Product forecasting
From Wikipedia, the free encyclopedia
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 unmeet needs and competitive alternatives.
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[edit] Bass model
where,
- F(t) is the probability of adoption at time t
- f(t) is the rate at which adoption is changing with respect to t
- N(t) is the number of adopters at time t
- m is the total number of consumers who will eventually adopt
- p is the coefficient of innovation
- q is the coefficient of imitation
Multivariate techniques such as regression can be used to determine the values of p, q and N if historical sales data is available.
[edit] Assessor model
The Assessor model was developed at MIT by Silk and Urban (1978). Assessor is a trial and repeat model that determines final market share as the product of trial and repeat. Assessor is actually a series of models that each determine key inputs into the model.
[edit] Preference
By examining the brand preference for each brand in a competitive context, preference shares for each brand can be determined.
[edit] Awareness Model
Based on the brands planned marketing mix of advertising in multiple vehicles, the ultimate brand awareness can be projected through time.
[edit] Sources
- Frank Bass (1969), "A New Product Growth Model for Consumer Durables" Management Science, 15, 215-227
- A. J. Silk and G. L. Urban (1978), “Pre-Test-Market Evaluation of New Packaged Goods: A Model and Measurement Methodology,” Journal of Marketing Research, 15 (May) 171-191.
