PSM — Price Sensitivity Meter — Digdata
PSM — Price Sensitivity Meter	Zoia	2020-10-08T12:53:34+00:00	
Price is one of the most important elements of company’s strategy. The price informs consumer about positioning and properties of the product. This means that it plays not only economic, but also communicative role.
To ensure that the price does not constrain the products promotion on the market, it is necessary to build a pricing policy, taking into account the perception of the price by consumers themselves. This requires constant research of consumer’s price expectations when designing pricing strategies.
When you might need a price study
Finding optimal price of the goods. Price Research helps to identify the optimal price for a product, taking into account psychological characteristics of consumer, brand image, competitive environment and pricing policy of competitors.
Assessment of consumer sensitivity to price changes. When setting a price for a new product or changing the price of an existing product, it is important to correctly predict possible reaction of consumers.
Forecast of changes in demand for different scenarios of price changes. Price is one of the most important factors that influence the purchase.
What Price Research methods do we use?
There are direct and indirect methods of price research.
Direct ones are based on obtaining information about customers’ preferences of a particular price level, as well as their expected behavior. An obvious problem with direct questions is respondents’ deliberate or unintentional deception. The purpose of the interview is usually obvious to them. We use the following methods: Price Ladder, Price Sensitivity Measurement.
Indirect methods are more accurate but more difficult to implement. Indirect methods of studying prices tend to hide from the respondent the logic of the methodology and the purpose of the study in order to maximize the sincerity of the answers. We use the methods of Brand Price Trade Off and Conjoint analysis.
Price Ladder. When using the Price Ladder method, we show the respondent a description of the product and a certain price for it.
The respondent answers, how likely it is that he buys a product for a specified price, using a 5-point scale of preferences.
«How likely is it that you buy such a product at the best price for you?»
«How likely is it that you buy such a product at the price of __ UAH per 1 package?»
Then we show the respondent the same product at a different price and ask the same question again.
The process can be repeated until we reach a proper number of price gradations. The result is a percentage reduction in readiness to buy at each price point.
Determination of product price sensitivity. We determine the optimal product price using Price Sensitivity Meter (PSM):
Respondents are asked to answer 4 key questions regarding their price expectation for a product or service:
«At what price does this product seem too expensive for you and you refuse to buy it?»
«At what price does this product seem so cheap, that you doubt its quality and refuse to buy?»
«At what price does the product seem expensive to you, but you still are willing to buy it?»
«At what price does the product seem inexpensive, and you still are willing to buy it?»
As a result, we get a graph that shows the following:
Best Price: The point where the least people reject a product because of its high price.
Lowest Price Point: marks the minimum limit of the acceptable price range.
Point of Marginal Cost: marks the maximum end of the acceptable price range.
Modeling the price shelf. The method makes it possible to predict the behavior of buyers at each step of the price increase.
We put the respondent in a real purchase situation. We give him several products to choose from at a certain price.
Then the price of the selected product rises (or the price of other products decreases) and the respondent should make a choice again.
If the price changes according to the scenario of the real market situation, the research results are predictive in terms of consumer reaction to price changes.
As a result, we get a forecast of buyers’ behavior when the price changes.
Conjoint Analysis. Allows you to predict sales in various scenarios.
Conjoint Analysis allows you to answer the question of how sales will change if we:
change the pricing strategy,
change the properties of the product,
change the design,
introduce a new TM or SKU,
remove one SKU from the product family.
This type of analysis will be useful in cases of:
choosing the optimal product configuration;
choosing the optimal combination of price, package size, packaging design for new and current product (for example, choosing between several options for chocolate covers);
determining the significant characteristics of the product.