Objectives

Optimizing the Marketing Mix enables you to determine the optimal spending level and the budget allocations along any dimension of interest (customer segments or sub-segments, campaigns, channels, media, products, time, frequency, etc.).

Results from this application will be profit estimates for the various marketing mix categories leading to the optimal budget and dollar allocations. The following graph illustrates the results from one of these types of analyses.

Analysis and Customer Data

The following historic data and analyzes are used to build the allocation models:

• Past performance data (marketing expenditures linked to leads, sales or profits), resource allocations (advertising dollars by channel, product category; gross profit margins by product type; business constraints; objective) are gathered.
• What-if scenarios are run to account for different assumptions such as increasing or decreasing marketing expenditures (What impact on sales would a decrease in TV spend of 30 percent) and other market changes (What will be the effect of declining response rates).
• Calibrated response curves are built from the above data to reflect the market reactions to various changes in the marketing mix expenditures.
• The response curves and functions are incorporated into models that enable the user to derive the optimal marketing mix allocations, promotional dollar reallocations, etc. while maximizing profit contributions.

Benefits

The benefits that can be realized from utilizing this solution:

• Enables user to define any number of what-if scenarios and compare and contrast the result (should there be a shift in budget from Campaign A to Campaign B).
• Enables user to use business performance measures such as profitability, ROI, revenue, or incremental customers gained to determine the optimal marketing mix and prioritize marketing strategies across all business dimensions.