Pricing Experimentation

What is Pricing Experimentation?

Pricing experimentation is a strategic method of finding the most effective pricing strategy through trial and error. In this approach, businesses test different prices and pricing structures to understand their impact on consumer behavior and overall sales. Through testing, they optimize their pricing for maximum profitability and market penetration.

The process involves setting different prices for similar products or services, normally through one of the following techniques:

  • A/B testing — Splitting customers into two groups — A (the control) and B (the test) — and offering different prices to each.
  • Multi-armed bandit testing — Using an algorithm that automatically adjusts prices based on customer behavior, allocating more traffic to the better-performing variant as the experiment progresses.
  • Multivariate testing — Examining the impact of multiple variables simultaneously. It helps understand how different pricing elements interact with each other and influence customer behavior.
  • Conjoint analysis — Testing different combinations of product features and price points to find the optimal mix.
  • Dynamic pricingComplex models, like probabilistic modeling and real-time price adjustments based on market demand and customer data.

Pricing is one of the hardest factors to get right because it’s so non-linear. There’s no guarantee customers will respond favorably to a particular pricing model or numerical value, even if it works for similar products. The only way to know for sure whether a pricing strategy will work is to experiment and iterate.


  • Experimenting with pricing
  • Price testing

Importance of Conducting Pricing Experiments

Since customers already make the connection in their heads, pricing needs to align with product value.

If a business sets its prices too low, they’ll either lose revenue from underpricing or risk customers associating their product with low quality. Setting prices too high discourages customers from buying or gives them unrealistic expectations. In both scenarios, a business risks losing potential sales.

Experimenting with prices minimizes these risks and helps businesses achieve price optimization — the sweet spot between customers seeing the best value for their money and profitability for the company.

It also helps businesses understand customer preferences and behavior, leading to better products and targeting. Let’s say a business finds people are more willing to pay for a product if it’s bundled with another item. Product devs can add features that make the two more interoperable, marketers can advertise it, and sales reps can mention it to prospects for whom it would be a good fit.

Since businesses can use pricing experimentation to understand their customers’ price sensitivity, it also plays a critical role in marketing and sales strategies. Thanks to testing, sales reps can prepare themselves for objections from price-sensitive customers, and marketers can write copy that reinforces their value proposition in relation to those customers’ pain points.

5 Factors to Consider in Price Experimentation

When testing different pricing models, amounts, and strategies, it’s important to remember your business is 100% unique. Even against competitors with a similar business model, you’ll find there are numerous factors differentiating it from the pack that can affect how customers view your brand (and how much it makes sense to charge them).

When conducting pricing experiments, make sure to pay attention or control for these factors:

Your ICP

Your ideal customer profile (ICP) is the first factor to consider. Since different segments of the market will have different needs, pain points, and priorities, what works for one won’t work for the others. You have to align your ICP with the product you’re selling and reflect it in your pricing.

When building an ICP, busiensses should consider:

  • Buying behavior, including why they buy, how often they do, and their process for doing so
  • Pain points and business challenges they face
  • How the product can benefit and solve those pains/challenges
  • Personal characteristics, like company size and industry
  • Levels of price sensitivity

For example, if you’re dealing with price-sensitive customers who only make major investments in products like yours once per year, you could test lowering the price, offsetting lower margins with an increased sales volume. Or, you might test higher prices in favor of a smaller, more profitable, and less price-sensitive customer base.

Competitor prices

Although competitor pricing isn’t everything, it certainly is a crucial starting point. Competitors are living, breathing examples of what’s already working (at least somewhat).

Suppose a CRM vendor wants to test different pricing strategies for its new marketing automation feature. In that case, it can investigate how other CRM vendors price their marketing automation components (if they have one). They’ll quickly find that most competitors use some form of flat-rate microservice offering or incorporate the feature into their higher-tier packages.

This automatically tells them what customers are accustomed to paying, and which pricing structure will be easiest for buyers to understand. That way, they don’t have to start from scratch when figuring out the best way to sell the feature.

Business cost structure

In general, businesses need to test pricing models that account not only for the cost difference between offering their products and the price of competitors’ offerings but also for overhead. This includes things like employee salaries, bills, rent, taxes, utility costs — you get it.

Your cost structure directly affects profitability. Understanding your fixed and variable costs is essential to set prices that not only cover expenses but also yield desired profit margins (e.g., in cost-plus pricing).

It also influences how price changes affect customer demand (price elasticity). For instance, companies with high fixed costs but low variable costs might price more aggressively to increase volume and cover fixed costs.

Plus, a thorough understanding of the cost structure provides flexibility in pricing strategies. For businesses with lower variable costs, there’s more leeway to experiment with pricing without significantly impacting the bottom line.

Price points, plans, and packaging options

Different price points and tiers allow a business to cater to various segments of the market. By structuring offerings into basic, standard, and premium tiers, companies can attract a broader range of customers — from those seeking low-cost options to those willing to pay a premium for enhanced features or services.

Pricing experimentation on certain groups within your customer base can help you understand which pricing plans are most attractive to certain consumer demographics, optimizing the product lineup to meet diverse needs.

Tiers and packaging variations enable businesses to experiment with multiple pricing strategies simultaneously. When you can test multiple variables while sill isolating the impact of each, you end up with a better idea of which combinations yield the highest total revenue or the best profit margins.

Psychological tactics

There are several types of psychological pricing, but they all operate on the same premise: that customer behavior is changeable. By cleverly framing product prices, businesses can steer customers towards certain actions.

For instance, you might test a $100/month subscription against a $99/month one to test different odd-even pricing strategies against each other. Users looking for an advanced, premium product might perceive the $100/month product as more sophisticated, while a customer looking for something affordable would see the $99/month option as less expensive.

Keep in mind that it’s worth testing higher prices even if you think your customer base is price-sensitive. It’s common for businesses to raise their prices and find that, in addition to retaining most or all of their existing customers, they ended up creating more demand for their product.

How to Run Pricing Experiments

Running a pricing experiment is a five-step process that involves setting goals, establishing a control group, choosing the right approach, and analyzing results.

1. Set goals and success metrics.

Like any other experiment, price testing needs a clear objective or goal. Normally, that falls into one of the following categories:

  • Increasing revenue
  • Maximizing profit margins
  • Attracting or weeding out a particular type of customer
  • Improving customer satisfaction
  • Making changes to your pricing policy (e.g., discounting)

Once you know what you want to achieve, you can select the appropriate metrics for measuring success. For example, if your goal is to attract a specific type of customer, your success metrics could include leads generated from that specific demographic, conversion rates, and customer retention.

2. Segment your customer base for A/B testing.

To effectively segment your customers for a split-test pricing experiment, you’ll want to consider various strategies that align with your business goals and the specific insights you want to gain from the experiment.

You mught segment customers on any of the following fronts:

  • Demographics (age, gender, location, or income level)
  • Firmographics (for B2B — company size, industry, or location)
  • Psychographics (customers’ lifestyles, interests, and attitudes)
  • Behavioral (purchase history, product usage, and engagement levels)
  • Geographical (region, climate, or market maturity)
  • Customer value (high-value vs. medium-value vs. low-value customers on an annual basis)
  • Technological (customers’ preferred devices, operating systems, browsers, or software)

It’s important not to overcomplicate things. Effective pricing experiments require a relevant sample size and careful data analysis. If you have too many customer segments, your results might not be statistically significant.

3. Create a variant and control group.

Siuccessful pricing experimentation also relies on your ability to isolate the impact of a single variable. The only way to do that is by using a control group — one that doesn’t experience the changes you’re testing.

Creating a control group can be tricky, but it’s necessary for accurate results. You could:

  • Test different pricing strategies between geographically distinct regions
  • Randomly assign customers to either the varianct or control group
  • Segment customers based on behavior and then apply the variant to only one segment

Just like when segmenting customers, don’t change more than one variable at a time. This would make it impossible to identify which changes affected your results.

4. Assess the data to make pricing decisions.

Once you’ve collected all the data from your pricing experiment, it’s time to analyze it and make decisions based on your findings.

Consider the following:

  • Did customers in either group respond differently to the pricing changes?
  • Did any of the variations result in more sales? Higher average order values or deal sizes? More leads generated?
  • Which variant performed best overall against your success metrics?

The answers to these questions will help inform your decisions on how to set prices going forward. If a certain tier or packaging option resulted in higher profits, it might be worth considering as a permanent pricing strategy or testing against another variable.

5. Retest the optimal price on an ongoing basis.

Customer demand and market dynamics are constantly shifting, which is why it’s so important to test pricing on an ongoing basis.

  • Track your results and customer feedback to determine if the optimal price continues to be successful.
  • Analyze market trends, competitive pricing, and customer preferences to determine if any adjustments need to be made.
  • Regularly conduct pricing experiments for flat rates, tiers, usage-based components, and other pricing variables.
  • Also test discounting, bundling, upselling, and cross-selling strategies to figure out what sticks most.

A long-term pricing advantage accounts for anywhere from 15% to 25% of a company’s total profit, according to research from McKinsey. And the only way to create that advantage is to test things on an ongoing basis.

How SaaS CPQ and Billing Software Enables Price Experimentation

On the surface, SaaS pricing doesn’t seem too complex. But its combination of fixed-rate, tiered, seat-based, and sometimes usage-based pricing models make it a complicated web of variables. And each component plays a role in the overall success of your pricing strategy.

While there are several ways to overcome SaaS pricing challenges, CPQ and subscription management software stand out as the most effective solutions for handing just about all of them.

With CPQ (configure, price, quote), busiensses can:

  • Set pricing rules for different products and customer segments
  • Automate product configurations and pricing calculations
  • Test and and deploy new pricing strategies across the whole sales department
  • Eliminate human error and ramp-up periods typically associated with this process
  • Set prices dynamically based on real-time factors (with an advanced CPQ system)

With SaaS subscription management software, businesses can:

  • Track revenue and conversion metrics to determine which pricing strategies work best
  • Bundle, unbundle, and tailor subscription packages for different customer segments
  • Test free trial, upsell, and cross-sell offers more easily
  • Monitor customer churn to understand how pricing changes impact the current customer base
  • Automatically implement a new billing structure each time a variable changes

These two tools make it easier than ever for SaaS companies to implement changes for the variable group, test them, and analyze their impact. The process that used to take weeks or even months can now be done in a span of days.

People Also Ask

How long should a pricing experiment run?

As a rule of thumb, it’s best to run experiments for a two-week period. But, ideally, pricing experiments should continue until the results achieve statistical significance. This means the data collected must be substantial enough to confidently indicate whether price changes have led to the desired outcomes, such as increased revenue or customer engagement.

What are some ethical considerations for price experimentation?

When running pricing experiments, avoid using price as a variable in ways that might exploit certain customer segments or create unfair advantages. For example, offering lower prices to certain demographics based on sensitive information like race or gender could lead to public backlash and legal trouble.

Also ensure that any data collected during the experiment is handled with strict adherence to privacy laws and regulations. This involves securing personal information and using it solely for the purpose intended, under conditions that customers have consented to​.

Before testing pricing, disclose internally any potential conflicts of interest that might affect the experiment’s outcome. This includes situations where business interests might unduly influence the design or results of the pricing strategy, leading to biased or skewed data that could mislead stakeholders about the effectiveness of a price change​.

How can I avoid confusing customers with too many pricing options?

Significant fluctuations in pricing, especially without clear communication, leads to customer dissatisfaction and reputational damage. To avoid confusion, proactively tell customers about pricing changes and provide a rationale for them. When you do make changes, limit the number of options to a manageable amount that aligns with customer preferences.

What tools are available to help me run pricing experiments?

Along with CPQ and subscription management software, there are other tools available to help businesses run pricing experiments. These include A/B testing software, analytics tools, and market research platforms. It’s important to choose a combination of tools that best fit your business needs and goals.