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.
Precisely Define Your Objectives
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.
Free A/B Price Testing Tracking Sheet
Run effective pricing experiments and track your results with ease. Track:
-
experiments
-
variations
-
metrics
-
results
-
and key learnings!
Strategically Segment Your Target Audience
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.
Free A/B Price Testing Tracking Sheet
Run effective pricing experiments and track your results with ease. Track:
-
experiments
-
variations
-
metrics
-
results
-
and key learnings!
Carefully Design Your Pricing Variations
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.
Some examples of how to use A/B Price Testing for different SaaS models:
|
Pricing Model |
Description |
A/B Test Examples |
Implementation |
|
Flat-Rate Pricing |
One price for all features. |
Test different flat rates (e.g., $99/month vs. $129/month). |
Perfect for products with straightforward features or those with a specific niche market. |
|
Tiered Pricing |
Numerous plans with several features and price points. |
Test variables (3 vs. 5) or features included in each tier. |
Great for products with a range of features that can be bundled into different packages. |
|
Usage-Based Pricing |
Price based on customer consumption or usage of the product. |
Test different pricing thresholds (e.g., $0.10 per email sent vs. $0.05 per email sent) or offer volume discounts. |
Works well for products with varied usage between customers (e.g., email marketing, cloud storage). |
|
Per-User Pricing |
Price per seat. |
Test various per-user rates or offer discounts for large teams. |
Typically used for collaboration tools or project management software. |
|
Freemium Pricing |
Free plan with restricted features and paid plans for added functionality. |
Test limitations or features in the free plan, or experiment with different upselling strategies on the pricing page. |
Practical for acquiring a large user base and converting a percentage to paid plans. |
Use what is called charm pricing—prices that end in 9 or 5 make them more appealing. For instance, test $99/month versus $100/month to confirm the psychological effect. Charm pricing leads to increased conversions.
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:
|
Plan Name |
Price Point |
Features Included |
Target Segment |
|
Control (A) |
$100/month |
Feature 1, Feature 2, Feature 3 |
All Segments |
|
Variation 1 (B) |
$120/month |
Feature 1, Feature 2, Feature 3, Premium Support |
High-Value Users |
|
Variation 2 (C) |
$80/month |
Feature 1, Feature 2 |
Budget-Conscious |
Free A/B Price Testing Tracking Sheet
Run effective pricing experiments and track your results with ease. Track:
-
experiments
-
variations
-
metrics
-
results
-
and key learnings!
Meticulously Implement Your Test
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.
When it comes to the price test: be transparent with your users! Explain that they may see different prices.
Free A/B Price Testing Tracking Sheet
Run effective pricing experiments and track your results with ease. Track:
-
experiments
-
variations
-
metrics
-
results
-
and key learnings!
Carefully Monitor, Analyze, and Interpret Results
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:
|
Metric |
Result |
Interpretation |
Actionable Insights |
|
Conversion Rate |
Elevated |
The new price may be more appealing to customers, resulting in sign-ups/upgrades. |
Think about implementing the new price, but watch for impact on ARPU and CLV. |
|
Decreased |
The new price may be a deterrent, causing potential customers to hesitate or choose competitors. |
Examine the cause of the drop. Are there other issues influencing conversions? Consider adapting the price or offering with additional incentives. |
|
|
ARPU (Average Revenue Per User) |
Elevated |
The new price is producing more revenue per customer, possibly indicating a better perceived value. |
If CLV is also higher, implement the new price. If not, you could balance price with alternative value propositions to keep customers long-term. |
|
Decreased |
The new price is not engaging high-value customers or the perceived value is low. |
Rethink your pricing strategy. Consider offering different tiers or adding more value to your product. |
|
|
CLV (Customer Lifetime Value) |
Elevated |
Customers are willing to pay more over time, indicating increased loyalty and the potential for increased revenue. |
This is a good sign. Implement the new price and consider ways to increase customer lifetime value through upselling and cross-selling. |
|
Decreased |
Customers may be churning out faster because of price increase, resulting in an overall lower revenue. |
Scrutinize the reasons for churn. Offer incentives to keep customers or adjust the price to balance short-term revenue gains with long-term customer value. |
|
|
Qualitative Feedback |
Favorable |
Customers express pleasure with the new price and think of it as fair value. |
This reinforces your decision to adjust the new price. Keep gathering feedback to track customer sentiment. |
|
Unfavorable |
Customers grumble about the price increase or feel it’s unjustified by the value provided. |
Reconsider your pricing and value proposition. Possibly offer discounts or bundling features to address customer concerns. |
Free A/B Price Testing Tracking Sheet
Run effective pricing experiments and track your results with ease. Track:
-
experiments
-
variations
-
metrics
-
results
-
and key learnings!
Fearlessly Make Data-Driven Decisions
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
Free A/B Price Testing Tracking Sheet
Run effective pricing experiments and track your results with ease. Track:
-
experiments
-
variations
-
metrics
-
results
-
and key learnings!
Iterate, Refine, and Optimize
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.
Conclusion
Though pricing might feel like a puzzle but it’s a make-or-break factor for any SaaS business. And one way to get it right is to run A/B tests. It will help you find that sweet spot that keeps both your customers happy and your bottom line healthy. So experiment, dig into the data and keep tweaking your approach. That’s how you stay ahead of the game and leave your competition in the dust.
FAQ
-
There are three main methods: A/B testing (comparing two variations), cost-plus pricing (calculating costs and adding a markup), and direct pricing research (surveying customers about their willingness to pay).
-
Conversion rates (percentage of sign-ups or upgrades), ARPU (average revenue per user), and Customer Lifetime Value, (estimates the total revenue a customer generates over their lifetime) are the key metrics you should track.
-
Look for a statistically significant difference in metrics between the pricing variations. A higher level (e.g., 95%) suggests a reliable result. The effect size measures the impact of the price change in your metrics.
-
We don’t recommend having different price points for the same product only because it can be perceived as unfair. But if you do A/B test prices, consider using different names, bundles or offering slightly different features on the second product.
-
Because pricing is dynamic, repeated testing is recommended. Whenever you add new features, make any market changes or introduce a new pricing strategy, be sure to monitor your metrics and conduct testing.
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