Glossary of Forecasting Terms, Methods, & Techniques

 

Bayesian Probability: A probability based on a person's subjective or potential judgments and experience.

Casual Forecasting: This method involves finding factors that relate to the variable being predicted and using those factors to predict future values of the variable.

Conjoint Analysis: A statistical technique in which respondents' utilities or valuations of attributes are inferred from the preferences they express for various combinations of these attributes.

Decision Calculus Models: The quantitative models of a process that are calibrated by examining subjective judgments about outcomes of the process.

Demand Analysis: A study of the reasons underlying the demand for a product with the intent of forecasting and anticipating sales.

Exponential Smoothing: A forecasting technique to estimate future sales using a weighted average of previous demand and forecast accuracy.

Forecasting Models: In forecasting sales, share, or other marketing objectives, a variety of methods have been used, including time series models (e.g., moving averages, exponential smoothing), econometric models (e.g., regression, input-output), and judgmental models (e.g., Delphi technique).

Markov Model: Uses a matrix to find the probability that the user of a brand in a category will switch to another brand in the category.

Projective Technique: A qualitative research technique used to investigate attitudes and perceptions not described by verbal answers.

Qualitative Forecasting: Methods that rely on one or more persons to generate forecasts without using mathematical models.

Quantitative Forecasting: Methods use historical date to forecast the future.

Regression Analysis: A statistical technique used to derive an equation that relates a single continuous criterion variable to one or more continuous predictor variables.

Statistical Demand Analysis: A method of developing a sales forecast that attempts to determine the relationship between sales and the important factors affecting sales, typically using regression analysis, and the use of that relationship to forecast sales for the future.

Time-Series Forecasting: Projecting future values of a variable based on the past and current observations of the variable.

Tracking Study: Market research to measure brand positions and the long-term effects of marketing activity.

Sources: "Improving Marketing Effectiveness," by Robert Shaw (www.vbmf.com); American Marketing Association (www.marketingpower.com); and "Production and Operations Management," by Joseph S. Martinich (www.umsl.edu/~jmartini/).