How to Use B2B Research in Developing a Value-Based Pricing Strategy


A critical decision for any business developing new and differentiated products is determining the proper price point.

A critical decision for any business developing new and differentiated products is determining the proper price point. Price directly impacts the perceived value and quality of your product, can limit distribution options, is a crucial component of brand perception, and drives product profitability. So there are many compelling reasons to “get it right.” 

A common mistake in B2B markets is setting pricing based on the cost of the product plus a desired margin amount or percentage.  The problem with this method is that the market does not care about the margin a business needs to be profitable. Overall perceived value is what drives a customer’s purchase decision, and to properly price a product one must understand the dollar value or worth the customer places on the product attributes (what the product delivers).

Unfortunately, pricing research can be misleading if sound methodologies are not used. However, there are statistically proven research techniques that can provide the insight needed to develop the correct go-to-market pricing strategy intelligently. Two of these are conjoint analysis and the van Westendorp Price Sensitivity Meter.

Conjoint Analysis

Conjoint analysis is a survey technique that forces respondents to make choices between features for products just as they would in an actual purchase decision. As he/she does so, the respondent provides implicit information about the value they place on each feature (e.g., color) and the level of each feature (e.g., blue, green, yellow). Conjoint can be used to estimate preference and, by combining results across respondents, estimate market share, and provide pricing insight.

A product or service is first described using key attributes. For example, a pair of sunglasses can be described in terms of frame style, color, brand name, degree of polarization, price, and warranty. Each attribute consists of several levels. In our example, the style of sunglasses may be classic, fashion, lightweight, and rimless.

Respondents are shown a set of descriptions (or even actual products) created from a combination of levels from the different attributes and presented at various price points. They are asked to choose from, rank or rate each set of products.  As the number of combinations of attributes and levels increases, the number of profiles increases exponentially. Factorial design is used to reduce the number of profiles to be considered, without reducing the statistical value of the results.

Full-profile conjoint analysis presents several complete product descriptions to the respondent for acceptability or preference evaluations. Each product profile is derived using experimental design tools that control the number of times each attribute and each level appears. The respondent evaluates the profiles in terms of their preference or likelihood of purchase.

Adaptive conjoint analysis varies the choices presented to respondents based on their preference – the software learns as the respondent makes choices. Every succeeding product choice is more competitive and is a tougher choice for the respondent. Consequently, adaptive conjoint analysis reduces the survey length.

Choice-based conjoint analysis (CBC) is the most common form, requiring respondents to choose their most preferred full-profile concept from sets of 3–5 full profile concepts. This design is thought to simulate an actual purchase decision more closely than other conjoint choice exercises. The output provides excellent estimates of the value of each level and can be used to design products not included in the research and to forecast expected share.

Price is treated as an attribute in the conjoint design. The results of conjoint are “part-worths” or value units that are determined for each level of each attribute. The researcher can compare part-worths for one combination of attributes (one product) versus another. These relative values can also be used to predict market share.

Van Westendorp Price Sensitivity Meter

The Price Sensitivity Meter helps determine a psychologically acceptable range of prices for a single product or service. It is a frequently used pricing research method proposed by the economist Peter van Westendorp in the 1970s. It is particularly useful when:

  • You want to understand what price range the market considers to be fair for your product.
  • The competitive benchmarks are extreme (there is no other product on the market like yours, or the number of competitive offerings is very large).
  • You need fast, directionally correct results.

The Van Westendorp pricing model is based on a series of four questions designed to establish boundaries around what would be considered a fair price for a product or service. By looking at the percentage of respondents that believe a given price is too high or too low, the model suggests that the best price point can be established.

The four questions are:

  • At what price would you consider the product to be so expensive that you would not consider buying it? (too expensive)
  • At what price would you consider the product to be priced so low that you would feel the quality couldn’t be very good? (too cheap)
  • 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? (not a bargain)
  • At what price would you consider the product to be a bargain—a great buy for the money? (a bargain)

The frequency line graph of responses to these four questions should result in a diamond shape area of intersection,  as shown in the example graph below. The four points of the diamond are labeled as follows:

Point of Marginal Cheapness (PMC) – The point where more sales would be lost due to questionable quality than would be gained from bargain hunters.

Point of Marginal Expensiveness (PME) – The point above which cost is a serious concern, where it is felt that the product is too expensive for the value derived from it.

Optimum Price Point (OPP) – The point at which the percentage of customers thinking the product is too expensive is the same as those who believe it is so low that the quality is questionable.

Indifference Price Point (IPP) – Point at which the same percentage of customers feel that the product is getting too expensive as those who feel it is at a bargain price.

value based pricing strategy

The point of marginal expensiveness – rather than the optimal price point – is the price to be recommended. Above this point, demand for the product almost always drops off. In the chart above, that is the point to the right of the diamond, at the intersection of the yellow and green lines.

Conjoint and Van Westendorp are two proven research tools that can provide the market information needed to develop winning pricing strategies that will enhance both short term and long term product profitability and market share.

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