Optimization

The selections and allocations on the Define tab determine which customers are candidates for which offers , and may return many possible solutions. If a customer is eligible for multiple offers , which do you choose? Optimization allows you to identify the best or most profitable offer for each individual via the right channel within the constraints of budget and channel capacity. In other words, IBM® Analytical Decision Management optimization defines the best way that entities can be allocated to dimensions.

The goal of optimization is to identify the solution that best meets a specific goal, such as maximizing the revenue from a marketing campaign, or minimizing the risk of fraud or churn. The result of optimization is a solution that answers this question across all possible combinations within your population, in the manner that best maximizes the value you want to optimize (such as profit).

Optimization supports a number of deployment scenarios. For example:

• Real-time optimization. Optimizing allocations for a customer on a real-time interaction point (for example, best offers to make to a customer who is looking at the web site or who has called in to the call center).
• Batch optimization. Optimizing allocations across multiple customers on a batch interaction point (for example, best offers to make to each customer by the best outbound channel).
• Pre-scoring real-time offers ahead of time on a batch interaction point. For example, rather than performing a real-time optimization when the customer visits the web site, perhaps you would rather pre-calculate what offers should be made to the customer if they visit the web site, or if they call the call center, etc. If the customer does not arrive, then those precomputed offers could expire and can be recomputed on more recent data.

Optimization is helpful for solving problems such as allocating customers to marketing campaigns or offers, for example.

Applications configured to use complex mathematical optimization (CPLEX), such as IBM Analytical Decision Management for Campaign Optimization, IBM Analytical Decision Management for Operations, and IBM Analytical Decision Management for Demand Optimization, have an Optimize tab.

Note that CPLEX optimization scales in a non-linear fashion. For example, the increase in time and resources required to optimize over 1000 records will more than double when 2000 records are used – possibly taking four times as long or more. This is because optimization is trying to find combinations of records, and the number of available combinations increases non-linearly.

1. Specify optimization parameters in the table as desired. You can simply type in values, or click the icon next to each input to choose a field, browse for an existing model, build a new model, or create an expression which can then be used as input to the optimization. If the application is configured to include more than one decision hierarchy element, each hierarchy will have its own tab containing a parameters table.

   You can also reorder the parameters in the table, but this has no impact on the optimization.

   The following table describes some of the available items in the Optimization Parameters section:

   Table 1. Optimization parameters

   Item	Description
   Total Budget	Specify the total budget available across all campaigns.
   Max. Offers	Specify the maximum number of offers that can be made to a customer.
   Recent Offers	Specify a value for the number of recent offers a customer has already received.
   Campaign/Offer	Lists the available campaigns and offers, such as monthly specials and TV discount.
   Prob. to Respond	The probability that the customer will respond to an offer.
   Revenue	The expected revenue if the customer accepts the offer.
   Offer Cost	Cost of making the offer.
   Offers Available	The number of this offer available to be made.
   Channel	Lists the available channels (mediums used to communicate with the customer), such as e-mail.
   Capacity	The maximum number of offers that can be made through this channel, such as the maximum number of offers sent via mail.
   Channel Cost	Specifies the cost associated with making an offer through the channel.

2. Use the Priority drop-down menu to give priority to certain items. For example, offers given high priority will be considered before those that are normal or low priority. The prioritization equation is still computed for all offers, but the selection is done in different groups based on priority order. In other words, all solutions of a given priority are considered before any solution of a lower priority. The priority will take precedence over the object value. For example, if Offer A has a high priority and Offer B has a lower priority but higher expected profit, then Offer A will be selected.
3. Select Customize table to choose at which level you wish to define each parameter. For example, whether to specify parameters at the campaign level, or separately for each offer within a campaign .
4. The Optimize tab maximizes revenue or maximizes return on investment, based on the optimization equation used. Click Select equation and choose which optimization equation defines your goal.

   Total projected profit based on current project settings = (Prob. to Respond * Revenue) - (Offer Cost + Channel Cost)
   
   OR
   
   Return on investment =  ( (Prob. to Respond * Revenue) - (Offer Cost + Channel Cost) ) / (Offer Cost + Channel Cost)

   Where:

   • Prob. to Respond is a customer's propensity to respond to a particular offer.
   • Revenue is the income value or contribution expected from that response.
   • Offer Cost + Channel Cost is the cost of making the offer and the cost of using channels such as e-mail, mail, or telephone.
   Note: IBM Analytical Decision Management for Campaign Optimization projects created in releases prior to version 17 will use a different equation. The equation was updated in version 17.

   Equations can be modified for different applications by the application designer. While the specific equation may change, many business problems may be modeled in this manner.

5. In the Constraints section you can select from available constraints to define the boundaries the optimization solution must work within, such as total budget. For example, you likely do not want the amount spent to exceed the total budget.

   The application designer configures the optimization equations and the constraints. For more information, see the Application Designer's Guide.

6. To experiment with different parameter combinations and see how each impacts your result, click the Create a new scenario based on current project settings icon.
7. If desired, click the Perform a test on the application for a selection of records icon. Note that optimization global constrains are applied at the individual customer level (not globally), ROI is calculated at the individual customer level (not based on all customers), and if a record is excluded by the optimization, then its objective value is always shown as zero.

For applications that use complex mathematical optimization (CPLEX), such as IBM Analytical Decision Management for Campaign Optimization, IBM Analytical Decision Management for Operations, and IBM Analytical Decision Management for Demand Optimization, advanced options are available to administrators. See Advanced options for more information.

Note that for applications with multiple dimension hierarchy elements, when users open the application they can choose which elements to include and reorder them. If an element has been excluded, any objective functions or constraints will also be excluded. See the topic Project configuration for more information.