Profit is the universal measure of success for most businesses, and as such is usually the most valuable search criterion for marketing problems. Unless constrained to search within relatively profitable spaces of opportunity, Utility, Share of Preference, or Purchase Likelihood simulations mostly produce trivial solutions where the best features are delivered at the cheapest prices (attribute-based pricing, described below, offers an exception). Moreover, revenue searches focus solely on revenue without regard to profit. We recognize that a firm may have a specific goal in mind for a particular product line, such as maximizing penetration. But these strategies are generally the exception rather than the rule.
If profitability is to be optimized, the user must provide information about the unit cost for features. Such information is often hard to obtain, but we urge users to avail themselves of cost data, or to approximate costs wherever possible.
Cost information may be specified for attributes independently, or may vary depending on other variables. For example, if we were studying a pharmaceutical product, one attribute might be type of container, and another might be size of container. The costs of different types of container can depend on their sizes, and on several other variables as well, if desired.
The arithmetic of the profitability computation is very simple. For each product we have not only part worths reflecting respondent values, but we also have part-costs indicating the contribution to cost of different product attributes. We sum those part-costs to get the cost of one unit of product. We subtract that cost from the selling price of the product to get a unit margin, and we multiply unit margin by estimated market share to get a measure of relative profitability.
Profit = (Per_Unit_Price - Per_Unit_Cost) * Share_of_Preference * Total_Market_Volume
The user may specify the total number of units sold in the market, in which case estimated revenue and profitability can be stated in actual monetary amounts.
When Costs Depend on Share of Preference
Sometimes the cost to the producer per unit depends on the share of preference achieved. On the Revenue & Costs dialog, you can specify functions instead of fixed costs for levels of attributes.
For example, let's imagine that the cost to the producer of providing attribute 1, level 2 is $100 per unit, unless share of preference is greater than 20%, in which case the cost would drop to $80 per unit. Under Revenues & Costs + Cost Tables, you would specify the following Incremental Cost for attribute 1, level 2:
=IF(Share()<=0.2,100,80)
meaning, if the share of preference for the current product is less than or equal to 20%, return a cost of 100, otherwise return a cost of 80. Share() is a function in the software that returns the share of preference for the current product.
When you begin using logical expressions to define costs, you may find it more convenient to use the User-defined Variables section on the Revenues & Costs dialog to define share thresholds, such as Threshold1=0.2. In the cost tables, you can then use the function: =IF(share()<=Threshold1,100,80). That way, if you want to see what happens to the search solution when the threshold is changed to 15%, you can make that change in just one place.