Being a company that has decades of pricing excellence, one of the biggest issues we have seen so far is that, most companies have account managers that focus on a one on one relationship with the clients, however, they fail a 360-degree approach in deciphering all the drivers for example, what other customers are paying for the same product. Their managers and the account managers often look into the customer portfolio or at what is the customer buying, but they do not or in a very limited way compare customers within the same product. This a glitch and leads to them lacking in the visualization of what their price volume portfolio could be. This comes across a small risk however this can compel businesses to leave money on the table!

Price scatters or Scatter plots are the primary key to gain insights or a method where companies can begin a 360-degree approach, however, it is very important to understand what all can a price-scatter tell you and to be sure if the scatter plot is logical or illogical.  It is an indication of price variance in the business – so the exact same product at the exact same volume is being sold at entirely different prices.

Why does it occur: Customers with small revenues are at low margins because of significant discounts and uncontrolled price leakages. Due to excessive discounting by the sales negotiations, the companies end up giving discounts and negotiate ‘bad’ prices sometimes. On the other side customers with large revenues are paying list price which entails a high risk and chance of churn/ dissatisfaction. Resulting in excessive deal variability due to uncontrolled discounting & lack of commercial control (in the graph below)

Example: The opposite would be of Apple MacBook pricing which is a straight line, whether you buy 1 or 200 you pay the exact same for each

What are the insights that you could gain from scatter plots?

When a scatter plot is used to look at a predictive or correlational relationship between variables, it is common to add a trend line to the plot showing the mathematically best fit to the data. This can provide an additional signal as to how strong the relationship between the two variables is, and if there are any unusual points that are affecting the computation of the trend line. A common modification of the basic scatter plot is the addition of a third variable. The values of the third variable can be encoded by modifying how the points are plotted. For a third variable that indicates categorical values like geographical region or customer aggressiveness, willingness to pay for deals can be used. 

What can price-scatter plots bring to the table of pricing managers?

Over the past years, we have seen that in various businesses they have the most illogical price-scatter (example: Image1) which does not allow them to make strategic decisions in their end-use market for example.

What we usually see in these scatters is not always the same case as each business has its own customers, customer negotiations, etc. And the simple trick to gauge if the scatter plot is logical or not is to see if the general frontline is diagonal (example: Image2)

A logical price-scatter, at first hand, gives you immense insights on the current situations, current driver, and more importantly an indication if/or you must change something about your business price setting. This then leads you to the next steps where you come to start using an upper band (ceiling price) and a lower band (floor price) price scatters. These lines/bands are based on your data. By running an algorithm you are confronted with your upper and lower limit and within there it leads you to a benchmark that can be highly intelligent or it can be done through an average linear regression as long as you reach a price point that relates to your business. 

MRD has a pragmatic way of exploiting these price scatters, we understand the industry-specific problems and have created an intelligent pool of algorithms that basically run on the data to then give insights such as customer aggressiveness, deal recognitions, willingness to pay, discounting guidelines and more. 

For the upper and lower band, we use data analysis and modeling based on your data which means: With our tool, you can steer your business towards logical price scatters & walk to pricing excellence.