Pricing research

At the risk of stating the obvious, most people go into business to make a profit. And, as one study by Bain & Company stated, “Nothing affects profits more than pricing.” According to their research, each 1% improvement in realized price leads to an 8% increase in EBIT (earnings before interest and taxes). In short, better pricing = more profits. 

But for smaller companies and startups, the question of price may be a complicated one. In theory, supply and demand set it automatically. But for a business owner who's spent time and money on making a product or service, just letting the market decide won't be enough. 

Fortunately, there are a few research frameworks that can help you narrow down the best price for your product or service. Pricing research allows lets you price your product with the same thought as you used to design it. 

Read on to learn more about pricing research, the major frameworks you can use, and how to go about executing a pricing research study. 

The importance of pricing research

Pricing research is the process of gathering and analyzing data to find the best price for a product or service. It involves understanding consumer behavior, market trends, and competitive pricing to maximize profitability and market share. 

When conducted effectively, it removes the need for guesswork from the all-important question of pricing, instead providing actionable, quantitative data derived from your target audience. 

Obviously, having a great product is key to success. But setting that product at the perfect price point can help the business in a few key ways. Pricing research can help:

• Maximize profitability: Reach the highest possible profit margins while remaining attractive to consumers.

• Enhance a competitive edge: Help understand how competitors price their products and how they position themselves in the market.  

• Understand customer perception: Earn valuable insights into how customers view your product and brand, and align with them. 

• Enter the market: Find the best price point for entering new markets – such as new regions or industries – and launching new products or services. 

• Avoid undervaluation: Avoid underpricing in a way that devalues your brand. 

• Adapt to changes: Pivot swiftly in response to shifts in demand or changing market conditions.

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Pricing research methods

A few frameworks have emerged over the years to help businesses research prices. Each has their own pros and cons, which should be weighed given your particular use case. 

Van Westendorp Price Sensitivity Meter

The Van Westendorp Price Sensitivity Meter (or PSM) measures how consumers feel about your product at particular price points. It’s easy to understand and use, and results in a very actionable pricing range for your product. 

To use the meter, ask users four questions: 

1. Too expensive: At what price would you consider the product to be so expensive that you wouldn't consider buying it? 

2. 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? 

3. Expensive/high side: At what price would you consider the product to be expensive, but still worth buying?

4. Cheap/good value: At what price would you consider the product to be a bargain – a great buy for the money? 

Then, after plotting responses on a chart, where the y-axis represents the percentage of respondents and the x-axis represents the dollar amounts indicated, you can create a range:

• The lower limit of your price range is the intersection of the “too inexpensive” line and the “expensive/high side” line.

• The upper limit of your price range is the intersection of the “too expensive” line and the “cheap/good value” line. 

• The optimal price point is the intersection of the “too expensive” line and the “too cheap” line. 

The price sensitivity meter is easy to use and shows you different prices and suggested best prices. However, it's very subjective and doesn't have any background information, like market competition, production costs, and specific use-case scenarios. 

Gabor-Granger method

The Gabor-Granger method is a pricing research technique that presents people with a series of different price points to determine their likelihood of purchasing at each price. 

First, they’re asked if they’d buy the product for, say, $20. Then, if they said yes, they may be asked if they’d buy it for $25. If they said no, they may be asked if they’d buy it for $15. This continues throughout the acceptable price ranges to create data about the price point at which consumers will likely buy your product. 

The Gabor-Granger method is useful when you want to maximize revenue and profit, as it actively scales toward the high end of where consumers would purchase. It’s also fairly easy to pull off: it doesn’t need to be structured meticulously, as it works in a logical sequence. However, as with the PSM, it lacks context, including product features, cost structures, and market conditions. 

Conjoint analysis

Conjoint analysis is a double-edged sword: highly accurate, but complex to pull off adequately. It evaluates consumer preferences by presenting them with multiple product scenarios, each combining different combinations of attributes and price points. 

The process by which these combinations are found is called discrete choice modeling. It reduces the many possible variables that could affect pricing to a series of discrete choices that you can test with consumers. 

This method is best understood via a hypothetical scenario. Let’s say you’ve created a new type of productivity software. You’re curious about a few variables: monthly pricing, storage capacity, and customer support. These attributes could then be combined in a variety of configurations. 

One customer might be asked which of the following options they'd purchase: 

The next customer would get a different configuration. Through repetition, you may find that pricing is the most important attribute, with a strong preference for the $20/month price point. 

Conjoint analysis provides detailed insights and a rich understanding of the trade-offs consumers are likely to make. However, it’s complex to design, implement, and analyze. 

Monadic pricing

For monadic pricing research, you first split your respondents into different groups and then show each one a different price for the given product. Unlike conjoint analysis, there aren’t a bunch of variables being tested here: just pricing. So your product's features may be presented alongside competitors’ products, features, and pricing. Each group gets the same set of options, with the only change in the presentation being your product’s proposed price. This framework allows you to measure how respondents feel about your product as it would appear in the marketplace. 

Monadic pricing is scientifically sound and realistically recreates the shopping experience in the marketplace. However, it requires a large number of respondents to be statistically viable, as each price point must be tested against a valid sample size. 

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How to conduct pricing research

All of the frameworks above will provide you with lots of information about how customers feel about your product. 

Let’s show how you might roll out any of these research processes. To make things more concrete, let’s continue with our productivity app example from above.

1. Define your objectives

Start by being very clear internally about what you want out of this research. Is it a competitive analysis, an entry point to a new market, or to better understand overall pricing sensitivity? For the productivity software, let’s say it’s a hard launch into the market. 

2. Define your target market

Figure out who your potential customers are, including their demographics and purchasing behaviors. Let’s say the productivity software is fairly targeted, focusing on freelance therapists. 

3. Analyze your competitors

No matter which research framework you use, you’ll need some context about what the competition is doing. In this case, you’re looking for pricing structures. For the freelance therapist productivity software, maybe there are only two competitors, and neither of them focuses on this audience as closely. 

4. Select which pricing research methods you’ll use

Now you’ll pick the framework you want to use. Conjoint analysis is certainly reliable, but maybe because the mental-health therapist productivity software category is small, you can focus more on the Gabor-Granger method to maximize profits. This step is also the right time to determine which tools you’ll be using to deploy your tests. Lyssna could be used to run a preference test in the Gabor-Granger example, but targeted surveys could also be used to recruit participants and test the other examples listed above. Additionally, user interviews could help add rich qualitative context alongside the quantitative data derived by the research frameworks above. 

5. Execute your study

Now you can design your study and share it with a selection of your target audience. For our productivity software, let’s say we tested with 100 freelance therapists using the Gabor-Granger method. 

6. Analyze your data

You likely have a large grid of numbers on the back end of your study. For our productivity software example, this may result in a simple line chart (or demand curve) showing the percentages of people who are willing to buy at each price point. Voila: A surprising peak of $25 per month appears to be the consensus, with a stark dropoff at $30. 

7. Refine and implement

If this study is satisfactory, you can present the findings to your team. From there, it can be refined and iterated for further testing or implemented into marketing and other materials before going live in the market. 

Pricing research best practices

You should be ready to roll on your pricing research journey. Best practices to keep in mind include: 

• Use realistic scenarios: Earlier user research should highlight some of the use cases likely in your target audience, as well as possible competitors, so make the most of this contextual information. 

• Evaluate the price of the pricing research study itself: For startups and small businesses, you want to undertake research that fits your team’s capacity. If you think it’ll be important to iterate, factor that in, too. 

• Minimize bias: Avoid leading questions, be transparent with respondents about the purpose of the study, and have peers review your process and results. 

• Don’t forget to include the option for respondents to buy nothing: This is particularly important in conjoint analysis and monadic pricing – your results won’t be valid if “none of the above” isn’t one of their options. 

After all, your greatest competitor may be the option for someone to not purchase anything at all. However, with the right pricing research, you can minimize the chance of this happening.