“What is the right price?” This is a question every business has to answer. For some, this issue is extremely complicated. Perhaps you operate in a very competitive environment and raw material costs are escalating? Maybe, you have multiple products in the same category with different price points (a good, better, and best product). Maybe you have multiple products that you would like to bundle into a single offer? Maybe you have a complicated sales environment that involves distributors and consumers? Whatever your pricing problem is, there are basic fundamentals you first must understand. Let’s take an over-hanging view of common price elasticity pitfalls, the two main pricing analysis methods, and a quick case study (we all love case studies, right?)
Key Marketing Research Issue
Traditional focus groups and direct questioning approaches (e.g. surveys) suffer from a bias towards rational responses.
“If you ask a rational person a rational question…you’ll get a rational answer”
(If you love that quote, we devoted a whole MRX Minute video on the topic)
This is particularly misleading when developing pricing information. For example, if you ask someone, “Would you like to pay more or less?” they will always choose less. Who would want to pay more?
Pricing Analysis Methods
“Econometric price modeling” – an approach which uses statistical modeling tools to understand the relationship between pricing and sales using historical data.
“Experimental price modeling” – a specific application of conjoint-type marketing research which develops a specific relationship between customer interest and various price points on a forward-looking predictive basis.
*When companies shift from Cost-Plus pricing to Value-Based pricing, historical modeling is irrelevant. When shifting to Value-Based pricing the goal becomes “what is the selling proposition that maximizes our customer’s willingness to pay?”
Today we’ll take a closer look at Experimental Price Modeling (Conjoint-type approach)
Experimental Price Modeling
In a Value-Based model, price sensitivity is related to the value proposition. In other words, what people are willing to pay (price sensitivity) is based on how they perceive the benefits. Changing elements of the concept can change their willingness to pay.
Below is a diagram of how we look at Value Based Pricing.
Product Benefits – The reason people buy products. Classic example: You don’t buy a drill. You buy a hole in something. A drill is just a means to an ends.
Convenience – A good example is when you order pizza. If the pizza is delivered to your doorstep, you’re probably willing to pay more than you would if you have to go pick it up.
Image – Perception of the brand/product. It is the intangibles that a brand contributes to the perceived value of the product
Cost – The actual cost (perceived) of a product. When you buy a car, you have the sticker price, less the haggling discount that the dealer gives you, plus the cost of title registration and insurance, less any trade-in allowance …etc. In many categories, figuring out the cost of a product is difficult.
Time – It is the opposite of convenience. There is a perceived “cost” to spending time researching some type of products. If I don’t have to waste any time, I’m willing to pay more.
To quantifiably identify the impact each variable has on price, a conjoint analysis study is recommended. The type of Conjoint approach you use is based on your specific objectives (there are many flavors of Conjoint). Knowing which “flavor” is right for you can be confusing so it’s important to choose a research provider who is an expert in Conjoint.
In a Conjoint study, the respondent will see a mixtue of “elements” in your value prop as a single concept. For example, they might see a combination of different product benefits (warranty, convenience, brand name, price). In a Choice-Based Conjoint (CBC) study, the respondent is asked to choose between the concepts. By analyzing the choices made when certain “elements” are present or absent, we can statistically tease out the impact of each variable (and how each variable impacts each other). In the case of pricing, this information is extremely relevant because you can better understand the impact each variable has on the perceived value of your product.
Also, by isolating the impact of pricing changes, you can start to identify the optimum price point(s) and how sensitive your product is to pricing changes.
By way of example, let’s look at an office chair manufacturer who has products at multiple price points (they have a good, better, and best chair). Let’s fast forward to after they’ve completed the Conjoint exercise and they are looking directly at the price elasticity of the data.
Below is a chart of how the share (demand) of each chair responds to different price points. In this graph, the “good” chair (dark blue line) loses 4.5 percentage points of share as it increases in price from $99 to $119. However, as the “good” chair raises its price from $119 to $139, it only loses 0.9 percentage points of share.
The key takeaway being that if it does make sense for the manufacturer to raise the price of the “good” chair (considering the loss/gain of share for the “Better” and “Best” chairs), their revenue would be optimized at the $139 price point vs. the $119 price point. The jump from $119 to $139 is less price sensitive for the “Good” chair.
Pricing is a complex issue. It can involve:
- Product lines
- Distribution channel
- Customer segment
Pricing usually does not have a linear impact on demand. The key is looking for “elbow” points. As shown in the diagram above, moving from $99 to $119 had a different impact than when moving from $119 to $139. In other words, it’s important to identify the areas where the demand is less sensitive to price change.
The First Step
The first step in answering the question “what should my price be?” is identifying which pricing analysis method (Econometric or Experimental) aligns with your pricing strategy (Cost-Plus Pricing or Value-Based Pricing). If you choose to go the route of Econometric, make sure to sure use a research company with advanced statistical modeling tools. If you go the Experimental route, find a research company that specializes in Conjoint analysis (which has many flavors).
Want more information on Price Elasticity? Check out how a Building Products manufacturer tackled this challenge in a complex pricing industry.