Node Description
Correlation Segmentation Node
The Correlation Segmentation node allocates all Products into Product Families based upon their mutual Correlation. Very similar Products, as perceived by Customers, should end up in the same Product Family, whereas different Products should end up in different Product Families.
Note that the ‘Correlation Segmentation’ node offers similar functionality to the ‘Similarity Family’ node. But the ‘Similarity Family’ node is designed to re-group Products that were designed to be together as part of the same Product Line. For example, if a Product Line were split into individual SKU’s and each SKU was treated as a separate Product, then the ‘Similarity Family’ node is designed to selectively regroup those Products together.
The ‘Correlation Segmentation’ node, on the other hand, is designed to group Products into Portfolios of Products regardless of whether they were designed to be so grouped. Customer perception of Products that offer similar functionality and solve similar Customer problems defines the Product Portfolios. These Product Portfolios make it easier to calculate Portfolio Pricing and Long Term Pricing in a consistent way.
Several of these ‘Correlation Segmentation’ node can be chained together in a Workflow in order to edit and re-allocate Product Families, and ultimately ensure all Products are allocated.
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.
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Correlation Segmentation
The Correlation Segmentation node allocates all Products into Product Families based upon their mutual Correlation. Very similar Products, as perceived by Customers, should end up in the same Product Family, whereas different Products should end up in different Product Families.
Inputs
Input Product Array
The super-set of Products from which the smaller set of Product Families will be defined. Each row corresponds to a Product that is to be mutually compared to all of the Products within the growing Product Families.
Product Similarity Rankings
The list of all Product-to-Product rankings. That is, from the Customers who looked at Product01 how did they rank Product02. Alternatively, from the Customers who looked at Product01 what is the probability that they also looked at Product02 (sorted to provide a rank order).
Node
Configuration
Products need to have a mutual Correlation of greater than or equal to this amount in order to be allocated together into the same Family. This should be a high value to ensure that initially only the closest Products will be allocated. The Correlation Threshold will then be decreased to ensure more distant Products are suitably allocated to Product Families.
Outputs
Output Product Array
The Output Product Array corresponds to the Input Product Array but is updated to include the name of the Product Family that each Product has been allocated to.
Product Similarity Rankings
The Output Product Similarity Rankings is equivalent to the Input Product Similarity Rankings without any changes. The Product Similarity Rankings are simply passed through the node as a convenience to allow several of these ‘Correlation Segmentation’ nodes to be chained together.
Family Correlation Matrix
A symmetrical matrix reflecting the correlation between each Product Family and each of the other Families in the Output Product Array. The Output Family Correlation Matrix may be used to help identify small Product Families that are highly correlated – these Families might be manually joined together.
