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The Importance of Pricing

One of the most challenging decisions to make when launching a new product or service is determining its price point. Pricing is a company's most efficient profit lever. Pricing a product too high will negatively impact demand, while pricing it too low is leaving money on the table. Finding a balance on pricing is difficult, but with the help of survey research, an organization will be able to come to market at the optimal price. An organization can maximize its revenue optimization, unit sales, and brand value (value perception) with correct pricing. 

Determining Pricing  

The first step when determining pricing for a product is to define its users - the customer. Begin by making an educated guess to map out the people, organizations, size of organizations, and markets in which your product would be used. Within each segmented group, make educated guesses as to what that group does and does not value, their willingness to pay, and overall acceptance of your product into the market. This segmentation will help distinguish between the different markets when organizations begin their pricing surveys.  

After identifying specific customer groups to target, the next step is determining how these groups purchase and what they are looking for in a product. This cannot be done by simply analyzing the current market or using competitors' pricing for comparison. Instead, the most effective way to determine pricing is to use feedback from real-world customer engagement and through pricing surveys. Pricing surveys allow businesses to quickly collect and analyze information from (potential) customers and then implement it. One thing to note is that pricing should never be set in stone. Corporations should constantly analyze the market and their customers and adjust prices if needed. 

Once segmented, the next step is to reach out to potential clients with pricing surveys. Below is a collection of the most popular types of pricing surveys. When looking at the different types of surveys, they can be broken down into two main types: direct and indirect techniques. Direct techniques assume that the interviewee understands what the product or service is and what it is worth. Indirect techniques, usually conjoint or discrete choice analysis, combine the price with other product or service attributes, then extract feelings on price from questions about the total package.

Pricing Surveys

Van Westendorp Price Sensitivity Meter - Direct

The Van Westendorp Price Sensitivity Meter (PSM) is one of the most prevalent market techniques for determining consumer price preferences. It bases a series of questions on two critical elements: value metric and willingness to pay. Value Metric is how the user will be charged; per use, per visit, per view, per click through, etc. Willingness to pay focuses on determining threshold pricing – how much your customer is willing to pay (price elasticity). The four questions the Van Westendorp pricing model utilizes are: 

1. At what price is this way too expensive that you would never consider purchasing it? 
2. At what price is this starting to get expensive, but you'd still consider purchasing it? 
3. At what price is this a really good deal (you'd buy it right away)? 
4. At what price is this way too cheap that you'd question the quality of it?

With the data gathered from this survey create a price elasticity curve, like the one pictured below. From this curve, you will determine how much sales are gained or lost at a specific price point. 

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Conjoint Analysis Survey (CAS) - Indirect

A Conjoint Analysis Survey is one of the most commonly used techniques for optimizing product features and pricing. It mimics the trade-offs people make in the real world when making choices. In conjoint analysis surveys, you offer your respondents multiple alternatives with differing features and ask which they would choose. This trade-off process reveals which features are most preferred and drive willingness to pay.

The first step is to break the product into attributes and levels. For example, if examining vehicles, break down their attributes into brand, engine, price, and type, etc. Next, survey respondents are shown 10-20 conjoint questions and asked which (if any) of the products they would choose if these were the only ones available when they were shopping. Within each question, there are 3–5 product profiles they can choose from. Each product profile includes multiple conjoined product features (prices, size, color, type, etc.), each with multiple levels (small, medium, large).

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Finally, all of the data collected from the surveys are compiled and aggregated into a statistical model. By independently varying the features that are shown to the respondents in each question, the analysis can statistically deduce what product features are most desired and which attributes have the most impact on choice.

Conjoint analysis doesn't allow people to say that everything is important, which can happen in typical rating scale questions. Rather forces them to choose between competing realistic options. You gain information that far exceeds standard concept testing by systematically varying product features and prices in a conjoint survey and recording how people choose.

Discrete Choice Modeling (DCM) - Indirect 

Discrete Choice Modeling looks at the choice customers make between products and services. By identifying patterns in customers' choices, DCM models show how different consumers respond to competing products. This allows for the examination of the shared impact of product configuration, service bundling, pricing, and promotion on different classes of customers. 

The first step in DCM is to identify the product's key buying factors through focus groups. Focus groups explore consumer motivations in detail and let us develop hypotheses about how consumers go about purchasing products. They also allow us to hear customer impressions of products, programs, services, institutions, or competitor products. This can help develop new ways to communicate a product's value to a customer or develop creative product concepts.

The next step is testing the hypotheses from the focus groups. This is done through a set of choice experiments. In these experiments, a hypothetical marketplace contains a set of products and asks the person being surveyed what they would do: buy the product, do not buy the product, or buy it at a later date. Then the pricing and product characteristics are changed, and the interviewee is asked to choose again. Once all of this data is collected, it is inputted into a statistical computer model. If the experiment was done correctly, the modeling should yield answers to the following:

1. What are the key markets segments for the product?
2. What is the optimal price point, and how price-sensitive are customers? 
3. How much is a brand name worth to a product?
4. What advertising or promotional activities appear most effective?
5. Where should the company target its efforts? 

A typical DCM project takes at least five weeks to execute and ranges from $25,000 to $50,000+. The price can quickly balloon even higher, especially for new products with no market precedent. This could require additional focus groups, which can be thousands of dollars apiece. While being expensive, Discrete Choice Modeling can be extremely informative. Historically, it has returned large gains because the analysis allows firms to precisely position and price both products and services at launch. 

Monadic Price Testing - Direct

Monadic price testing focuses on testing a person's response when they see a price and are asked the state of their purchase intentions ("Would you be willing to buy this for $x?"). The price increases or decreases until a pricing threshold is determined. This process is repeated over and over with tens, hundreds, or even thousands of respondents. The monadic price testing model can be useful in creating a demand curve if there is a large enough sample and multiple price points are given. Monadic testing can produce inaccurate results if the prospective purchaser's value view is wildly different from the vendors. However, monadic price testing can be improved if the surveyor asks open-ended questions for comments. 

Gabor Granger Technique - Direct

The Gabor Granger Technique attempts to determine if it is possible to increase prices without a drastic decline in sales. It looks to uncover at which prices point(s) consumers' willingness to spend disproportionately increases or decreases.  First, the participants' willingness to buy a specific product or service is surveyed when they provide the probability they "would buy the product or service at a reasonable price". Those who show a willingness to buy are then presented with a series of defined prices (4 or 5 different prices), starting with the highest. Participants not willing to purchase are again presented with the second-lowest price and so on until they demonstrate a willingness to purchase or all pricing options have been shown. 

Sources: 

https://aytm.com/blog/pricing-strategy/

https://review.firstround.com/the-price-is-right-essential-tips-for-nailing-your-pricing-strategy

https://cxl.com/blog/pricing-research-volition/

https://review.firstround.com/our-6-must-reads-on-pricing-a-product

https://sixteenventures.com/develop-pricing-strategy

https://neilpatel.com/blog/5-psychological-studies/

https://openviewpartners.com/blog/saas-pricing-resource-guide/

https://www.onstartups.com/learn-by-example-38-saas-startup-pricing-pages-analyzed

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