Node Description
Price Maximize
The Price Maximize node is designed to continuously change the Price of a small set of Focus Products until the Maximization Goal is reached. Both increases in Price as well as decreases in Price are tested. The Maximization Goal can be to maximize Profit, Revenue, or Quantity Sold. While only the user-selected Focus Products can change Price, the user can define a broader set of ‘In Scope’ Products that are considered when evaluating the Maximization Goal.
For example, a Retailer may wish to maximize Profitability across their entire Store by changing the Price of one or two Focus Products. Or a Brand Manager may wish to maximize Revenue across all Products having the same Brand as the Focus Product.
Evaluating the Maximization Goal across a broader set of ‘In Scope’ Products is the way to account for Cannibalization. Cannibalization occurs whenever a Customer would have purchased a different same-Store or same-Brand Product but switches to the Focus Product because of a discount. While the Profit, Revenue, and Quantity Sold of the Focus Product would increase, the overall impact to the Store or Brand may be detrimental.
Note that other multi-Product Pricing nodes are available. The ‘What If Product’ node has a ‘Portfolio Pricing’ algorithm that can be used to reach a Maximization Goal by simultaneously changing different Prices of many Focus Products. This allows the ‘What If Product’ node to identify a Pricing strategy that will return greater Profitability without losing Customers. There is also the ‘Price War’ node that simulates Competitive Rivals constantly setting and resetting maximizing Prices for multiple Products in a series of Competitive Battles.
This Community Node documentation assumes you have already downloaded the open-source KNIME analytics platform and installed the free Market Simulation (Community Edition) plugin. If not, start by returning to Getting Started.
Downloads
#1 Maximize Revenue
Inputs
Product Array
The Input Product Array includes the set of Products that define the Market.
WTP Matrix
The Willingness To Pay (WTP) Customer Distribution matrix for each Product column in the Market by each Virtual Customer row.
Node
Configuration
Set to Maximize the Revenue of the Spacely Sprockets Product.
The node will start by adjusting the Price of the Spacely Sprockets Product by +/- 16%. If that doesn’t improve Revenue, then the Price Adjustment will halve to +/- 8%. This continues for up to 100 Tuning Adjustments.
Outputs
Product Array
The Revenue Maximizing Price for Spacely Sprockets is found to be $114.59. At this Price, Revenue increases by $102,417.
Key Indicators
It took the node an Iteration Count of 5 improvements to find the Revenue Maximizing Price. Decreasing Price by 23.6% resulted in an increase in Revenue of 16.1%.
#2 Two Products
Inputs
Product Array
An additional column ‘Store’ has been added to indicate that both Products belong to the same Store. This is important to eliminate same-store Cannibalization.
Node
Configuration
The goal is now to change the Price of both Spacely Sprockets and Jetson Gears to maximize Revenue.
The goal has also been set to maximize Revenue across the ‘Store’.
Outputs
Product Array
The Revenue Maximizing Price for both Products is now $128.04.
Total Results
The GroupBy node aggregates the results by Store. The new Prices lifts total Store Revenue by $77,660.
At the same time, Market Share increases by 17.6% but Profitability drops by $10,389.
