The Bundle Generator node adds a new Bundled Product to both the 'Output Product Array' and the 'Output WTP Matrix'. The Willingness To Pay (WTP) each individual Customer has for the Bundle is a scaled-sum of the WTP the same Customer has for each of the selected Products within the Bundle.
Generating Product Bundles can help the user explore ways to increase the sales of an existing range of Products. The Bundle should increase the total Quantity sold without merely providing a discount to existing Customers as this Cannibalization may cause total Profitability to decrease.
How to scale individual Customer WTP values depends upon how much additional value the Bundle provides to Customers. In most cases, Customers will suffer from Diminishing Marginal Utility. That is, each additional Product added to the Bundle is less-and-less interesting to Customers. However, in some cases, Bundling together Products can increase the Marginal Value of each. For example, a Customer buying a Bundle of stereo equipment will be confident that each of the components will work together.
There are two ways the Bundle Generator node can scale WTP values:
Applying a general 'Scale Scenario' rule is useful when the value of the Bundle will be some fraction of the sum of included Products. For example, Customers may, on average, value the Bundle 15% less than the individual Products. Note that firms may still be willing to sell this Bundle at a 15% discount to encourage Customers to buy additional Products that they wouldn't otherwise buy.
Applying additional Booster/Diminisher adjustment factors can be a useful way to fine-tune the scaling. For example, if a Bundle includes two Products from the same Category then the Customer may more heavily discount the value of the second Product as they'll already be able to consume the value of the first Product.
The Booster/Diminishers work differently than the 'Scale Scenario' rule. The Scale Scenario starts with an aggregated WTP sum and then scales it. The Booster/Diminishers work at a deeper level by looking at the individual WTP value of each Customer for each Product. For example, imagine a Product that you only need to buy once. If you came across a bundle with two of them, then the second Product is worthless to you. This situation would be better handled by a Booster/Diminisher. Setting the 'All Products Booster / Diminisher' to 0.0 would reduce each Customer's WTP for the Bundle down to the level of just the most valuable Product within the Bundle - eliminating the value of all other Products. Note that the 'Bundle Generator' node can apply both the Booster/Diminishers and the 'Scale Scenario' rule, but the Booster/Diminishers are applied first.
The act of Bundling, itself, already changes the nature of the Product Differentiation offered without any scaling. Bundling has the effect of averaging the value a Customer places upon a set of Products. For example, if a Customer has a relatively high WTP for the first Product but a low WTP for the second Product, then the Customer's aggregated WTP for the two Products will be closer to the overall market average. In terms of Product Differentiation, Bundling increases Vertical Differentiation (that is, the mean of the summed WTP) but reduces the relative Strange Differentiation (the standard deviation of the summed WTP) and reduces Horizontal Differentiation (the correlation difference to other Products).
Several Bundles can be generated simultaneously by specifying a list of Bundle Names along with included Product Names in the optional 'Input Bundle Products' table. Alternatively, several Bundle Generator nodes can be cascaded one after the other, with each generating just a single Bundle as specified by the 'Products to Include' column selector.
More Help: Examples and sample workflows can be found at the Scientific Strategy website: www.scientificstrategy.com.
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