How to Run A/B Price Testing for SaaS

Not sure what to charge for your SaaS product? Start by conducting A/B price testing to determine your price strategy. This guide will take you through the process of running A/B price tests for your SaaS business.

Start by setting your goals for your price test. Your objectives should be SMART:

• Specific: Increase MRR by 10%.
• Measurable: Track MRR, conversion rates, and average contract value (ACV).
• Achievable: Set realistic goals based on historical data and industry benchmarks.
• Relevant: Should correlate with your overall business goals (e.g., profitability, growth)
• Time-Bound: Define the timeframe for the test (e.g., 6-8 weeks).

Be clear about the details of the details of the test and what the goals are. 

• Increase Revenue: Investigate premium features and next level price points. Examine your product’s demand elasticity (how the quantity demanded changes in response to a price change) could influence this decision. If demand is not elastic, you can consider increasing prices without impacting sales.
• Reduce Churn: Experiment with markdowns or value-added offers. As an example, Spotify could offer an annual plan at a discounted price as a test to encourage customers to commit to a longer subscription.
• Improve Conversions: Test different messaging or pricing pages. For instance, Groove, which is help desk software, was able to increase their conversions by 25% when they redesigned their pricing page. This clearly defined the value proposition of each plan.

Schedule a comprehensive competitive research before you conclude your objectives. Investigate their target audience, functionality, price strategy, branding and perceived value. By knowing their strategies in pricing, you’ll be able to set your own benchmarks and discover business possibilities. 

Begin by testing with a smaller group of customers. Divide your audience into specific segments based on relevant metrics:

• Demographics: Age, location, industry.
• Firmographics: Company size, revenue, stage.
• Behavioral: Usage patterns, feature adoption, engagement.
• Subscription Level: Free trial, basic plan, premium plan.

Take criteria such as use case, CLV, industry or anything specific to your SaaS product to create further segmentation. For instance, the email marketing tool MailChimp could take its base and segment on the size of their email list and then test different models in pricing for enterprise vs. small business.

Take segments where you believe the most significant impact exists or where there is a lack of data. A defined smaller size sample can give more actionable insights. Be sure you determine the size that is required for the sample to yield statistically significant findings. You can use online software or calculators to figure out the right size sample relevant to the confidence level and effect size you desire.

Consider the following multiple pricing models and variations to test:

• Price Points: Test a range of prices to identify the most favorable point.
  For example, Basecamp experimented with different price points, ultimately deciding on a flat fee model that appealed to its target audience.
• Billing Frequency: Try monthly, quarterly, or annual billing. Zoom, for example, could test a discount offer for annual subscriptions.
• Pricing Tiers: Offer different feature sets at different price points. Maybe a “Pro” version for a product like Dropbox could unlock extra features and justify a higher price.
• Discounts and Promotions: Test LTO (limited-time offers) or introductory pricing. HubSpot, a CRM platform, successfully used introductory pricing to attract new customers and then gradually transitioned them to regular pricing.

Don’t Forget: It’s important to separate the price variable as much as you can when A/B testing. Also, steer clear of changes to anything else (product, marketing) when you are testing so that your results are based only on the price variations.

To give you an example, take a look at the pricing matrix table to visualize your variations:

Use a reputable A/B testing platform like Optimizely, VWO, or Google Optimize 36 for: 

• Randomization: Users randomly assigned to variations.
• Traffic Allocation: Manage the amount of traffic in each variation.
• Statistical Significance: When results are not due to chance .
• Goal Tracking: Monitor conversions and revenue per variation.

Merge your CRM with the testing tool to collect your data. Some payment providers have integrated A/B testing into their tools. If you’re using PayPro Global, check out this page.

For each variation, you should track critical metrics: 

• Conversion Rate: Percentage of users who upgrade or enroll.
• ARPU (Average Revenue Per User): Total revenue divided by number of users.
• CLV (Customer Lifetime Value): Total worth of customer over entire relationship with your brand.

Shoot for at least 95% confidence level with statistical significance between variations. In other words, you should be 95% certain that the differences are not due to chance. Take into consideration the effect size (this suggests the extent of difference in variations). One larger would mean there was a higher impact.

Investigate the feedback you receive from users to realize the perceptions of different options in pricing.

This table illustrates how you should interpret A/B price testing results:

When you reach statistical significance with your test, name the winning variation derived from your pre-defined objectives.

• Implement the proper segment if it outperforms the control
• Run a follow up test with edited variations if you have inconclusive results.

Don’t forget there is a long term effect when implementing your pricing model. While short term increase in revenue is tempting, think about what impact this will have on customer churn. If the price change leads to churn, it may not be sustainable for the future

A/B testing should not be thought of as a one-time thing, but more of an ongoing process of optimization.

• Consistently track the performance of your pricing strategy.
• To continue making advances, explore different variations.
• With market changes and customer feedback, adjust your pricing accordingly.

SaaS businesses must remember pricing is dynamic. Using A/B testing is a fundamental way to be sure that your pricing is aligned with your goals to maximize your potential.