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  2. Forecasting - Wikipedia

    en.wikipedia.org/wiki/Forecasting

    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. In addition to climate, such variations can also be due to holidays and customs: for example, one might predict that sales of college football apparel ...

  3. Demand forecasting - Wikipedia

    en.wikipedia.org/wiki/Demand_forecasting

    An example of a model for forecasting demand is M. Roodman's (1986) demand forecasting regression model for measuring the seasonality affects on a data point being measured. [11] The model was based on a linear regression model , and is used to measure linear trends based on seasonal cycles and their affects on demand i.e. the seasonal demand ...

  4. Bass diffusion model - Wikipedia

    en.wikipedia.org/wiki/Bass_diffusion_model

    The basic premise of the model is that adopters can be classified as innovators or as imitators, and the speed and timing of adoption depends on their degree of innovation and the degree of imitation among adopters. The Bass model has been widely used in forecasting, especially new product sales forecasting and technology forecasting.

  5. Marketing mix modeling - Wikipedia

    en.wikipedia.org/wiki/Marketing_mix_modeling

    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.

  6. Product forecasting - Wikipedia

    en.wikipedia.org/wiki/Product_forecasting

    Product forecasting is the science of predicting the degree of success a new product will enjoy in the marketplace. To do this, the forecasting model must take into account such things as product awareness , distribution , price , fulfilling unmet needs and competitive alternatives.

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    It utilizes predictive models to analyze a relationship between a specific unit in a given sample and one or more features of the unit. The objective of these models is to assess the possibility that a unit in another sample will display the same pattern. Predictive model solutions can be considered a type of data mining technology.

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