Chapter _ 5 Measuring Market Opportunities

5/28/2018 Chapter _ 5 Measuring Market Opportunities

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Measuring MarketOpportunities: Forecasting

and Market KnowledgeChapter 5


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A Forecasters toolkit

Statistical and other quantitativemethods

Statistical methods use past history and variousstatistical techniques, such as multiple

regression or time series analysis, to forecast

the future based on an extrapolation of thepast.

Not useful for entrepreneurs.

In established firms, for established products,

statistical methods are extremely useful.


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Limitations of S & Q methods

As with all forecasting methods, statistical

methods have limitations. Most important oneis that they generally assume that future will

look very much like past.

If product or market characteristics change,

statistical models used without adequate

judgment may not keep pace.


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Observation.

This method is to directly observe or gather existing

data about what real consumers do in the productmarket of interest.

Observation based forecasting is attractive because itis based on what people actually do.

If data can be found from existing secondry sources-in company files, at the library, or on the internet-data collection is both faster and cheaper than a new

study, from scratch. Does not apply to new products.


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Surveys or Focus Groups

These surveys can be done with different

groups of respondents. Consumers after being shown a statement or a

prototype or sample of the product, can be

asked how likely they are to buy, creating asurvey of buyers intentions.

The sales people can be asked how much they

are likely to sell, completing a survey of salesforce opinion.


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Limitations of Focus groups

What people say is not always what people do.

The persons who are surveyed may not be

knowledgeable.

What people imagine about a product conceptin a survey may not be what is actually

delivered once the product is launched.


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Analogy

Used when neither statistical method nor

observations are possible to forecast the salesor market potential for a new product .

Then in such case analogy is used.

Under this method, the product is comparedwith similar products for which historical dataare available.

Limitation is that new product is never exactlylike that to which the analogy is drawn.


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Judgment

Sometimes forecasts are made solely on the basis of

experienced judgment or intuition. Some decisionmakers are intuitive in their decision processes andcannot always articulate the basis for their judgments.

Those sufficient forecasting experience in a marketthey know well, may be quite accurate in theirintuitive forecasts.

As a limitation judgment cannot be defended

compared to evidence-based methods, when the twodiffer.


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Market test

Market tests of various kinds are the last of our

most commonly used methods. Used largelyfor new products, market tests such as

experimental test markets may be done under

controlled experimental conditions in research

laboratories, or in live test markets with real

advertising and promotion and distribution instores.


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Mathematics entailed in Forecasting

The combination of judgment and other

methods often leads to the use of either of twomathematical approaches to determine the

ultimate numbers: the chain ratio calculation or

the use of indices.


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Rate of diffusion of innovations

This theory seeks to explain the adoption of an

innovative product or service overtime among agroup of potential buyers.

This is particularly useful for entrepreneurs or other

marketers to see if the investment in development andintroduction of the new product will be adopted by

the target market or not.

This is useful to mangers in predicting the adoptionrate.


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The adoption process

This involves the attitudinal changes

experienced by individuals from the time theyfirst hear about a new product , service, or idea

until they adopt it. Some tend to adopt early,

some late, and some never.


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Five stages of adoption process

1. Awareness. In this stage the person is only

aware about the product, and is motivated toseek information about the product.

2.

Interest. Here individual is sufficientlyinterested in it but has not yet involved.

3. Evaluation. Here the individual is mentally

applying the product to his own requirementsand anticipating the results.


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Five stages of adoption process

4. Trial. Here the individual actually uses the

product, but will not yet adopt it.

5. Adoption. In this stage the individual not only

continues to use the new product but alsoadopt it.


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The rate of adoption

Those who adopt a product go through the

five stages in adoption process.

1. The risk , cost of product failure or

dissatisfaction.2. The relative advantage over other products.

3. The relative simplicity of the new product.

4.Its compatibility with the previously adopted

ideas and behavior.


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The rate of adoption

5. The extent to which its trial can be

accomplished on a small scale basis.

6. The ease with which the central idea of the

new product can be communicated.


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Adopter categories

Using time of adoption as a basis for

classifying individuals, five major groups canbe distinguished:

Innovators.

Early adopters

Early majority

Late majority

Laggards.


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These adopter groups can be considered marketsegments.

One would use a different set of strategies tomarket a new product to the early adopter groupthan to market it to the late majority group.

Commercial sources are most important at theawareness stage in the adoption process, while

personal influence is most important at

evaluation stage. In the interest stage both areimportant. In trial stage marketers shouldfacilitate the prospect to try the product .


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Implications of diffusion of

innovation theory

A good way to estimate how quickly an

innovation is likely to move through thediffusion process is to construct a chart that

rates the adoption on the six key factors

influencing adoption speed.

View Exhibit 5.7


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Keys to good forecasting

The first key is to make explicit the assumptions on

which the forecast is based. This way if there isdebate or doubt about the forecast, the assumptions

can be debated, and data to support the assumptions

can be obtained.. The second key is to use multiple methods. When

forecasts obtained through different methods,

converge near a common figure, greater confidencecan be placed in that figure.


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Sources of error

Forecasters are subject to anchoring bias, even

though market conditions have changed .

Capacity constraints are sometimes

misinterpreted as forecasts.

Incentive pay can be a source of bias in

forecasting.

Implicit assumptions can overstate a wellintentioned forecast.


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Market knowledge systems

Internal record systems.

Marketing databases.

Competitive intelligence systems.

Client contact and sales force Automationsystems.

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Chapter _ 5 Measuring Market Opportunities