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'''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 (business)|distribution]], [[price]], fulfilling unmeet needs and competitive alternatives. | |||
==Bass model== | |||
Bass model is one type of forecasting method primarily used in new product forecasting. In general, there will be no historical demand for new product. Then, Bass model tries to capture shape of demand of existing product and apply new product. | |||
{{main|Bass diffusion model}} | |||
<math>\frac{f(t)}{1-F(t)} = p + \frac{q}{m} N(t)</math> | |||
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. | |||
==Fourt-Woodlock model== | |||
The [[Fourt-Woodlock_equation|Fourt-Woodlock]] model is another method used to estimate product sales. | |||
<math>V = (HH \cdot TR \cdot TU) + (HH\cdot TR\cdot MR \cdot RR \cdot RU)</math> | |||
The left-hand-side of the equation is the volume of purchases per unit time (usually taken to be one year). On the right-hand-side, the first parentheses describes trial volume, and the second describes repeat volume. | |||
HH is the total number of households in the geographic area of projection, and TR ("trial rate") is the percentage of those households which will purchase the product for the first time in a given time period. TU ("trial units") is the number of units purchased on this first purchase occasion. MR is "measured repeat," or the percentage of those who tried the product who will purchase it at least one more time within the first year of the product's launch. RR is the repeats per repeater: the number of repeat purchases within that same year. RU is the number of repeat units purchased on each repeat event. | |||
==Assessor model== | |||
===Preference=== | |||
By examining the brand preference for each brand in a competitive context, preference shares for each brand can be determined. | |||
Assessor is owned by M/A/R/C Research ( http://www.marcresearch.com/ ) and can be used for concept screening, testing and volumrtric forecasting. In combination with Choice Modeling it can be used to optimize offers and products. | |||
===Awareness Model=== | |||
Based on the brands planned [[marketing mix]] of advertising in multiple vehicles, the ultimate brand awareness can be projected through time. | |||
== 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. | |||
== External links == | |||
* [http://www.bassbasement.org/BassModel/ The Bass Model - Frank M. Bass Official Website] | |||
[[Category:Market research]] | |||
Revision as of 02:03, 31 January 2014
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.
Bass model
Bass model is one type of forecasting method primarily used in new product forecasting. In general, there will be no historical demand for new product. Then, Bass model tries to capture shape of demand of existing product and apply new product. Mining Engineer (Excluding Oil ) Truman from Alma, loves to spend time knotting, largest property developers in singapore developers in singapore and stamp collecting. Recently had a family visit to Urnes Stave Church.
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.
Fourt-Woodlock model
The Fourt-Woodlock model is another method used to estimate product sales.
The left-hand-side of the equation is the volume of purchases per unit time (usually taken to be one year). On the right-hand-side, the first parentheses describes trial volume, and the second describes repeat volume.
HH is the total number of households in the geographic area of projection, and TR ("trial rate") is the percentage of those households which will purchase the product for the first time in a given time period. TU ("trial units") is the number of units purchased on this first purchase occasion. MR is "measured repeat," or the percentage of those who tried the product who will purchase it at least one more time within the first year of the product's launch. RR is the repeats per repeater: the number of repeat purchases within that same year. RU is the number of repeat units purchased on each repeat event.
Assessor model
Preference
By examining the brand preference for each brand in a competitive context, preference shares for each brand can be determined. Assessor is owned by M/A/R/C Research ( http://www.marcresearch.com/ ) and can be used for concept screening, testing and volumrtric forecasting. In combination with Choice Modeling it can be used to optimize offers and products.
Awareness Model
Based on the brands planned marketing mix of advertising in multiple vehicles, the ultimate brand awareness can be projected through time.
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.