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The ideal sales information system should
represent a compromise
between what managers think they need, what managers really need and what is
economically feasible.
For example, to know the need of advertising and to set the size of
advertising budget by the Brand Managers, they should know the degree to
marketing
saturation, the rate of sales decline in the absence of advertising and
the spending plan of competitors.
The information system is to be designed to provide these data needed of
making the key marketing decision.
Analytical Marketing System :
An
analytical
marketing system consists of advanced techniques for
analyzing marketing data and problems. Such a system normally includes a
Statistical Bank and a Model Bank.
a) Statistical Bank
This is a collection
of statistical procedure, for extracting meaningful
information from data. It includes normal statistical tools like averages,
regression analysis, cross tabulation, discriminant analysis,
factor analysis and
cluster analysis
b) Model Bank
This is a collection of models which aid decision making. A model may
be defined as set of variables and their interrelationships designed to represent a
real system. Such models help in the stimulation of real life situations there by
enabling prediction and control. Some models which have came to be used
extensively by companies include.
-
Sales forecasting models.
-
Transportation planning model.
-
Media mix planning model.
Models can be of two types–namely: i) descriptive model & ii)
decision
model.
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I)
Descriptive Model :
These models are designed to communicate, explain or predict. The
descriptive models can be built at three levels.
i)
Macro Model :
This consists of a few variable and a set of relationships among them.
Ex. Relationship between sales and national income, price and advertising etc.
ii)
Micro Analytical Model :
It specifies more links between a dependent variable and its
determinants, eg. impact of advertising and sales through linkages, reach
frequency, consumer trial etc.
iii)
Micro behavioural Model :
This model creates hypothetical entities
who interact and produce a
record of behaviour which is then analyzed.
Besides queuing models also describe waiting line situations and their
impact.
II)
Decision models :
Decision models assist managers to circulate alternatives and find
optimum solutions. Ex. Differential calculus mathematical programmes
statistical decision models and game theory.
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