This workflow shows a more flexible way to use a Recursive Loop to optimize Market KPIs.
The Market used in this loop is based upon the BB-101 Simple Monopoly, but the Recursive Loop itself is very powerful and can be adapted to any number of situations.
The Competitor wishes to maximize their Revenue KPI. A Recursive Loop is set up to test whether raising Price by 2% or lowering Price by 2% will result in more Revenue.
The loop is continued until neither raising nor lowering Price improves the KPI.
The Sprockets Products and its associated WTP Matrix is generated by the Customer Distributions node.
The Simulate Market node can be used to model a wider range of Markets where the actual number of Customers in the real-world is different to the number of Virtual Customers in the simulation.
The improved Price calculated from the last iteration is returned to the beginning of the next iteration.
A math formula is used to increase Price by 2%. A similar math formula is used at the bottom branch of the loop to decrease Price by 2%.
- Increase Price
- No Change in Price
- Decrease Price
Decreasing Price would improve Quantity sold. Increasing Price would improve Profit. Maintaining the current iteration Price would maximize Revenue.
In this case, maximizing Revenue is the most important so the Price that results in the highest Revenue is sorted to the top.
The loop is configured to run up to 100 times or until the Revenue Maximizing Price is equal to ‘No Change’.
At each loop iteration, the Product Price drops from $150 to $147 to $144.06 all the way down to $86.94. The expected Quantity, Revenue, and Profit are all calculated.
The decreasing Price iterates past the Profit Maximizing Price which occurs at $106.40. Recall that the ‘Profit Engine’ node used the Demand Curve to identify $105 as the Profit Maximizing Price.