Setting prices for goods and services can be a big challenge for businesses. You need a pricing strategy that helps you identify an optimal price. The goal is to make your customers see the price as a value that they are willing to pay but still provide you with a profit. It would be ideal to intuitively know what that price is, but intuition alone can’t solve this problem—you need to conduct pricing research.
Read on to find out what pricing research is, how to conduct it, and the common pricing research models you should become familiar with.
Pricing your product can’t be done with a simple mathematical equation. You need to conduct pricing research as a part of your overall strategic market research. Pricing research is what guides you in determining the optimal price point for products or services to maximize revenue. It’s the process of researching the right price for your product.
It’s critical to find the right price for your product because overpricing may limit your market share, and underpricing can prompt your customers to question product quality. Performing pricing research helps you:
The only way to fully understand what your product should cost is to do your research.
Now that we’ve established that pricing research is essential for finding the optimal price for your product, let’s move on to how to conduct your research.
The first step in any type of research, including pricing, is to define the purpose of your research. Are you pricing a new product or optimizing an existing price?
There are a variety of tools for researching. Choose your tool or method based on your stated purpose. Are you looking for a specific price point or a range?
How do customers view price in the context of purchasing products like yours? For example, does a high price mean elite or unreasonable?
Conduct research based on the method you’ve chosen to meet your goals. SurveyMonkey has a variety of research tools to meet any need.
Evaluate the data you collect—SurveyMonkey has various tools to assist with analysis—and choose the best price for your product.
There are several ways to find the right pricing structure for your product lines. Let’s look at four of the most common pricing research methods.
The Van Westendorp pricing model, developed in 1976 by Dutch economist Peter Van Westendorp, is used to develop a price range for your products. Van Westendorp’s Price Sensitivity Meter typically asks the target market questions similar to these four in survey form:
The collected data is used to plot points on a price sensitivity map, where the x-axis is the price and the y-axis is the percentage of survey respondents who selected that price point. The intersections of the data points are what help you identify your price range and estimate your ideal price.
The intersection of questions one and two (too inexpensive, and good value) is your point of marginal cheapness (PMC), and the intersection of questions two and four (inexpensive/good value, too expensive) is the point of marginal expensiveness (PME). These two points represent the low and high price limits your customers are willing to pay—also known as the “range of acceptable pricing.”
Note: The Van Westendorp price sensitivity meter does not take competitive pricing into account.
In the 1960s, economists Andre Gabor and Clive Granger developed a pricing technique that used survey research to discover the price elasticity of products. The Gabor-Granger method of direct pricing research asks people in your target market questions like this example:
After considering all of the information about product X, how likely are you to purchase it at Y price?
Using skip logic, if the respondent answers with one of the bottom three (Somewhat likely, Not so likely, or Not at all likely), they would be presented with the same question with a lower price point.
If they answered with one or two (Extremely likely or Very likely), the number of responses would be counted toward a top-2-box score. The percentages of these answers are added together to show the percentage of respondents who are likely to purchase your product.
For example, if 15% answered extremely likely and 25% answered very likely, your top-2-box score would be 40%. 40% of your target market would be likely to purchase your product at the price you listed.
Another way to administer Gabor-Granger price testing is to ask questions like this one:
Based on what you now know about product X, would you purchase this product at $200?
If the respondent answers yes, they are asked again for the price of $225. If the answer is yes, they are asked again for a price of $250. If the answer is no, the maximum price they are willing to pay is $225.
The data collected from the Gabor-Granger method is then used to determine demand at particular expected price points (price elasticity) using data-driven evidence. Just keep in mind that this pricing method does not consider your competition.
Yet another method of pricing research is found in conjoint analysis. Often considered the most reliable pricing strategy, conjoint analysis uses discrete choice modeling to determine the influence that price and product features have on willingness to pay. This is similar to the actual experience of making purchasing decisions while shopping.
Survey respondents are presented with prices and features from a group of similar products and asked to choose which item they would buy based on the comparison. The collected data can be analyzed to determine which price points have the most impact on shoppers.
An example might look like this:
If you were in the market for a new smartphone, which of the following would be most appealing to you?
|Model||Samsung Galaxy A50||iPhone 12 Pro Max||Google Pixel 4a||None|
|Price||$140.99||$1399||$479||I would not choose any|
|Screen Size||6.2 in||6.7 in||6.2 in|
|Storage||64 GB||512 GB||128 GB|
This may be followed by an open-ended question asking why the respondent chose the answer they did.
As you can see, conjoint price analysis is also a measure of what features your customer base is willing to pay for in your product. The next question may look like this:
|Model||Microsoft Surface Duo||iPhone 12 Pro Max||Motorola Razr||None|
|Price||$975||$1399||$1400||I would not choose any|
|Screen||Gorilla Glass||Ceramic Shield||Unknown|
Again, respondents are asked to qualify their answers.
Question sets would continue with varied attributes and price tags to find what price and feature sets are most appealing to shoppers. Beware of overburdening your survey respondents with too many sets. This can lead to confusion and survey fatigue.
Unlike conjoint analysis, monadic price testing presents respondents with only one product in isolation rather than a group of similar products. Your test group is split into subgroups. Each subgroup is presented with the same product but at different prices. They’re either asked whether they would purchase the product at the given price, or they’re given a rating scale referring to the likelihood to buy at the given price.
The data from monadic price testing reveals how respondents react to price in the context of the product description. Pricing is tied to brand value, so this also puts a dollar value on your brand.
However, monadic testing does not usually ask respondents to provide insights about the prices (why a price is too high or low). It also won’t help you determine if you could be charging more than the given price or how elastic or inelastic your pricing is.
There’s no way to price your products or services for maximum revenue without pricing research. Whether you use Van Westendorp, Gaber-Granger, conjoint analysis, monadic testing, or a combination of methods, you need data.
The SurveyMonkey Price Optimization solution can help you obtain the data to set new prices, optimize existing prices, and even personalize your pricing by niche audiences. Let us help you wade through the pricing process!
Collect market research data by sending your survey to a representative sample
Get help with your market research project by working with our expert research team
Test creative or product concepts using an automated approach to analysis and reporting