Understanding Price Elasticity: Product Pricing is More than Just a Number

Understanding price elasticity is critical to price optimization. In this post, we talk about ways to measure and quantify price elasticity, and what that can mean for your pricing strategy.

What is price elasticity, and why is it so important?

Many marketing professionals think they understand how to set product prices. After all, they’ve had years of experience. They’ve seen how demand rises and falls, and how pricing can interact with demand. But the truth is that it is very difficult to predict exactly how customers will react to a changed price, which makes pricing strategy and price optimization a real challenge.

Product teams the world over have the same goal: decrease SKU losses and increase sales and revenue. Let’s see how price elasticity can impact these goals. First, we’ll discuss what it is and its various types. Then we’ll talk about the benefits of price elasticity modeling.

What Is Price Elasticity?

Simply expressed, price elasticity is one way to measure consumer reaction to price changes. For example, if an item’s price goes up, its sales go down. However, this isn’t always strictly proportional to the rise in price, as we explain in the next section.

You can calculate price elasticity by dividing the change in volume (as a percentage) by the percentage change in price.

Closely related to price elasticity is cross-price elasticity. This measures how many consumers will switch to Product B when Product A’s price changes. The formula is Product A’s percentage change in volume divided by the percentage change in price for Product B.

Price Elasticity Zones: Where Does Your Product Fit?

As you can imagine, there are many factors that influence price elasticity modeling, and we will discuss them in the next post. There are also gradients or zones of price elasticity.

If prices on your favorite brand of snack crackers were to rise sharply, you might cut back or even switch brands; after all, you can live quite easily without snack crackers. But if an item is an absolute need that can’t be replaced, you can only curtail your use so far. Therefore, there are zones of price elasticity that help you determine where your product falls.

  1. Perfectly Elastic. In this zone, a small change in price results in a very large change in demand. This zone is home to things that consumers view as expendable and brand-agnostic.
  2. Relatively Elastic. In this zone, small changes in price cause significant changes in demand. Consumers might have a definite preference, but they can also easily find other comparable products that fill their needs.
  3. Unit Elastic. Changes in price, in this zone, are matched by changes in quantity.
  4. Relatively Inelastic. This is the zone where brand loyalty (and consumer need) begin to play a part. Large changes in price cause small changes in demand because people are not willing or able to substantially reduce their consumption. Gasoline is a good example of a relatively inelastic product.
  5. Perfectly Inelastic. These are things consumers absolutely need and must pay the set price to obtain. For example, if you have only one water provider in a city, residents are basically stuck paying whatever the provider charges. 

The Benefits of Price Elasticity Modeling

Price elasticity is used to find the price point of maximum profitability: the point where increased prices and margins are offset by lower demand and sales. This ideal price point can be compared with current pricing to see what products are under- or over-priced. Of course, these forecasted points need to be properly weighted with other metrics to be effective.

Calculated max profit points and other pricing strategies provide directional guidance for product teams. When implemented alongside data analytics that includes competitors’ stats, this can be used to better align prices to the current market, to identify market changes, and even to optimize products at a segment or location level.

As more data becomes available and more systems are in place to process it, the age of pricing by guesswork is ending. In our next post, we’ll look at several other factors that influence price elasticity. Join us!

Authored by Anirudh Mathur, Consultant at Absolutdata Analytics and Zubin Saini, Manager, Absolutdata Analytics

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