Price Elasticity Explained. Get your pricing on track with your financials.

Price Elasticity Explained. Get your pricing on track with your financials.


No alt text provided for this image

A proper demonstration is vital for a successful sales process, and the demo itself can be a make-or-break moment. Demoboost offers a unique solution, enabling long-lasting effects that elevate your prospects' product experience right from the initial conversation. Say goodbye to tedious, one-off demos - with Demoboost, you can set up free trials and discover a more practical approach to winning over your prospects



According to CB Insights, nearly 18% of startups fail due the price issues. We can consider the number higher if we know that 42% of this survey responded that the key reason behind failure is No Market Fit which might be directly connected to price. We can discuss many metrics, but I selected one fundamental to consider while building the startup strategy. This one is in the mix that helps validate the other attributes your teams have already developed or put in motion.?

Price elasticity is the metric that measures how sensitive demand is to changes in price. A high price elasticity means that demand is very sensitive to changes in price, while a low price elasticity means that demand is not very sensitive to changes in price. Pretty simple.?


The formula would look as follows:?

Price elasticity of demand = (percentage change in quantity demanded) / (percentage change in price).?


To illustrate this better, if the price of a good increases by 10% and the quantity demanded decreases by 5%, then the price elasticity of demand is -0.5. This means that the quantity demanded is half as responsive to price changes as it would be if the elasticity were equal to 1.?

The beauty of this metric is that you must know the key to interpreting the results. Therefore the price elasticity of demand can be classified into three categories:

  • Elastic demand: The quantity demanded is very responsive to price changes. This means that a small price change can lead to a significant change in the quantity demanded.
  • Inelastic demand: The quantity demanded could be more responsive to price changes. This means that a large change in price can lead to a slight change in the quantity demanded.
  • Unit elastic demand: The quantity demanded is exactly responsive to price changes. This means that a 1% change in price will lead to a 1% change in quantity demanded.

There are some interesting practices on the market that can help us understand that topic better. The price elasticity of demand for necessities (necessity products) is typically inelastic. People need these products to survive, so they are less likely to change their consumption habits in response to price changes. On the opposite side of the spectrum, we have a luxury goods price elasticity of demand typically elastic. It s because people do not need these products to survive, so they are more likely to change their consumption habits in response to price changes. In competitive markets (agriculture, retail, transportation), elasticity is typically higher than in monopolistic markets (e.g., utilities, telecoms, and some software companies). This is because, in a competitive market, there are many sellers of similar products, so consumers have more choices. This gives consumers more power to negotiate prices, which leads to a more elastic demand. This sounds obvious, but it's important to remind everyone about these practices before we dive into the example.?

Here is a quick example from an Airline company that is considering raising the price of its tickets by 10%. The airline wants to know how this price increase will affect demand.

The airline has historical data on the price and quantity of tickets sold. This data shows that the price elasticity of demand for airline tickets is -0.6. This means that a 1% increase in price will lead to a 0.6% decrease in demand.

Percentage change in demand = (-0.6)*(10%) = -6%

It means the price increase will lead to a 6% decrease in demand. If the airline sells 100 tickets per day, the price increase will lead to a decrease in demand to 94 tickets per day.

The airline needs to consider the impact of the price increase on demand before deciding. If the decrease in demand is manageable, the airline may save money by raising prices. But that's only sometimes inevitable, and organizations have several good tools in their toolbox to reduce the risk of losing customers, like loyalty programs, temporary promotions with discounts, partner with other businesses. Please note that a 1pt difference can make much money if the airline operates on a large scale. This industry is already a tough one from the margins and profits point of view. For the same reason, these de-risking strategies are almost inevitable across industries like airlines.?

Conclusions: price sensitivity is only part of the story. The real game starts with what you will be doing afterward. Following our airline industry example, knowing that you are very likely selling fewer tickets is connecting your directly with the marketing department, trying to figure out what is your next television commercial and how you will bring extra volumes of tickets. Although this might be a very creative process, it requires a more robust financial process to understand how much you can spend on marketing while increasing the process and avoiding cannibalizing your margins. Another critical part of the readout process is an industry context. These metrics can't function in isolation; otherwise, you cause more harm than good. The list of variables includes the usuals, product, business type (B2B vs. B2C), business model (SaaS, free to play, freemium vs. premium, on-prem), pricing type (fixed, subscription, consumption-based), competition landscape (high, low, medium). A few additional practical suggestions are below:?

  1. Use accurate data. We all know this story. The trash in equals trash out. Better get this right.?
  2. Use a large enough sample size. Follow the principles here, creating several scenarios. Ensure you divide your data into two sets. One where you create a model, trying to figure out the scenarios, and the one you will test the model against. Data set matters.?
  3. The formula is limited. This is a simple formula, so context is not here. Sounds obvious? Many need to read. It's an approximation calculation, not an exact science. That's why I suggest connecting this with the financial data.?
  4. Price elasticity is not a slope. Both can refer to demand, but that's different. The slope measures the rate of change in quantity demanded per unit change in price, while the price elasticity of demand measures the percentage change in quantity demanded per unit change in price.?


要查看或添加评论,请登录

社区洞察

其他会员也浏览了