As a product marketer, identifying the right price for your solution is a pillar of go-to-market strategy. Set your prices too low, and you may leave money on the table. 

Pricing your solution too high can lead to a competitive disadvantage or shut out an important segment. 

This article provides a high-level overview of standard pricing research techniques to guide pricing strategy and set price points. 

When to conduct formal market research to guide pricing strategy

Most pricing evaluations start with a review of competitors’ pricing. Your company’s competitive intelligence team or platform will typically have some data on competitive pricing. However, the data are sometimes insufficient to develop an effective pricing strategy. 

Often, an accurate price is not publicly available, especially in more expensive solutions that involve sales reps, discounts, and negotiations. In new solution categories, vendor pricing may not have stabilized yet. 

Or, when creating a slimmed-down or beefed-up version of a solution, it may not be clear how far you need to lower prices or how much you can increase them.

In these situations, conducting a pricing research study can help you better understand the market’s perception of the value of your solutions and its willingness to pay (WTP).

The 3 critical insights to guide pricing strategy

Pricing data can be gathered with several methodologies, ranging from large-scale quantitative surveys of hundreds of customers/prospects to a dozen in-depth interviews with prospects. 

Regardless of the data collection approach, pricing research should be designed to provide these three categories of insights:

  • Current pricing context: What the market pays today.
  • Willingness to pay: A pricing exercise that explores willingness to pay (e.g., some version of a Gabor Granger question set).
  • Optimal price range: A pricing perception analysis, which helps identify the optimal price range (e.g., components of Van Westendorp Pricing Sensitivity meter).

1. What the market pays today (Market context)

What companies are doing today provides an important reference point to understand how much the market is willing to invest in solutions like yours.  To understand market context, you need to know:

  • What solutions does the target market use today?
  • Are they using an indirect solution such as a spreadsheet or a module of another system? 
  • Are they investing in a comparable solution? A competitor?
  • How much do they spend on those solutions? 

The answers to these questions indicate the relative importance customers and prospects place on the activities related to your solution category and their perceived ROI on the solutions they use. 

Also, the current solution serves as their reference point for new solutions. Knowing this starting point helps put your solution in context. Will it be perceived as a premium product, in which case you will need to ensure that your sales and marketing materials can help buyers justify the additional cost. 

Our research finds that while B2B buyers will pay more for a solution that is better than what they have today, it is incremental.

Buyers typically will not buy solutions that cost multiples (2X, 3X, etc.) over what they currently pay, even if buyers acknowledge that the new solution is superior to what they have in place. Conversely, will your solution be viewed as cost-neutral or even a bargain?

When asking B2B buyers what they pay, one important guideline to keep in mind is not to apply an artificial level of precision to the data. B2B buyers are human and prone to understating what they pay.

For example, they may have a general feel for what they pay (e.g., reporting the cost is about $25K annually when the actual cost is $27K). 

Or they may be fairly accurate about the base license cost but fuzzier about the fees for customizations or additional modules. The data they provide are accurate when treated as a scope-of-magnitude estimate; you need to use judgment and inference to refine it from there.

The next step in identifying the right pricge point is to collect direct feedback on your pricing. Some advanced trade-off modeling techniques, such as conjoint, can help refine costs. However, for most B2B offerings, two standard and straightforward pricing research methodologies provide the insights needed.

2. Willingness to Pay: Gabor Granger Questions

The Gabor Granger (GG) questions are a straightforward, useful approach to identify the market’s price tolerance. The first step is to identify three price points for your solution/service:

  • The lowest you can realistically price your offer at and still make a profit.
  • The price point you think is a realistic price.
  • The stretch price point is the most you feel you could charge for your offer.

Some teams gain useful insights simply by setting their price points in preparation for a research study– it is the first time they have systematically thought through the pricing.

Once you have identified these three price points, ask customers and prospects to rate their willingness to pay for (or at least consider) your solution at each price point. 

Start with your stretch price – the highest one. If they will not pay for your solution at your stretch price, ask if they would consider it at the realistic price point. 

Lastly, ask those who are still unwilling to invest at your realistic price about their interest at the lowest price point. 

Adding additional price points along the continuum (e.g., asking about four or five price points instead of three) can help to identify nuances along the continuum. Keep in mind that the effectiveness of testing more than three price points in the GG questions diminishes as research respondents become aware of the protocol. 

Analyzing the results provides two insights into the marketplace’s willingness to pay.

  • The first is an estimate of the percent of the market that would be willing to invest at any given price point. 
  • The second is a potential flat point in pricing elasticity – the point where increasing or decreasing prices has little impact on the number of buyers willing to consider the solution. 

Willingness-to-pay data often informs TAM or SAM analysis. If you plan to do this, keep in mind the following two recommendations. 

First, ensure you include questions about when the buyer plans to consider an upgrade/replacement. They may be willing to spend $50K on a solution like yours, but if they recently bought a new solution, they will not be ready to switch again for a few years.

In addition, a standard research practice is to apply a discount factor to account for the delta between stated intentions in a survey and actual behavior in the real world. 

3. Optimal Price Point: Van Westendorp Price Sensitivity Meter

Another useful pricing methodology is the Van Westendorp Price Sensitivity Meter (PSM), which focuses on price expectations and acceptability rather than willingness to pay.

The PSM provides a useful perspective on perceived value because the GG WTP questions are inherently influenced by the implied question about whether they will buy, even if asked hypothetically.

As an analogy, if you asked people how much they would be willing to spend on a house, their answer would be influenced, at least subconsciously, by how they feel about the idea of buying a new house today. 

However, most people know how much a house in their neighborhood should sell for, even if they are not in the market for or selling their house. The PSM explores the latter and is a bit less of a loaded question.

The PSM asks about price points for solutions in four scenarios: When is the price…

  • So cheap it raises quality concerns
  • A bargain
  • Getting expensive
  • Prohibitively expensive

The wording of these questions can be adapted to fit the solution as long as the spirit of the question remains. Plotting the results provides the optimal price range, meaning the price point that will appeal to the broadest perception of the market.

Prices above this optimal range will be acceptable to an increasingly narrow slice of prospects that view the solution as a premium product. 

When your research consists of a qualitative data set, the average of the Getting Expensive data points makes for an effective list price for solutions that involve sales negotiations and discounting. 

We recommend combining the Gabor Granger and Van Westendorp approaches because they help mitigate the limitations associated with each approach and it provides a more accurate read on willingness to pay and price elasticity. 

It is important to note that both approaches assume that the audience is familiar enough with the solution or category to make reasonably informed judgments about its value and their company’s willingness to pay. As with all market research, pricing research requires effective screening to ensure data are collected from the correct target audience.

Insights and use cases

The insights from these three categories of data (What they pay today, Willingness to pay, and Acceptable price points) can help inform your pricing and go-to-market strategies by identifying:

  • How your pricing compares to competitors and the market’s expectations
  • Which market segments to avoid and which segments are most likely to find your pricing acceptable
  • Potential ways to optimize your price point to win market share or use a skimming strategy
  • The sales and market challenges you face, e.g., will you need to educate your buyers to help them justify the cost?

What about Conjoint analysis?

If you have some experience with pricing research, you may be asking yourself, “What about conjoint?” Conjoint analysis and its kin are commonly used for packaging and pricing research – especially in consumer research.

The distinguishing feature of these methodologies is that they force respondents to choose between a series of features or hypothetical product configurations in a series of trade-off choices. The trade-off exercise better simulates real-world buying decisions than rating or ranking scales.  

As powerful as they are, trade-off techniques have limitations. At their core they work best for products with a small set of key features that are clearly defined. Examples from the consumer electronics world include weight, battery life, size, # of ports, etc. 

The reliability of conjoint analysis diminishes rapidly if more than six features are included in the exercise. Many B2B products have dozens of features and functionality, which is too many to include effectively in a conjoint exercise. Features can be grouped into broader categories, such as integration and functionality bundles. 

However, rolling up features into a category adds ambiguity around what B2B decision-makers are responding to when they trade one thing off against another—you lose the specificity of the feature trade-off the technique is especially useful for.

We also find that when B2B product marketers need market research, they often have multiple informational needs to address in a single study. 

Unfortunately, the number of trade-off tasks required in a conjoint or similar analysis tends to use up all the time available in a survey, leaving little time to cover other questions. 

These points about conjoint analysis are not criticisms, just the requirements of the technique. Conjoint is a great tool and we use it when it fits the project goals. However, in our experience, a more straightforward approach provides the pricing insights most B2B solutions providers need.

Isurus Market Research delivers research-based insights for product marketers in B2B SaaS companies to inform GTM strategies. To learn more about how we help with pricing strategies or address other product marketing questions, visit our website or contact us here.