The complexities of price optimization
Landing on the right price during pricing optimization is a notoriously complex process, and the stakes are high. If the product or service goes to market at a price point consumers feel is “too cheap”, it may be perceived as low-quality, resulting in lower sales. “Too expensive”, and consumers will be unlikely to purchase it either. In order to make an accurate prediction, researchers need to factor in additional complicating factors like consumer behavior and preferences, potential fluctuations in demand, price elasticity, cost considerations, and broader dynamic market conditions, both current and future.
The price optimization process also relies on the accurate, extensive analysis of large data sets, including historical sales data, competitor pricing data, qualitative and quantitative data collected from consumers, and more. This requires an experienced market research provider with an integrated strategic approach and the advanced statistical tools needed to get the job done.
3 effective methods for setting optimal prices
There are three primary methods used to identify ideal prices for products and services, all three of which are offered by CRG, supported by the HUUNU prediction market platform and industry-leading predictive survey methodologies.
Conjoint/Discrete choice price optimization method
The conjoint/discrete choice method for pricing optimization most closely mimics the way consumers make purchasing decisions in the real world. Variable key features and attributes of each product and service are presented to the consumer in combination with a corresponding price point. These different product and service profiles are systematically rotated, and consumers are asked to choose which product or service they would choose in each carefully presented scenario.
A typical conjoint/discrete choice survey question may look something like this:
Depending on how consumers react to feature and price changes, researchers can apply models to accurately determine the consumers’ price sensitivity (i.e.: the price elasticity of the product), along with their Willingness to Pay (WTP), or the highest price they are willing to pay for a particular product or service. With this data in hand, it’s possible to determine how demand changes relative to changes in price and features for the product or service under testing.
Conjoint/Discrete choice price optimization processes require the largest sample sizes among the three methods featured here – usually about 300 to 800 participants. The surveys also take longer to complete, averaging about eight minutes per survey, and require commercial statistical analysis software to process. However, Conjoint/Discrete choice surveys deliver a huge amount of rich data, and allow for the testing of thousands of product/price combinations in a single survey, delivering comprehensive, accurate results.
The Van Westendorp price optimization method
The Van Westendorp price sensitivity meter is the original price optimization method, first developed in 1976. The method asks consumers four questions about a particular product or service:
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At what price would this product be so cheap you’d doubt its quality and not consider it (“too cheap”)?
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At what price would this product be a bargain, or a great buy for the money (“acceptably cheap”)?
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At what price would this product seem expensive, but you’d still consider purchasing it (“acceptably expensive”)?
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At what price would this product be too expensive for you to consider (“too expensive”)?
Van Westendorp argued that, by plotting the answers to these four questions onto a graph, you’d reveal the acceptable price range for that particular product, as shown here:
In 1993, Newton et al. added what’s now called the Newton-Miller-Smith extension to the Westendorp price optimization method with the inclusion of five additional purchase intent questions (“definitely would purchase”, “probably would purchase”, “might or might not purchase”, “probably would not purchase”, and “definitely would not purchase”). This allows for the development of a demand curve at each of the four price points, which yields an additional dimension to the data.
While the Westendorp method is the quickest approach, taking only a few minutes to complete, it typically only allows for the testing of one product or service and only a few variations at a time.
The Gabor-Granger price optimization method
The Gabor-Granger price optimization method is based on a simple premise. Consumers are asked if they would buy a specific product or service at a particular price. If they answer yes, they’re asked if they would still buy it at a higher price. If they answer no, then the question is asked again, at a lower price. In this way, the consumer comes to their “final price”, an optimized price point for the product or service.
Like the Westendorp method, this approach is low-input, with surveys only taking a few minutes to complete.
For product price optimization, choose CRG
CRG offers a comprehensive, integrated approach to price optimization, backed by industry-leading prediction market and predictive survey methodologies.
Depending on your needs and objectives, CRG combines Conjoint/Discrete choice, Westendorp, or Gabor-Granger methodologies to help you determine the ideal price point for your product or service.
For more complex products or services with multiple possible attributes targeted at multiple market segments, we deploy the Conjoint/Discrete choice method with a predictive survey methodology to predict market response to different pricing methodologies.
For simpler pricing strategies aimed at understanding consumers’ price sensitivity thresholds and value perception, we deploy the Westendorp method in conjunction with the HUUNU prediction market platform or a predictive survey.
If you’re looking for more direct price feedback regarding customers’ Willingness to Pay and price sensitivity range, we’ll employ the Gabor-Granger method, along with a predictive market research survey approach.
The result is a comprehensive, expert solution that delivers the accurate insights you need to drive data-backed strategic decisioning regarding the optimal price point for your product or service. This can be within an established category, or in a never-before-seen breakthrough category.
For an industry-leading product price optimization solution, get in touch with our team today.
