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Cracking the Code of Price Optimization: Strategies for Success

Every product and service that enters the market has its perfect price – the price that precisely balances perceived value and customer price sensitivity in a way that maximizes sales, enhances demand, and ensures success against competitors.  

 

Finding this price is a critical step in any go-to-market strategy, but the process can be challenging without the right strategic approach. 

 

In this article, we’ll take a closer look at the most effective price optimization strategies, why they’re important, and how to incorporate them into your go-to-market strategy.

 

What is price optimization?

Price optimization is a predictive market research approach that aims to determine the ideal price point for a product or service. Using a variety of methodologies and data-driven insights, market researchers calculate the price point that will maximize sales by perfectly balancing consumer price sensitivity and perceived value, while optimizing profitability.

 

The price optimization process tests various price point and product or service feature combinations among target consumers and key market segments to determine the price that is most likely to drive purchase. This ideal price should factor in product or service costs, competitor pricing, market demand, and broader economic considerations to predict which price point will capture the most value.

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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:

optimization_1

 

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:

  • At what price would this product be so cheap you’d doubt its quality and not consider it (“too cheap”)?

  • At what price would this product be a bargain, or a great buy for the money (“acceptably cheap”)?

  • At what price would this product seem expensive, but you’d still consider purchasing it (“acceptably expensive”)?

  • 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: 

 

optimization_2

 

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. 

 

optimization_3

 

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.

 

 

FAQs

Why is price optimization important?

Bringing a new product or service to market at the right price point can make or break its success. Too cheap, and consumers may perceive the product or service to be of poor quality, influencing their purchasing decisions (and your bottom line). If the product or service is perceived as too expensive, it may negatively impact a consumer’s likelihood of purchase. Product price optimization involves striking exactly the right balance between perceived value, purchase intent, and profitability. It’s a precise science and requires advanced market research and analysis methodologies to identify the ideal price point that drives sales, without compromising profitability.

What factors influence price optimization?

There are a number of factors that influence price optimization, including:

  • Market demand

  • Economic climate

  • Consumer behavior and preferences

  • Competitor activity and pricing

  • Perceived brand value

  • The desirability of various features and attributes

And more.

How often should prices be adjusted or optimized?

This also depends on a number of variable factors. Industry activity, competitor activity, economic factors, shifting market trends, consumer behavioral patterns, changing production costs, and sales data should all be closely monitored to determine whether prices need to be adjusted or optimized. 

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