate Testing

Multivariate testing goes further than A/B testing by allowing you to test multiple variables simultaneously. For example, you could test different combinations of price points, product descriptions, and promotional messages to see which combination shows the best results.

2. Price Anchoring

Price anchoring involves presenting customers with a higher-priced option alongside a lower-priced one. This technique can influence perceptions of value and make the lower-priced item seem like a better deal.

Suppose an online retailer offers a premium version of a product at $99.99 alongside a standard version at $49. In that case, customers may be more likely to choose the standard option, perceiving it as a better bargain.

Price anchoring example (Source)

3. Dynamic Pricing

Dynamic pricing adjusts prices in real time based on factors like demand, competitor pricing, and customer behavior. Airlines often use dynamic pricing to change ticket prices based on how many seats are left on a flight or how close the flight date is.

Dynamic pricing in action (Source)

This strategy is perfect for finding a suitable price point for your product that maximizes revenue while also attracting customers.

When conducting an online split test, you’ll also need the right A/B testing tools. These tools make it easier to create and run tests while also giving insights into customer behavior.

Popular A/B testing tools include:

• Omniconvert: An all-in-one website optimization tool that also offers advanced A/B testing features via Omniconvert Explore.
• A/B testing tools in Shopify or WooCommerce apps: This is perfect for e-commerce businesses looking to test different pricing strategies directly within their platform.

Offline split testing for pricing

Implementing split tests in physical stores can be a bit trickier, but it’s doable.

One way is to adjust pricing on different items or within different store locations.

For example, a grocery chain might run a test by lowering the price of a popular cereal in one store while keeping it at the regular price in another. By comparing sales figures from both locations, they can see how price impacts buying behavior in real time.

That said, in-store promotions come with unique challenges. For example, customer flow will be highly reliant on the time of day, local events, and weather. To overcome these challenges, it’s important to run tests over a significant period.

Key Components of a Successful Pricing Test

There’s more to a successful test than just switching numbers around.

To truly gain insights that lead to increased revenue and customer satisfaction, you need to pay attention to some key components:

1. Conversion rate

Conversion rate is often the first metric businesses look at when evaluating a pricing test. It tells you the percentage of visitors who make a purchase after seeing a particular price.

Pro tip: Look beyond immediate conversions. Are customers who bought at a lower price more likely to churn after a month? You need to balance conversion rate with long-term metrics to ensure you’re not just making sales but building loyalty.

As Mary Zhang—Head of Marketing and Finance at Dgtl Infra, who managed to increase their average deal size by 15% through careful price testing—says, “Don't just focus on conversion rates. We track metrics like Customer Lifetime Value and churn rate to understand the long-term impact of price changes.”

2. Revenue

While the conversion rate is important, revenue is the ultimate goal that reflects the success of the price point. Revenue considers both price and volume, meaning it gives a fuller picture of how well a pricing strategy works. A price that boosts conversion but doesn’t move the needle on revenue is probably not worth pursuing.

For example, Amazon experimented with its pricing model and discovered that lowering prices on certain items, even by small amounts, can lead to a significant increase in total revenue due to higher sales volume.

This strategy is often referred to as "charm pricing" or "psychological pricing," where prices are set just below a round number (e.g., $19.99 instead of $20) to make products appear cheaper and encourage more purchases.

Amazon's “charm pricing” strategy (Source)

3. Clear hypothesis

Always start with a specific, measurable hypothesis. For the uninitiated, a hypothesis is like a prediction where you outline what you expect from the test and why.

For instance, "Increasing our enterprise plan price by 10% will result in a 5% increase in revenue without significantly impacting conversion rates."

4. Statistical significance

Statistical significance tells whether the results of a test are reliable or just happened by chance. It helps you determine if the difference in results—like a boost in sales or a drop in conversion rates—is likely due to the changes you made (like a new price point) rather than random variation.

Mary Zhang, Head of Marketing and Finance at Dgtl Infra, emphasizes, “We ensure each test variant has at least 1,000 visitors to achieve statistical significance. In our last test, we ran the experiment for six weeks to reach this threshold.”

Without statistical significance, your results may be inconclusive.

Pro tip: Use online sample size calculators offered by tools like Optimizely to calculate the sample size needed for statistical significance so you can feel confident in your data.

Sample size calculator (Source)

5. User experience

Pricing isn’t just about the dollar amount—it’s also about enhancing the customer experience and how customers perceive that value. For example, framing a price as a monthly fee instead of an annual one can make it feel more affordable, even if the total amount is the same.

Spotify uses UX design in its pricing pages to highlight the benefits of its Premium plan versus the Free plan.

Shopify highlights the benefits of its Premium version for a better user experience

By showing how Premium offers ad-free listening and offline music access, they’re not just presenting a price—they’re presenting a lifestyle upgrade.

Pro tip: Conduct UX testing along with price testing. Get direct feedback on how customers feel about the price presentation, and consider running A/B tests on the design and layout of your pricing page.

Conclusion

Whether online or offline, split testing plays an important role in determining which pricing structure works the best for your business.

However, it’s not a one-time process. The true value of split testing lies in its iterative nature—each test provides valuable information that can inform future pricing adjustments.

It’s an ongoing process that will help you refine and optimize your pricing structure with changing times, market trends, and customer preferences.