# Market Mix Node

The Market Mix node is designed to take a set of Products and determine which mix, or subset, minimizes inventory carrying costs while generating nearly the same level of profitability. This capability is also known by the terms ‘Assortment Optimization’, ‘Shelf Optimization’, and ‘Merchandise Planning’.

Removing Products from the original set to create a smaller optimal mix is not a simple matter of identifying those Products with the fewest Sales or lowest Revenue. Customers who buy low Revenue Products may be very loyal and would exit the Market if those Products were to no longer be offered. On the other hand, Customers who buy high Revenue Products might easily switch to a same Brand alternative.

The milk Market provides a good example. Suppose you sell three types of milk: Full-Cream Product A (FC-A), Full-Cream Product B (FC-B), and Non-Fat Product C (NF-C). Market Share is split such that 40% of Customers buy FC-A, 30% of Customers buy FC-B, and 20% of Customers buy NF-C. If you could only stock two Products which would you eliminate? The wrong answer would be NF-C. While generating the lowest Sales, NF-C Customers would exit the Market if the Product were suddenly not available (they would not suddenly start drinking full cream milk). The right answer is FC-B as these Customers would easily switch to the FC-A Product.

This Premium Node is not available as part of the free Community Edition. Premium Nodes help clean and connect real-world data to Market Simulations, and provide advanced Market Science analysis. Note that these descriptions are often deliberately vague.

# Market Mix

The Market Mix node is designed to take a set of Products and determine which mix, or subset, minimizes inventory carrying costs while generating nearly the same level of profitability. This capability is also known by the terms ‘Assortment Optimization’, ‘Shelf Optimization’, and ‘Merchandise Planning’.

## Inputs

#### Input Product Array

The set of Products that define the Market. Each row corresponds to a Product that competes for customers in the Market.

#### Input WTP Matrix

The Willingness To Pay (WTP) Customer Distribution matrix for each Product column in the Market by each Virtual Customer row. The total number of Virtual Available Customers is equal to the number of rows in the WTP Matrix.

## Node

#### Configuration

The user can select which ‘Key Performance Indicator’ (KPI) to maximize at each increment when determining which Product will be eliminated. The options include:

Quantity: eliminate the Product that contributes the least Incremental Quantity to all remaining Products. In other words, the next Product to be eliminated will maximize the residual Quantity from all of the remaining Products.

Share: eliminate the Product that contributes the least Incremental Market Share to all remaining Products.

Revenue: (default) eliminate the Product that contributes the least Incremental Revenue to all remaining Products.

Profit: eliminate the Product that contributes the least Incremental Profit to all remaining Products.

## Outputs

#### Output Product Array

The Output Product Array corresponds to the Input Product Array but lists only those Products in the ‘What If Product Set’. The rows will be ranked from the Products that contribute the least (that is, the Products that should be first eliminated) to the Products that contribute the most (that is, the Products that should remain in the optimal Market Mix).

#### Step Array

The Output Step Array corresponds to the Input Product Array but is updated after every iteration when a Product is eliminated from the Market Mix to show the forecasted sales of each remaining Product.

#### Incremental Trace

The incremental Output Product Array values at each decision point when the next Product to be eliminated is being considered. The impact of all the Products being considered for elimination will be listed alongside each ‘Rank’ step. The ‘Output Incremental Trace’ will contain the same columns as the ‘Output Product Array’.