Quantitative Forecasting:

Quantitative forecasts are based on assumptions. The common methods are:

Regression analysis:

Using the least squares method. This method has the following advantages:

It guarantees the best fit, i.e. the best sales prediction with the data available.

It is a statistical method: Therefore we have the advantage of probability distributions to make probabilistic forecasts and to reach conclusions about the relative magnitudes of forces that affect sales.

On the other hand:

(a) It works only with data that can be quantified. With the qualitative forecasts discussed, assumptions and judgements were made about important marketing factors. The regression forecast will suffer to the extent that these factors are not in the equation.

(b) It is easy to be deceived by the apparent accuracy of results when in fact the regression equation may perform rather poorly.

Conclusion:

• The only thing certain about the future, as far as the marketing manager is concerned is the inevitability of change.
• The organization must constantly exert an effort to know its customers and their needs and to provide them with the right product at the right time.
• Demand analysis forms the foundation for understanding sales potentials and forecasts. The determinants of demand include the elements in the marketing mix of the firm and of its competitors, the characteristics of the buyers and environmental factors.
• For estimating future demand, the company may use qualitative and/or quantitative methods. The forecasting techniques discussed include expert opinions, chain ratio, historical analogy and regression analysis. These techniques vary in appropriateness with the purpose of the forecast, the type of product and availability of data.