lecture 5 market measurement

Market Measurement

Chapter 5

What it is and Why it is important• Measuring primary and selective demand• Why it is Important? Identify various opportunities Size and rate of growth of markets shape

corporate strategies Estimates of industry and company sales

essential for marketing strategies, programs, and budgets for individual products

Bench mark to evaluate performance of a company, a product, a sales territory, or a distributor

What it is and Why it is important

• Essential for marketing managers to: Understand the procedures commonly used to gather

and estimate market measurements Understand with the limitations of the measurements and

potential sources of errors or bias inherent in them Market measurement techniques are estimates Can not simply accept a single measure as perfectly

accurate By understanding the assumptions used to develop any

measure can better evaluate :- degree to which such measures are optimistic or

pessimistic- the reliability of the measures

Basic types of Market Measurement

1. Actual Sales:a. Industry salesb. Company sales2. Sales forecast:a. Industry sales forecastb. Company (or product line, brand) sales forecast3. Market Potential: Current market potential the upper limit of demand

for a product within a defined period a. Current Market Potential: The maximum sales opportunity that can be

achieved by sellersb. Future market potential

Relationship among basic kinds of market measurements

• Company sales will be lower than industry sales, and industry sales will be below market potential. ( only exception to rule monopoly)

• The ratio of company sales to industry sales is the market share

• Changes in the rates in any of the three measures - market potential, industry sales, or company sales changes , the gaps will increase or decrease


• Changes in market potential may be the result of either more users or current users purchasing more often

• Industry sales may change over time for several reasons:

Prices may decrease, improving potential customer’s ability to buy

Industry’s marketing efforts may become more intensive , so a greater number of potential customers fully perceive or obtain product benefits

Environmental factors ( such as economic conditions or changing social values) may stimulate the willingness or ability to buy the product


• Company sales may change over time for one of two reasons

1.Industry sales may change because of change in market potential. That is the primary demand change.

2. Some firms may gain sales and increase their market share at the expense of competitors by offering and promoting superior combination of benefits.

Strategic implications of these measures

• If a large gap exist between market potential and industry sales then a large primary gap exist.

- This means that managers should examine the factors influencing primary demand

• If a large difference exist between industry sales and company sales, then a selective demand gap exist

- Managers should examine the buyer’s choice processes to identify opportunities to increase market share

Defining What to measure• Must clearly specify the relevant market in

order to measure industry sales and market potential

• The relevant market must be defined in terms of product form, customer segment, and time.

• Example a cereal manufacturer could explore market potential for

1. All cereals or some variant cold cereal ( Product form)

2. The mass market or some segment, such as southwest, or single household

3. The next quarter or next year (time)

Absolute Market Potential

• Absolute potential is an estimate of maximum potential demand, usually based on number of factors:

i. the number of potential users ii. the rate of purchase• Absolute potential indicates the total dollar or

unit volume that could be sold in a given market.

• Three kinds of decisions rely on estimates of absolute market potential

Decisions that rely on estimates of absolute market potential

1. Evaluating Market opportunities: To assess what market opportunities to pursue in the

future In order to justify resource commitments in the case of

new product-form or new product-class markets In the case of existing products, market opportunities

can be examined if the market potential can be compared with industry sales

- If the market potential is significantly larger than industry sales, then all suppliers have an opportunity to increase their sales volume by pursuing policies (such as lower price) to close the primary market demand

- If industry sales are already close to market potential, then a firm will know that the only avenue for sales growth is to improve its market share.


2. Determine sales quotas and objectives Potential demand in some territories may be

growing so rapidly that that sharp yearly increases in sales objectives are appropriate

In other territories it may be stagnant in the number of potential buyers and purchase rates

A fair evaluation of sales force and distributor performance should be based on the potential for sales in the market


3. Determining the number of retail outletsThe potential in a given retail market area

will be a major input to these decisions

Measuring Absolute Market Potential

• Two essential components of absolute market potential are:

1.The number of possible users

2.The maximum rate of purchase

• Estimates of absolute market potential by geographic area, industry type, household type can be obtained from:

- trade associations

- commercial research firms

Estimating Market Potential in Consumer Market

• Use published data when characteristics of the potential buyers is known and readily measurable

• Both government and private sources are employed (statistical survey of Pakistan, Imports from customs. Income-tax, industry reports, etc.) when:

- Potential buyers for consumer goods can be described in terms of basic demographic or locational factors

• If data on total industry sales are given average demand per household (or person) can be calculated

Relative Market Potential• The percentage distribution of market

potential among different portions of a market( such as geographic areas or customer groups)

• Three major applications of relative market potential

1. Allocation of promotional expenditures2. Allocation of sales people among territories3. Locating facilities ( warehouse, district sales

office, manufacturing plant, etc.)

Measuring Relative market share• Corollary factors are measurable and

likely to be correlated with market potential

• Examples of single corollary factors are:Housing units for appliancesDisposable income levelsNumber of people over 50Average winter temperature

Targeting High-Potential markets• Industry and company sales may vary quite sharply

across geographic territories• In some territories, per capita purchase of products may

be very high as compared to those in other territories• Primary demand gap is some what larger in areas with

low per capita sales• Similarly brand share differences often vary across

markets• Marketers construct special indexes to portray these

difference• A category development index (CDI), is a measure that

help identify the territories in which category primary demand gaps are relatively large or small

• A brand development index (BDI) is a measure that can be used to assess selective demand across territories

Calculating A Development Index

Area Annual Case Sales (Category or Brand)

Thousands of households

Sales per thousand

Total

A

B

C

1600,000

22,500

13,500

52,000

80,000

900

750

2400

20

25

18

22

Total Index for each territory is calculated as:

Index = Sales per thousand household in territory x 100

Index

100

125

90

110

Sales per thousand Total

• Category and brand development indexes are useful as diagnostic tools to help managers identify the markets in which primary demand and selective demand gap exist

1. High CDI/ High BDI: In these territories both brand and category consumption is high. There is little need for development activity

2. High CDI/ Low BDI: The brand needs support if it is to grow. Promotional and distribution support is probably low

3. Low CDI/ High BDI: opportunities appear to exist to expand primary demand if management can identify why some people are not using the product

4. Low CDI/ Low BDI: Neither the brand or the category has widespread acceptance in the market

Sales Forecasting

• Sales forecasts are estimates of future levels of sale

• These market measurements can have a tremendous impact on all functional areas of an organization because they are used in making number of different decisions

Basic Types of sales Forecast

• There are two basic types of sales forecast:

1. Industry sales forecast and

2. Company sales forecast

Industry sales forecast

• Total sales that will be achieved by all the suppliers in relevant market

• Depending on how the firm has defined the relevant market, industry sales could be determined for:

- a product form,

- product class,

- or for all competing product classes satisfying the same generic need


• There are four basic uses of industry sales forecast

1. Industry sales forecast indicate expected rates of growth of alternative markets.

- They are useful elements in corporate marketing planning

- Indicate different rates of growth for various product form or classes

- Decisions on appropriate relevant market can be made


2. Rate of industry sales growth has major influence on competitive intensity

- If forecast indicates a dramatic decline in rate of industry growth. Management knows future company sales gains must come from increase in market

3. Industry sales forecast are also important to middle management.

- Knowing the future level of industry sales enables a firm to calculate the market share required to reach its sales goals

4. Rate of industry growth generally has a major influence on company sales growth

Company Sales forecast• Company sales forecast can be developed at more

than one level• A company may wish to forecast company sales of a

specific item ( regular size Tide), a brand (Tide), a product line (P & J detergents) or total company (all P&J sales)

• Forecast at item level are generally more useful for decision related to production scheduling and transportation of goods to distributors

• Forecasting at higher level of aggregation, company sales, are most useful for overall company financial planning

• From a marketing strategy and planning perspective, the most important forecast are those that focus on brand sales or product line sales because marketing decisions are most often designed to influence sales at these level of aggregation

• Not all forecasting approaches are equally useful for marketing decision making

• Even when brand or product line sales are being forecasted, the value of forecast to managers will depend on the type of approach used to develop the forecast

• Time series methods are generally used to get the best estimate of expected sales

• Descriptive forecasts are appropriate to explain how our price and marketing budget might influence future sales

Time Series Based Forecasting Methods• Basic assumption underlying time-series models is

that sales can be forecasted with acceptable accuracy by examining historical sales patterns

• These models are relatively easy to use because the only data needed are past sales and these models can be implemented by means of easy to obtain canned computer programs

• A further advantage is that the possible range of the deviations of actual sales from forecasted sales ( called forecasting error) can be estimated statistically

• As a general rule, time series models are more useful when market forces are relatively stable within forecasting horizon

• If sales trends are not likely vary because of economic changes, marketing actions, or technology, these models are likely to be reasonably accurate

• Such conditions are often found when short-run forecast horizon ( less than 1 year) are required

• They may also be found over longer forecast periods in case of markets that technologically mature, are not very susceptible to effects of economic fluctuations, and are expected to witness few major changes in marketing effort

• Even in the most stable markets, however, seasonal variations, changes in trends and random fluctuations do occur

• Accordingly variety of methods have been developed for “smoothing out” random fluctuations by averaging recent sales levels, giving weights to monthly sales levels to adjust for season ability, and increasing the importance of most recent data.

• Consider figure 5.2. the dots in this figure portray annual sales for Tootsie Roll company from 1984 - 1993

Moving Averages• This method is based on the average of some

specified historical period to focus the value of a future period. Table 5-10 provides the sales forecast for a 3 year moving average.

• The forecast for 1987 is the average of sales of 1984, 1985, and 1986

• The forecast error is the difference between actual sales and forecasted sales

• Limitation is that all the years used to create the moving average are given equal weights

Exponential Smoothing• More weights are given to recent years• Exponential smoothing allows differential weighting of the years. • The formula for exponential smoothing is

Y( t +1) = α At + (1 – α) Yt

Y(t +1) is the forecasted value, α is the smoothing constantAt is the actual sales for the period tYt is the forecasted sales for the period tThe sales forecast, with a smoothing constant of .5 for 1990

( table 5.10)148.91 = (.5) 179 + ( 1 - .5) 118

The smoothing constant is restricted to values between zero and one. The larger the smoothing constant, the greater emphasis on more recent years

• When the data are characterized by an increasing trend, both moving averages and exponential smoothing estimates will always be below actual sales

Straight Line Projections

• In cases where pronounced trends exist, random fluctuations are not severe, and managers wish to forecast several periods in future, line fitting approaches are employed to identify the sales time series

• A computer program is used to determine the equation of best “fitting line” – the line or the curve that closely approximates the historical trend.

• This equation is then used to forecast future sales by projecting that same line or curve into future

Questions for evaluating the reliability of time series forecasts

1. Do we have long enough history of sales data to construct a reliable trend

2. Can we expect industry growth trends to level off because industry sales are approaching market potentials

3. Is it likely that industry sales will shift because of economic , demographic, or technological factors?

4. Can new competition can be anticipated that will influence industry or company sales

5. Can we expect major changes in the marketing activity of competitors

6. Does industry/ company have production capacity to fulfill industry / company sales forecasts

7. Does our company plan any major change in its marketing program

Descriptive models – based forecasting methods

• When environmental changes can be expected to create a shift in the historical pattern of sales , then time series models are likely to prove unsatisfactory

• In such situations forecasting techniques that link sales to one or more factors thought to cause or influence sales

• Descriptive models such as multiple regression models are used when a number of factors have impact on sales

• Multiple regression models allows to incorporate the expected effect of any controllable marketing variable likely to be significant when one is forecasting company sales

• The goal is to assess the relationship between these controllable variables and sales

• Can variation in sales for different time periods be explained by levels of price, promotion, distribution, so on in those time periods

• A multiple regression model with sales as the dependent variable and the controllable factors as predictors or independent variables, will address this question

• Consider table 5-12 represents data on market share for a leading brand

• Notice that market share varies from low of 46.61 percent in period 14 to a high of 61.08 in period 21

• The factors used to explain variation in sales are relative price levels, distribution and advertising

• The relative levels are the ratio of the company level to the industry average

• The multiple regression model based on the data in table5-12 isMarket share =.61 – 1.11(relative distribution

+.97(relative price) + .04 (relative advertising)

• Many factors could explain why market share varies from one period to another, the model explains greater than 60% of the variation is based on relative level of price, distribution, and advertising

• The company determined the standard error of forecast of 0.25 i.e., two third of the time the estimates of the sale will be with in standard error of actual sales. 95% of the time forecasted share will be with in 2 standard error( 0.5) of actual market share

• Multiple regression allows managers to predict dependable variable( for example market share) for different levels of predictor variable price, distribution and price

• If we set relative price at .95, relative distribution at 1.06 and advertising at 1.0 , the estimated level based on the multiple regression model as

• Market share = .61 - .97(.95) + 1.11(1.06) + .04(1.0)

Judgmental Models

1. Jury of executive opinion

2. Delphi techniques

Interpreting the Forecast

• Sensitivity AnalysisIf several techniques gives essentially the same results, the

reliability of a forecast should be greaterSome firms develop parallel forecast based on alternative

techniquesKnowing how different techniques or assumption lead to

alternative estimates enables a manager to determine how sensitive the forecast is to a change in these factors

When forecasts are highly sensitive managers should expect greater imprecision and should closely monitor the environment to find out which model and which assumption must closely approximate reality

Possible Results of Company Sales Forecast Errors

Results of Over Estimation

Excess capacity leading to layoff, loss of skilled labor

Price cuts or additional marketing expenses

Distributor ill will because of excess distributor inventories

Inventory costs:

Cash flow problems and cost of capital tied up in finished goods, components or raw materials

Technical obsolescence or damage

Storage or warehousing costs

Results of Under Estimation

• Loss of sales or consumer goodwill• Overtime costs• Costs of expediting shipments• Reduced quality control because of

reduced maintenance of machinery or full production capacity

• Production bottlenecks because of lack of materials and parts

lecture 5 market measurement

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