I have conducted various market research projects throughout my career. From my perspective, pricing research is one of the most interesting types of market research.

When recommending a product’s retail selling price, we need to consider several key factors:

• Company’s gross margin and sales volume targets
• Consumer willingness to pay: Can retailers successfully sell the product at a particular price point?
• Price perception: How do consumers perceive the product at a given price? For example, are sharp price cuts appropriate for luxury brands?

It is essential to consider consumers’ reactions to price changes.

So, how can we understand these reactions? There are several approaches.

Before you scroll down, don’t worry. I will provide general ideas about each technique without delving into technical details or algorithms in this article.

Van Westendorp Price Sensitivity Meter (PSM)

PSM is a simple technique for identifying a product’s optimal price range as consumers accept.

This method involves asking four key questions in a survey:

• Too expensive: At what price would you consider this product too expensive that you wouldn’t even consider buying it?
• Expensive: Then, at what price would you consider this product still expensive, but you start to give some thought to buying it?
• Cheap: At what price would you consider this product a bargain – a great deal for the money?
• Too cheap: At what price would you consider this product too cheap that it would make you question its quality?

Using the data from these four questions, we can make the following cumulative frequency plot to analyze the results.

We can determine a product’s optimal price range by analyzing intersections of the following lines:

• Lowest accepted price: The intersection of “Too cheap” and “Expensive” responses.
• Highest accepted price: The intersection of “Too expensive” and “Cheap” responses.

PSM is a straightforward technique for identifying a product’s optimal price range. There are a few considerations before using it in a survey.

First, the price range is obtained based on respondents’ claimed answers, which may not always reflect actual buying behaviors. Respondents may tend to provide lower prices to the four questions.

Second, the price range heavily depends on consumers’ sensitivity to price. In categories where consumers are less price-sensitive, PSM may yield a wider optimal price range.

Discrete Choice Modeling (DCM)

DCM is an indirect technique for researching pricing. In a survey, respondents are presented with different choice tasks that simulate real-life purchase scenarios. Each task includes various products at different price points.

Respondents can choose which product(s) they want to buy in each scenario, how many they wish to buy, or opt not to buy anything at all.

The collected data is analyzed using a simulator, which allows us to estimate how changes in price affect a product’s revenue, observe shifts in volume share, and determine where gains or losses originate.

Beyond pricing, DCM also supports product innovation by identifying the key attributes that drive consumer choices.

The good thing about DCM is that it is an indirect technique. Instead of respondents explicitly stating how much they are willing to pay, their purchase behavior reveals the optimal price point.

This technique relies on a few key assumptions. We assume that all products in each scenario have 100% awareness and distribution, as well as zero or equal marketing efforts across all products.

Actual Retail Data Analysis

If retail data by store is available, we may leverage marketing science to analyze how consumers react to price changes.

This method relies on consumers’ actual purchase behaviors.

When we use this method, there are a few important considerations.

This analysis requires a substantial amount of input data, including the actual selling price and sales volume of both the target product and its competitors, ideally on a daily basis and at the store level.

On the other hand, some uncontrolled external factors can influence the results, such as:

• Stockouts: If a product is out of stock, retail data does not reflect actual demand.
• Seasonality: Sales fluctuations occur naturally, such as increased ice cream sales in summer.
• Temporary promotions and merchandising efforts: A price drop alone may not boost sales if a competitor invests heavily in trade marketing or secures a better shelf position.

Lastly, determining the optimal price point of a product can be challenging if its price fluctuates only slightly in the historical data.

Final words

I hope this article provides you with a quick overview of how pricing can be researched.

As a gentle reminder, the final pricing decision should take into account factors beyond consumer behaviors, such as gross margin and sales volume targets.

If you want to discuss this further, let me know.

Vincent

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