In an unpredictable global marketplace, managers face the constant challenge of trying to determine where their company is headed next. They must respond quickly and effectively, using only a handful of levers to help build sales and marketing efficiency and market share. This is where decision models can play a key role. By providing headlights for predicting future short and longer term sales response activity, they can help managers make better decisions.
By definition, decision models are used to predict the outcomes of marketing-mix decisions. At the most basic level, decision analysis models input sales response variables – such as market-size/opportunity, demographics, and/or firmographics, marketing communications, price, and promotional offers – into a database. Then, by using typical mathematical techniques, they predict how the market will respond to changes in the analyzed set of variables. The result can help measure the effectiveness of marketing efforts and provide decision support for actual decisions.
Decision models are most useful when they’re backed with relevant, timely, and accurate data and variables. With a good mix of variables, decision models can deliver useful information to help managers reach decisions. Decision models can be used to answer several “if this-then-that” questions. Just as in descriptive models, they can find a regular pattern to predict how a market will react to changes in marketing-mix variables. With this information, the manager has a better chance of finding the correct solution than by depending on intuition or non-empirical data.