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A bottom-up sales forecast at the SKU-account/POS level requires taking into account product attributes, historical sales levels and store specifics. The large number of different variables which describe the product, the store and the promotion attributes, both quantitative and qualitative, could potentially have many different values.
The Bass model has been widely used in forecasting, especially new product sales forecasting and technology forecasting. Mathematically, the basic Bass diffusion is a Riccati equation with constant coefficients equivalent to Verhulst—Pearl logistic growth .
Marketing mix modeling (MMM) is an analytical approach that uses historic information to quantify impact of marketing activities on sales. Example information that can be used are syndicated point-of-sale data (aggregated collection of product retail sales activity across a chosen set of parameters, like category of product or geographic market) and companies’ internal data.
The final step is to then forecast demand based on the data set and model created. In order to forecast demand, estimations of a chosen variable are used to determine the effects it has on demand. Regarding the estimation of the chosen variable, a regression model can be used or both qualitative and quantitative assessments can be implemented.
Some forecasting methods try to identify the underlying factors that might influence the variable that is being forecast. For example, including information about climate patterns might improve the ability of a model to predict umbrella sales. Forecasting models often take account of regular seasonal variations.
It is a measure used to evaluate the performance of regression or forecasting models. It is a variant of MAPE in which the mean absolute percent errors is treated as a weighted arithmetic mean. Most commonly the absolute percent errors are weighted by the actuals (e.g. in case of sales forecasting, errors are weighted by sales volume). [3]
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The Monte Carlo method in Excel Prof. André Farber Solvay Business School; Sales Forecasting, vertex42.com; Pricing using Monte Carlo simulation, a practical example, Prof. Giancarlo Vercellino; Personal finance. A Better Way to Size Up Your Nest Egg, Businessweek Online: January 22, 2001
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