What is Price Testing? | DealHub AI

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The #1 Agentic Quote To Revenue Platform for HubSpot.

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Table of Contents

What is Price Testing?

Price testing is a research method businesses use to determine the optimal price for a product or service by analyzing customer behavior, willingness to pay, and market demand at different price points.

There are several different ways to test prices:

Surveys and direct customer feedback (e.g., Van Westendorp, Gabor-Granger)
Experimental testing (e.g., A/B testing, monadic testing)
Market simulation (e.g., conjoint analysis)
Cost-based approaches (e.g., cost-plus pricing)

The end goal of price testing is to maximize revenue, profitability, or market share by aligning prices with customer expectations and market positioning. When prices are optimized, you’re neither underpricing (leaving money on the table) nor overpricing (scaring away potential buyers).

At that point, your pricing becomes a competitive advantage — it’s actually a lever for persuasion and conversion, rather than a mere transactional detail.

Synonyms

Price experimentation
Pricing research
Pricing study
Product pricing test

The Purpose of Price Testing

According to research from McKinsey, a long-term advantage in pricing can account for anywhere from 15% to 25% of your company’s total profit. And the only way to achieve that level of advantage is to test your prices constantly.

The reasons price testing is so advantageous for your business are further-reaching than you might think, though.

Price tests help you understand willingness to pay.

If you know the limit to what customers will pay for your product, you have a better understanding of how much value they see in it. From there, you can improve your marketing campaigns to help them see more value in your product and make changes to the product itself to better align with their perceived value.

With willingness to pay data, you also know what you can and can’t afford to spend on promotions and discounts. And you know the upper limits of your cost structure (i.e., how much your operating expenses can be before you start losing money).

Experimentation helps you optimize for customer lifetime value.

If you know how much customers are willing to pay and how often they’re likely to repurchase, you can maximize their lifetime value by adjusting prices and creating loyalty programs or other incentives.

You can stay on top of market dynamics.

You may already know how much demand there is for your product, and whether that demand is elastic or inelastic. However, those dynamics can change quickly. By constantly testing prices, you can better gauge market trends and adjust your strategy accordingly.

Agility keeps your product from being too commoditized.

In other words, you’re not competing solely on price. You’re playing the value game, which is much more advantageous for your brand overall. On top of that, it enables you to adapt pricing geographically based on local purchasing power, foreign exchange rates, and operating costs.

Being flexible means you can test new things before fully diving in.

Whether you’re launching a new product, expanding into a new market, or expanding your product line, price experiments give you valuable data before you make a major investment. It’s less of a risk and more of a calculated move.

You’ll have an edge over competitors who don’t experiment.

In an OpenView Partners study of over 2,200 SaaS companies, more than half (52%) of companies said they don’t test their pricing at all. An additional 19% said they only piloted it before going live. Only 6% of companies had done in-depth pricing research to understand their customers’ willingness to pay.

This means the vast majority of companies are essentially “making up” prices and hoping they stick. If you’re the one company in your industry that’s constantly staying on top of pricing trends and experimenting to find optimal prices, you’ll capture a significantly larger share of the market. And your customers will be a lot happier overall.

Benefits of Price Testing

Continually testing prices for your products and services is hugely beneficial. Pricing will always be an inexact science in some ways, but testing eliminates some of the guesswork that comes along with determining what to charge and to whom.

Its most valuable benefits are:

Hitting the “sweet spot” between margins and demand. If you price your products too high, you might have solid profit margins, but that’s worth nothing if significantly fewer people are buying from you. If you price too low, you have the opposite problem. Through price testing, you can figure out what price gets you the highest sales volume while maintaining a solid margin.
Improving customer satisfaction. Customers aren’t happy when they feel like they’re getting a bad deal. If they’re happy with what you give them for the price works well enough, they’ll continue to do business with your company. And they’ll have a more favorable opinion of your products.
Making better pricing decisions . If you’re setting product prices based on data and real customer feedback, they’re going to have a far more positive impact than if you’re just making changes based on a hunch or competitor pricing.
Differentiation from the competition. While you don’t want to go too far in the opposite direction of competitors, pricing your products at a level that highlights your positioning can increase your sales volume. For instance, if you’re a high-end brand, coming down on the price might make your customers think your prodct is “cheap,” even if it’s the best of the best.

Methodologies for Price Testing

Van Westendorp Price Sensitivity Meter

The Van Westendorp Price Sensitivity Meter gauges consumer perceptions by identifying acceptable price ranges, helping to understand at what price points a product is considered too cheap, a bargain, expensive, or too expensive.

Start by asking respondents four key questions:

Too Cheap: At what price would you consider the product to be priced so low that you would feel the quality couldn’t be very good?
Bargain/Good Value: At what price would you consider the product to be a bargain—a great buy for the money?
Expensive/High Side: At what price would you consider the product starting to get expensive, so that it is not out of the question, but you would have to give some thought to buying it?
Too Expensive: At what price would you consider the product to be so expensive that you would not consider buying it?

The responses are plotted as cumulative frequency distributions for each question. The intersections of these distributions reveal key price points:

Point of Marginal Cheapness (PMC): The intersection of the “Too Cheap” and “Expensive” curves, indicating the lower bound of an acceptable price range.
Point of Marginal Expensiveness (PME): The intersection of the “Too Expensive” and “Cheap” curves, representing the upper bound of an acceptable price range.
Indifference Price Point (IPP): The point where the “Expensive” and “Cheap” curves intersect, suggesting the price at which an equal number of respondents perceive the product as cheap or expensive.
Optimal Price Point (OPP): The intersection of the “Too Cheap” and “Too Expensive” curves, indicating the price at which the number of respondents considering the product too expensive equals those considering it too cheap.

Gabor-Granger method

The Gabor-Granger method is a pricing research technique developed in the 1960s by economists André Gabor and Clive Granger. It is designed to assess consumer demand and price sensitivity by determining the optimal price point for a product or service.

To start, respondents are presented with a product or service description, often accompanied by images or detailed features. Each respondent is shown a series of predetermined price points and asked to indicate their likelihood of purchasing the product at each price. You can do this using a simple “Yes/No” format or a scaled response (e.g., “Definitely Buy” to “Definitely Not Buy”).

In some implementations, if a respondent indicates willingness to purchase at a certain price, they are subsequently shown a higher price point. Conversely, if they are unwilling to purchase, they are shown a lower price point. This process continues until the maximum price the respondent is willing to pay is identified.

The end result is an illustration of the percentage of respondents willing to purchase at each price point, highlighting how demand varies with price. From that, you can calculate potential revenue by multiplying the price by the corresponding demand, helping identify the price point that maximizes revenue.

Conjoint analysis

Conjoint analysis is a survey-based statistical technique you can use to understand how consumers value different attributes that make up your product or service. The results guide product development decisions and help you assess the components of product value and how they feed into overall price perception.

You start by determining its key features (attributes) and defining varying degrees or options (levels) for each attribute. For example, for a smartphone, attributes might include screen size, battery life, brand, and price, with each having multiple levels.

From there, you’ll create a set of product profiles, each representing a unique combination of attribute levels. Due to the vast number of possible combinations, businesses generally use a fractional factorial design to present a manageable subset to respondents.

Respondents are shown a series of product profiles and asked to make choices, rank, or rate them based on their preferences. This process simulates real-world purchasing decisions, requiring respondents to evaluate trade-offs between different attributes.

Finally, you apply a statistical method (e.g., multinomial logistic regression or hierarchical Bayesian models) to the collected data. This is how you estimate the utility (value) consumers assign to each attribute level. This indicates the relative importance of each feature and how changes in attributes influence consumer preferences.

Monadic price testing

With monadic testing, each respondent is exposed to only one price scenario, allowing researchers to gauge purchase intent without the influence of alternative pricing options.

The total sample is divided into separate groups, known as cells. Each cell is presented with the same product or service but at a different price point. Respondents in each cell are shown the product with the assigned price and are asked about their purchase intentions or perceptions.

You’ll collect the responses to determine the likelihood of purchase at each specific price point. By comparing responses across all the different cells, you can estimate demand at each price level and identify the optimal price (although this doesn’t account for price elasticity across multiple levels).

Cost-plus pricing

Cost-plus pricing is a straightforward pricing strategy where you add a fixed percentage markup to your product’s total production or service delivery cost to determine its selling price.

Implementing it is as easy as 1-2-3:

Add up your direct and indirect production/service delivery costs.
Decide your target profit margin.
Add the calculated profit margin to the total production cost

While this isn’t a “test” per se, you can test different margins over time to arrive at the optimal markup.

Advantages and and disadvantages of each method

To help you understand which is best for your business, here’s a structured table summarizing the advantages and disadvantages of each price testing methodology:

Methodology	Advantages	Disadvantages
Van Westendorp Price Sensitivity Meter	– Identifies price perception and acceptable price ranges. – Simple to implement via surveys. – Helps in avoiding extreme pricing errors.	– Does not consider real purchase behavior. – Lacks competitive context. – Works best for new products but less effective for established ones.
Gabor-Granger Method	– Directly tests price willingness to pay (WTP). – Easy to conduct via surveys. – Provides demand curves at different price points.	– Respondents may overstate or understate their willingness to pay (hypothetical bias). – Assumes a linear demand curve, which may not always be accurate. – Focuses solely on price without considering other product attributes.
Conjoint Analysis	– Evaluates trade-offs between price and other product attributes. – Mimics real-world decision-making. – Quantifies the value consumers place on each attribute.- Provides deep insights into price elasticity of demand.	– Requires expertise to design and analyze properly. – Can be time-consuming and expensive. – Complexity increases with more attributes.
Monadic Price Testing	– Measures real purchasing intent for a single price point per group. – Provides reliable data for demand estimation. – Useful for A/B testing.	– Requires a large sample size to test multiple price points. – Can be expensive to implement at scale. – Does not measure price elasticity across multiple prices in one test.
Cost-Plus Pricing	– Simple and easy to implement. – Guarantees the company makes a profit from each sale. – Works well for stable-cost industries.	– Ignores customer willingness to pay and competitor pricing. – Doesn’t guarantee price optimization. – Can lead to suboptimal pricing in competitive markets.

Note: In some cases, combining multiple methods may provide a more comprehensive understanding of optimal pricing strategies.

Implementing a Price Testing Framework

To do it properly, you have to first determine your objectives. Then, you’ll pick the methodology that fits those objectives and run the tests. After that, you’ll analyze the results and use them to inform your pricing decisions.

Steps to develop a price testing framework

Define your objectives

What do you want to get out of your price tests? Examples of objectives include:

Testing customers’ perceptions of value
Determining willingness to pay at different price points
Evaluating the impact of a price change on sales/demand
Identifying the optimal price point for a new product or service
Comparing demand and sales volume at two different price points
Figuring out which pricing models work best for your target customers

With your pricing team, figure out which objectives are most important to you and prioritize them. This will help you narrow down which pricing methodology to use.

Single out your target audience

Your ideal customer profile (ICP) is the group you’re going to want to test these pricing strategies on. Make sure you’re picking a representative sample of your target customers to get the most accurate results. Tailor your framework to align with their preferences, behaviors, and purchasing power.

Choose your price testing method

Using our table above, determine which price testing method would be best for your pricing objectives.

A/B testing is best if you want to directly compare two different price points.
Dynamic pricing is best when you want to adjust prices based on market demand while protecting your margins.
The Van Westendorp Price Sensitivity Meter excels at testing customers’ perceptions of value.
The Gabor-Granger method evaluates willingness to pay most effectively.
Monadic price testing helps you measure purchase intent and customer satisfaction at different price points.
A conjoint analysis helps you find the optimal price point for a new product or service, and which pricing models work best.

Develop your hypothesis

A hypothesis is a testable statement about the potential outcome which you can benchmark against. For example, “If we increase our price by X%, sales volume will decrease by Y%.” This will help you measure the impact of your pricing changes and make informed decisions.

Design and implement the test

First and foremost, you’re going to want to make sure you have the right software to run tests. This will vary depending on which kind of test you run — survey-based tests would use a software like SurveyMonkey, for example. Others might use price optimization software or an ecommerce platform.

Also make sure you have a controlled group and a test group.

The control group should have your current pricing strategy.
The test group will have the new one you want to try out.

Set a time frame for your test (ideally, between two and four weeks), then run it and monitor customers’ reactions.

Analyze your data

During your test, your system will have collected data on customers’ reactions and purchasing patterns. Analyze this data to see how the original price performed against the control, or how different attributes impacted purchase intent and willingness to pay.

Draw conclusions and make decisions

If a price change has a positive impact on your bottom line, it might be worth implementing. Test multiple different price points and models to see which one has the best results. When making decisions, remember to look into other factors, like competitive pricing as well.

Benefits of a using a price testing framework

Compared to just running a test without a structured framework, following the steps above brings several tangible benefits:

You’ll pick the right test for your situation.
Your customer base will actually represent your target market.
You’ll have a controlled group that allows you to compare different pricing strategies and see their impact on purchasing behavior.
Your data analysis will be more thorough — you’ll truly understand (a) how customers currently value your product and (b) how you can influence that.
You’ll have a structured process in place for future pricing tests, making them more efficient and effective.

Aligning Pricing Strategies with Market Dynamics

Understanding your customers’ expectations

When it comes to pricing, customers have certain expectations and behaviors. Understanding these can help you better craft your pricing strategy.

Reference prices

Customers often use reference prices to assess whether a product is a good deal or not. This is called the anchoring-and-adjustment heuristic, or anchoring bias.

These could be previous prices they’ve seen for the same product or similar products from competitors. A lower price compared to their reference price could entice them to purchase, while a higher price might deter them.

That’s why some companies drive sales with promotional offers using price anchoring — it shows how much your product used to cost or how much it usually costs to create a reference point for customers.

Price sensitivity

Some customers are more sensitive to pricing than others. This is often dependent on factors like income, age, product category, and level of necessity. For example, a student may be more price-sensitive when buying textbooks compared to a high-earning professional shopping for luxury items.

Market competition

Price sensitivity can also vary based on timing. For instance, a gas station in the middle of nowhere will be able to charge higher prices because there are no other options for customers in the area. However, if a new gas station opens nearby, the original one may have to lower their prices to remain competitive.

Price consistency

Buyers value predictability. If you’re constantly changing your prices, they may feel misled or lose trust in your brand. This is why, in general, it’s a bad idea to A/B test your prices in real time — customers getting different prices for the same product can lead to confusion and frustration. Instead, if you want to experiment with pricing strategies, it’s better to do controlled tests.

Customer perception

Customers often associate price with quality. A higher price can give the impression that the product is of better quality, while a lower one could raise questions about its value. If you’re selling to buyers who care about quality, low prices could be costing you sales — you should increase them to match their demand even if you can afford not to.

Adapting to market changes

Price sensitivity can change depending on market conditions. For instance, during an economic downturn, consumers look for cheaper alternatives to their usual purchases.

The level of competition in the market can also affect price sensitivity and value perception. If there are several similar products available, buyers will have more options to choose from and will be more conscientious of the ticket price.

This is especially true if larger competitors with economies of scale enter the market and can afford to sell products for significantly cheaper.In addition to changing your prices, you need to consistently pursue operational efficiency and cost reduction (within reason). That way, if the market is willing to pay less, you can afford to lower your margins a bit.