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Marketing Forecasting

Dr. E. D. Gailey 30 Mar 2015

Market Potential, Penetration, and Forecasting

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Market Potential

 Maximum potential number of units that can be sold at a given time

 How many target market customers have the desire and means to purchase the product?

 Example: What is the current market potential for HDTV in the U.S.?

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Market Potential Example - HDTV, U.S. Market

Market potential (U.S. market)

 115 million households (approx.)

 At an average price of $500, there are approximately 85% of households with income to purchase

 98 million households (= 115 million x 0.85)

 96% of those households live in an area with the infrastructure to support HDTV

 96 million households (= 98 million x 0.96)

 Average annual purchase rate is 20%

 19 million purchases (= 96 million x 0.20)

This is the current market potential (all brands)

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Market Potential Example - Cola Flavored, Carbonated Soft Drinks, U.S. Market

Market potential (U.S. market)

 290 million people 8 years and older

 People who consume carbonated soft drinks on a daily basis; 80%

 232 million people (= 290 million x 0.80)

 Proportion preferring cola-flavored; 60%

 139 million people (= 232 million x 0.60)

 Average number of carbonated soft drink occasions per day; 3

 152.2 billion carbonated soft drink occasions per year(= 139 million x 3 x 365)

 Average amount consumed per occasion (liters); 0.7 l.

 106.5 billion liters per year(= 152.2 billion x 0.7)

This is the current market potential (all brands)

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Useful Facts

Global population: 7.2 billion (2015)

U.S. population: 321 million (2015)

U.S. households: 115 million (2014)

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Market Penetration

 The percentage of current sales of the product (i.e., product category, product form, brand, or model) relative to the market potential

 Example: What is the current market penetration of HDTV in the U.S.?

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Market Penetration

 Example: What is the current market penetration of HDTV in the U.S.?

 Penetration (%) = current annual sales / market potential x 100

 17.8 million / 19.1 million x 100 = 93%

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Product Diffusion and PLC

 Product diffusion evaluates how quickly consumers will adopt (i.e., purchase) the new product based on the consumers’ perspective of the product

 PLC tracks the effects of changes in the market on demand for the product

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Product Diffusion and PLC

Product diffusion is based on first time purchases

PLC is based on total purchases

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Diffusion and Rate of Adoption

 Rate of adoption is a measure of how quickly a new product is accepted by consumers.

 Market development index measures actual purchases relative to maximum potential purchases.

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Source: Marketing Management by Best, 4th ed.

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Factors that Influence Rate of Adoption

1. Relative advantage

2. Observability of benefits

3. Relative simplicity

4. Trialability

5. Risk (to consumer)

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Product Adopters Categories

Early majority 34%

Late majority 34% Early

adopters 13.5%

16% 2.5%

Innovators

Laggards and nonadopters

Source: Adapted with permission from Marketing, 11/e, Acetate 8-8, by Michael J. Etzel, Bruce J. Walker, and William J. Stanton. The McGraw-Hill Companies, Inc. © 1997. All rights reserved.

See text Exhibit 6.5, p. 152 for characteristics

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Major Forecasting Methods

 Existing Products (useful in short- term forecasting when growth is steady)

 Regression

 Moving average

 Extrapolation

 New and Existing Products (useful in long-term forecasting)

 Bass model 13

Forecasting Considerations

 Lead Indicators

 Other significant influences  Example – Gas prices of purchases of fuel

efficient vehicles

 Example – Interest rates on high price products

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Bass Model

 Bass equation constants 1. Coefficient of Innovation (p) – Related to

the probability that a individual will adopt a product at any time, without the influence from other people.

2. Coefficient of Imitation (q) – Influence of adopters on non-adopters.

3. Market Potential

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Bass Model

 Three Methods of Use  Before introduction to market

1. Analogy – Base on coefficients of similar products

 After introduction to market

2. Trial and Error – Adjust coefficients based on initial data

3. Statistical estimation – Adjust coefficients based on initial data using statistical optimization techniques

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