When crafting a new product or enhancing an existing product, there's a major question that must be answered: how to price the product. That’s where leveraging primary market research comes in. Market research helps you gain insights into your target customers, the purchase drivers influencing their decisions, and other factors that will impact your success in a specific building product category.
Typically, the product development process is broken down into five distinct stages:
- Discovery and exploration to identify market needs and opportunities
- Concept screening
- Concept testing
- Product testing for feature and benefit validation
- Product launch testing
Once you've completed phases 1-4 of the product development stage gate process, with a solid new or revised product offering in hand that is validated from prior research, then it's time to ensure you have the right pricing, packaging, and placement defined to avoid your go-to-market push becoming a flop.
It's at this point that conducting pricing elasticity research is important, so that your channel, marketing, and sales teams are setup for success when the official product launch occurs, equipped with the information on ideal price ranges that they need in order to set an initial price point for various channel members and customers. Having this information up front also enables for faster price pivoting should a product launch not be hitting quotas as expected.
What is Pricing Elasticity?
If a price change for a product causes a substantial change in either its supply or its demand, it is considered elastic. Elastic products are often non-commodity items that have competition such as automobiles, outdoor power equipment, and kitchen faucets. Examples of products that are inelastic, in which a change in price creates a smaller change in demand, are often necessary items such as cigarettes, fuel for our cars, lumber, and certain hardware products. If the price goes up just a little bit for these items, the demand doesn’t usually go down in kind (and can sometimes go up!)
Price Elasticity of Demand is an analysis technique that examines the relationship of two price points and the corresponding sales volumes of a product. Used in combination with price sensitivity techniques such as Gabor-Granger or Van Westendorp, which can be used to approximate an ideal price point, Price Elasticity of Demand can define the relative strength of effect a change to the price of a product can be expected to have on revenue.
In the following price elasticity example using conjoint analysis, we see purchase share is highest for Brand X at the lower price (among other varying attributes) against two other brands’ products. Share increases more for homeowners with $100k+ income.
How To Calculate the Price Elasticity of Demand
Now that we know the basics, let’s explain the technical side of the Pricing Elasticity of Demand (PEoD).
PEoD is formally defined as a ratio of the percent of change in number of units sold compared to the percent of change in the price point in relation to the starting price point.
((Q1 - Q2) / Q1) / ((P1 – P2) / P1)
where
- Q1 = original quantity sold
- Q2 = new quantity sold
- P1 = original price per unit
- P2 = new price per unit
If we examine the intent of equation, we’ll see that the first part ((Q1 - Q2) / Q1) takes the difference in sales volume between the two scenarios being tested and, by dividing by the initial sales volume, produces a value that represents the percent change in sales volume. We then do the same with price points to derive the percent change in price. So frequently the PEoD is represented by the following simplified formula.
%Δ quantity / %Δ price
This ratio can be used to estimate the revenue that can potentially be achieved by changing the unit price. A ratio of 1 reflects a scenario where there is no change in revenue should there be a change in price. A ratio above 1 reflects a positive change (increased revenue) and a ratio below 1 reflects a negative change (decreased revenue).
There is a significant problem with strictly using the basic equation described above to calculate the PEoD ratio in that the computation of that equation is directional. The PEoD for a price increase will always provide a different ratio than the PEoD for a price decrease using the same base values. For this reason, a modified equation is commonly used which is known as the PEoD midpoint formula. Using the PEoD midpoint formula the ratio is instead the absolute value of comparing the percent change in quantity of demand in relation to the midpoint of the two quantities being tested to the change in price in relation to the midpoint of the two price points being tested.
| ((Q 1 - Q 2) / ((Q 1 + Q 2) / 2)) / ((P 1 - P 2) / ((P 1 + P 2) / 2)) |
The resulting ratio is still read the same way; a 1 means there’s an equilibrium and no change in revenue should be expected based on this change in price points, a value greater than 1 means it will result in revenue growth while a values less than 1 means that it will result in revenue decline.
Because PEoD is based on the percent change in units sold and price per unit, it is significantly affected by the magnitude of the values being tested. For example, testing a price change from $1 per unit to $2 per unit is a 100% change in price while a product initially sold for $100 per unit would have to increase to $200 per unit to see a similar pricing elasticity ratio. The number of units sold is affected by the magnitude of the numbers being compared in similar ways.
Factors that Affect Pricing Elasticity
The PEoD analysis technique assumes a constant level of demand. There are many factors that can magnify or reduce the consumer’s behavior regarding changes in pricing that won’t be reflected in the PEoD as calculated.
Price as a percent of income
While comparing lower price points can cause the PEoD to be significantly higher than when comparing higher price points, it is wise to keep in mind products that represent a small percentage of the consumer’s income are less price sensitive than products that represent a large percentage of the consumer’s income. Virtually no one is comparing prices on bubble gum but almost everyone shops around when buying a new car.
Availability of substitutes
If the product being examined is one of a kind in the market consumers will be less reactive to price changes; if they want the product they’ll pay what’s being charged and changes to the price will have a minimized effect. Conversely if there are numerous similar products on the market consumers will be more reactive to price changes; if one brand of product lowers its price consumers may switch brands to get what is seen as an equivalent product at a lower price. The ubiquitous availability of gas stations means that a small change in gas prices can dramatically shift consumers shopping behavior.
Immediacy of purchase
If a consumer needs a product immediately they will have less opportunity to comparative shop and will therefore be less responsive to price changes. If consumers have time to compare products and prices then price changes will have a greater effect on their purchasing decisions. Examples may include health and medical services or natural gas for your home.
Luxury vs. Necessity
Inextricably linked with immediacy of purchase is the necessity of the product. Consumers are more likely to shop for the best value when purchasing luxury items (or even choose to go without) than when shopping for necessities. In some rare instances a luxury item can create demand by simply raising prices.
Knowing How to Price a Product
Whatever your needs, our market research team at The Farnsworth Group can provide you with the right tools to conduct effective pricing elasticity research. Our focus has been, and will remain, serving the building products industry with valuable insights to forecast the market, deeply understand the customer, and strategize go-to-market tactics accordingly.
During the pricing elasticity and feature valuation stage of the product development stage gate process, we utilize research methods and modeling to provide recommendations on which combinations of features are most desired and at which price points. The result is a product and pricing strategy that your channel, sales, and marketing teams can be confident in.
Written by Jeff Shull, Online Fieldwork Manager
Jeff brings two decades of experience in the home improvement and building products industry to his role managing all B2B data collection efforts and developing programming solutions to yield accurate answers to complex client questions. Based in Indianapolis, Jeff is the master of programming, data analysis, and data tabulations here at The Farnsworth Group. When he’s not programming studies for fielding, you will likely find Jeff tackling a new woodworking or woodturning project.