global consumer buying power: segmentation and forecasts prepared by chris holling, executive...

Global Consumer Buying Power: Global Consumer Buying Power: Segmentation and ForecastsSegmentation and Forecasts

Prepared byChris Holling, Executive Managing Director, Business Planning Solutions

May 25, 2005

Copyright 2005 Global Insight, Inc. 2

Sizing and Forecasting Markets

Income Distribution

Socio-Economics\Culture

Demographics

Size & Forecast Size & Forecast Your Target Your Target

MarketMarket

Consider, quantify, and validate all the potential drivers of demand for your products.


Developing a Comprehensive Methodology

Database integration, statistical analysis, and econometric modeling capture the complex relationships between market characteristics and market size.

HouseholdDemographics

Macroeconomic Analysis

ConsumerSegmentation

Consumer MarketsDemand/Sales


The Key to a Successful Model

Include the appropriate concepts

Represent the true timing of reactions

Possess coefficients with the appropriate magnitudes

Earn the confidence of users

To be successful, a model must:

4Copyright 2005 Global Insight, Inc.


Start with the Demographics

Product 1

Product 2

Product 3

Product 4

Product 5

Product 6

Product 7

Product 8

15-19 20-24 25-29 30-44 45-54 55-64

Each segment has a different target market, which is incorporated into the sales forecasting models.

Target markets can differ across countries.


Consider All the Drivers of Demand

5.8

4.4

0.9

0.4

-0.7

-2.4

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

Inflation Adjusted Apparel Prices

Unemployment Rate*

Consumer Confidence

Population

Per Capita Disposable Income

Per Capita HH Net Worth

Compound Annual Growth Rate, 2002-07

Source: Global Insight


The Process Is Key to Generating Buy-in

Sales of Product X = 1.1 x (Office Const.) + .35 x (Corp. Profits) + ... + constant


Data are Dumb…You Must be Smart

Structural modeling is the most trustworthy Search for causation, not correlation Be clear whether you are modeling

demand or supply — only one per equation

T-statistics are often misinterpreted T’s measure precision of estimate, not

whether a factor is important Multicolinearity must be dealt with

through constraints, not exclusion of good factors



Benchmark Results Against Relevant Experience

Counter-intuitive elasticities are usually a sign of spurious correlation, data errors, or multicolinearity

Short-run income elasticities should be high for discretionary goods, particularly items that consumers can postpone purchasing

Price elasticities should be high when close substitutes are available

Demographic factors, often trend-like, are easily confused with penetration curves


Modeling: A Good Model?

The task: Develop a country-wide product sales model using 1997–2003 historical data

Typical drivers were used: income, relative price, demographics, rate of urbanization

Results: Great fit! Great regression statistics!

R-squared = .98

Durbin-Watson = 1.86

S.E. of regression = 1.9%

75

80

85

90

95

100

105

110

1997 1998 1999 2000 2001 2002 2003

Actual Solved

Actual versus Solved


Modeling: Let’s Be Careful Out There

A CLOSER LOOK The equation:

log(sales) = 9.6 + (-1.8)*log(income) + 2.7*log(relative price) + 5.7*log(rate of urbanization) A 1% increase in income suggests a 1.8% decrease in sales?

Unlikely! A 1% increase in the relative price suggests a 2.7% increase in sales?

Unlikely! A 1% increase in urbanized population suggests a 5.7% increase

in sales? Unlikely!

Clearly, a good fit and excellent regression statistics do not always result in the best equation!!


Global Consumer Markets Database

Income Distribution

Socio-Economics

Demographics

Size & Forecast Size & Forecast Your Target Your Target

MarketMarket

A Tool to …

Assess Overall Market Attractiveness Size Country Markets Anticipate Growth by

Customer Segment Identify Market Risk &

Exposure Conduct Product Penetration

Rate Analysis


Global Consumer Markets DatabaseGlobal Consumer Markets Database

Cross-country comparable data 10-year forecasts plus 10 or more

years of history, annual frequency 22 consumer product categories Detailed household income

distribution forecasts 95 Countries Population by gender and age Semi-annual updates

Uncover Market Opportunity & Risk



Demographics and Income Distribution by Country

Household Income Distribution *<$5K

>$5K–<$10K

>$10K–<$20K

>$20K–<$30K

>$30K–<$40K

>$40K–<$50K

>$50K–<$60K

>$60K–<$70K

>$70K–<$80K

>$80K–<$90K

>$90K–<$100K

>$100K–<$150K

>$150K

* Additional segments can be added on a custom basis

Population by Age and Sex0 to 4

5 to 9

10 to 14

15 to 19

20 to 24

25 to 29

Socio - EconomicsUrban Population

Households and Average Household Size

Educational Attainment Index and Illiteracy Rate

Education Expenditures

Health Expenditures

Education Enrollment (primary, secondary, tertiary)

Labor Force (male and female), unemployment

Life Expectancy and Fertility Rate

60 to 64

65 to 69

70 to 74

75 and over

30 to 34

35 to 39

40 to 44

45 to 49

50 to 54

55 to 59


Consumer Spending & Risk

Buying Power IndicatorsNational Wealth

Gross National Income

Disposable Income

Per Capita Disposable Income

Income Distribution

Consumer Spending by TypeDurables

Semi-durables

Non-durables

Services

Spending by Category *Food

Alcoholic Beverages

Non-Alcoholic Beverages

Tobacco

Clothing & Shoes

Household Equipment

Household Energy

Other Household Services

Transportation Equipment

Transportation Services

Communication

Entertainment

Education

Medical

Financial & Other Services

Restaurants & Hotels

Personal Care

* Additional categories can be added on a custom basis

Consumer Market Risk IndicatorCustom weighted index of relevant risk factors to companies servicing the consumer markets


Tap into Global Buying Power (Top 15 Consumer Markets)

China

India

Korea, South

Russia

Argentina

United States

Germany

France Canada

Japan

Italy

Brazil

United Kingdom

Spain Australia

Mexico

Taiwan

Hong Kong

Poland

0

5

10

15

20

25

30

35

40

45

50

0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10%

Consumer Spending Growth, 2004-09 CAGR (%)

Co

nsu

mer

Ris

k

Bubble Size = Consumer Spending, 2004 (1997 US$)


China and India Are on the Rise

Ranked number of households with income >US $20,000 (1997$)

1993 2003 2010 2020

US US US China

Japan Japan China US

Germany China Japan Japan

Russia Germany Germany India

China Russia Russia Germany

France France Brazil Brazil

UK UK France France

Brazil Brazil UK UK

Italy Italy Italy Indonesia

India India India RussiaSource: Global Insight’s Global Consumer Model incorporating U.N. and World Bank data


As the World’s Affluent Class Grows

Affluent: Households with income > $60kMiddle Class: Households with income $20k - $60k

Sum of 95 countries. Income reported in 1997$.

0.8

1.2

1.6

2.0

2.4

2.8

1988 1991 1994 1997 2000 2003 2006 2009 2012 2015 2018

Ind

ex 1

988

= 1

Affluent

Middle Class

Under $20k

Under 20k74%

Affluent11%

Middle Class15%


Target Specific Customers ...

Middle Class: Households with income $20k - $60kSum of 95 countries. Income reported in 1997$.

3.6% 2.7% 2.9% 14.9%9.4%1.5%17.1%7.5%4.1%

14.1%

0

10

20

30

40

50

China Brazil Poland Indo-nesia

Mexico Russia SouthKorea

Argen-tina

Hungary Pakistan

Nu

mb

er

of

Ho

us

eh

old

s (

mil

lio

ns

)

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

Labels Indicate the Compound Annual Growth Rate of the Middle Class: 2004-2020

Top Markets by Absolute Change in Number of Middle Class Households: 2004 – 2020


The Number of Young Children Peaked in 1991…

500

510

520

530

540

1988 1992 1996 2000 2004 2008 2012 2016 2020

Top Growing Markets

2004 to 2020 Absolute Increase (millions)

Pakistan +5.67

Uganda +3.16

Nigeria +3.16

United States +2.49

Iran +1.65

Top Declining Markets

2004 to 2020 Absolute Decrease (millions)

India -4.13

China -3.86

Brazil -1.19

Indonesia -1.15

Mexico -1.11

Ch

ild

ren

Ag

e 0

-to

-4 Y

ea

rs (

mill

ion

s)

Sum of 95 Countries in Global Consumer Markets Database


…Leading to a Peak in Young Adults in 2012

Top Growing Markets

2004 to 2020 Absolute Increase (millions)

India +18.27

Pakistan +6.74

Nigeria +6.11

Bangladesh +4.02

United States +2.43

Top Declining Markets

2004 to 2020 Absolute Decrease (millions)

Russia -5.21

Iran -2.65

China -2.62

Ukraine -1.62

Japan -1.60400

450

500

550

1988 1992 1996 2000 2004 2008 2012 2016 2020

Ad

ult

s A

ge

20

-to

-24

Ye

ars

(m

illio

ns)

Sum of 95 Countries in Global Consumer Markets Database


Cell Phone Culture

United States Russia India China Brazil

Clothing & Shoes 1.9% 3.5% 5.8% 5.4% 2.8%

Communication 2.0% 10.7% 16.1% 17.9% 6.3%

Entertainment 2.9% 6.6% 10.3% 12.8% 4.7%

Financial & Other Services 3.9% 7.3% 9.4% 15.3% 5.2%

Food 1.8% 1.0% 4.8% 7.1% 1.9%

Household Equipment 2.7% 9.2% 10.6% 12.7% 5.4%

Personal Care 3.8% 5.6% 8.6% 16.4% 4.6%

Restaurants & Hotels 2.1% 3.1% 5.8% 7.0% 2.9%

Transportation Equipment 2.1% 8.7% 12.9% 14.5% 5.3%

Total Consumption 2.0% 5.3% 3.3% 5.7% 1.7%

CAGR of Consumer Spending in 1997 US$

Category Spending Trends – Category Spending Trends – Consumer Expenditure Growth 2004-2009 (1997$ CAGR)Consumer Expenditure Growth 2004-2009 (1997$ CAGR)


The Rural Exodus: Led by China & India

URBANIZATION:URBANIZATION:

Top 10 by Absolute Increase in Urban Population: 2004 to 2020

millions of people

China +269.5

India +165.2

United States +51.8

Indonesia +44.4

Brazil +40.5

Nigeria +36.9

Pakistan +30.6

Philippines +24.0

Mexico +23.5

Bangladesh +22.7



Take it to the Next Level


Case Study 1: Calculating market opportunity by country based on household income distribution.

Case Study 2: Developing market attractiveness indexes to rank country markets and prioritize resource allocation decisions.

Case Study 3: Producing sales forecasting models to predict market demand by country.


Calculating Market Opportunityfor Product X in Brazil

Income Bracket in Real US$

Absolute Segment Size

in 2003

Estimated Penetration

Rate

Potential Customers

Less than $5K 19.5 million 9% 1.7 million

Between $5K and $10K 13.5 million 15% 2.0 million



Greater than $20K 9.2 million 97% 8.9 million

X =

Total Households 51.2 million Opportunity 17.6 million

Case Study #1 Case Study #1


Calculating Market Opportunity for Product X in Brazil

2003 represents an inflection point for market growth

2003-2020 CAGR = 3%

2003-2020 CAGR = 1.6%

100

120

140

160

180

200

220

240

260

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

2013

2015

2017

2019

Ind

ex 1

987

= 1

00

Total Households

Total Households

Potential Customers

Potential Customers

Missed Opportunity



Developing a Market Attractiveness Index

1. Identify key determinants of market attractiveness

2. Weight indicators based on their relative importance

3. Rank country and regional markets

4. Allocate sales and marketing resources

Note: Rank is from 1 (Best - top 10% of countries) to 10 (Worst - bottom 10% of countries). The lower the score, the more attractive the country.



China Demographic Variables: Age-Specific Weighting

Body

0%

3%

6%

9%

12%

15%

18%

15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59

Face

0%

3%

6%

9%

12%

15%

18%

15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59

Sun

0%

3%

6%

9%

12%

15%

18%

21%

15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59

Product X Product Y

Product Z



China: Weighted Demographic Indices

0.96

1.00

1.04

1.08

1.12

1.16

1.20

1.24

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

97 99 01 03 05 07 09 11 13 15 17 19

Level (left scale, index 1997=1.0)Year-over-year growth (right scale, percent)

Weighted Demographic Index - Face Products

0.96

1.00

1.04

1.08

1.12

1.16

1.20

1.24

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

97 99 01 03 05 07 09 11 13 15 17 19


Weighted Demographic Index - Body ProductsProduct X Product Y



United States: Weighted Demographic Indices

0.95

1.00

1.05

1.10

1.15

1.20

1.25

1.30

1.35

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1997 2000 2003 2006 2009 2012 2015 2018


Weighted Demographic Index - Face Products

0.95

1.00

1.05

1.10

1.15

1.20

1.25

1.30

1.35

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1997 2000 2003 2006 2009 2012 2015 2018


Weighted Demographic Index - Body ProductsProduct X Product Y



Brazil: Weighted Demographic Indices

1.0

1.1

1.2

1.3

1.4

1.5

0.5

1.0

1.5

2.0

2.5

3.0

1997 2000 2003 2006 2009 2012 2015 2018


Weighted Demographic Index - Body Products

1.0

1.1

1.2

1.3

1.4

1.5

0.5

1.0

1.5

2.0

2.5

3.0

1997 2000 2003 2006 2009 2012 2015 2018


Weighted Demographic Index - Face ProductsProduct X Product Y



Real Disposable Income per Capita

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2

3

4

5

6

7

8

9

10

1997 2000 2003 2006 2009 2012 2015 2018

Level (left scale, thousands of year 2000 US$)Year-over-year growth (right scale, percent)

Real Disposable Income Per Capita

China US

18

20

22

24

26

28

30

32

-1

0

1

2

3

4

5

6

1997 2000 2003 2006 2009 2012 2015 2018

Level (left scale, thousands of year 2000 US$)Year-over-year growth (right scale, percent)

Real Disposable Income Per Capita



China: Education Enrollment Rates

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

Primary Enrollment Rate Secondary Enrollment Rate Tertiary Enrollment Rate



United States: Education Enrollment Rates

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

110%

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020




Brazil: Education Enrollment Rates

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

110%

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020




China: Urban vs. Rural Population

0

100

200

300

400

500

600

700

800

900

1,000

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

Mil

lio

ns

Urban Population Rural Population



United States: Urban vs. Rural Population

0

50

100

150

200

250

300

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

Mil

lio

ns




Brazil: Urban vs. Rural Population

0

20

40

60

80

100

120

140

160

180

200

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

Mil

lio

ns




China: Driver and Forecast Comparisons

Real 2000 2001 2002 2003 2004 2005 2010 2015 20201997/ 2003

2003/ 2010

2010/ 2020

2003/ 2020

Millions of 1997 US$Body 94 98 103 106 113 122 172 233 299 5.8% 7.1% 5.7% 6.3%Face 1,084 1,231 1,423 1,581 1,761 1,939 3,075 4,912 7,573 14.5% 10.0% 9.4% 9.7%Sun 100 116 125 138 151 165 260 412 627 11.2% 9.4% 9.2% 9.3%Deodorant 10 11 12 12 12 13 17 29 47 12.8% 5.5% 10.4% 8.4%

DriversMillions of 1997 US$

Per Capita Income 0.7 0.7 0.7 0.8 0.8 0.9 1.1 1.5 1.9 5.5% 5.2% 5.4% 5.3%

H'hds with PPP Income >$15K 72.2 79.6 90.0 100.3 109.9 119.3 174.9 277.9 500.6 10.5% 8.3% 11.1% 9.9%Urban Population 456.4 471.6 487.0 504.5 521.1 537.3 618.3 703.2 790.5 3.5% 2.9% 2.5% 2.7%

Index 1997=1.0Demographic Variable-Body 1.03 1.04 1.05 1.06 1.06 1.07 1.07 1.13 1.15 0.9% 0.9% -0.1% 0.3%Demographic Variable-Face 1.04 1.06 1.07 1.09 1.10 1.12 1.12 1.18 1.22 1.5% 1.2% 0.1% 0.5%Demographic Variable-Sun 1.04 1.05 1.07 1.08 1.10 1.11 1.11 1.17 1.20 1.4% 1.1% -0.1% 0.4%Demographic Variable - Deod. 1.03 1.04 1.05 1.06 1.06 1.07 1.07 1.13 1.15 0.9% 0.9% -0.1% 0.3%

NominalMillions of Renminbi

Body 748 790 826 872 966 1,084 1,775 2,843 4,289 5.7% 10.7% 9.2% 9.8%Face 8,656 9,952 11,465 13,005 15,007 17,231 31,818 59,809 108,444 14.3% 13.6% 13.0% 13.3%Sun 802 936 1,004 1,137 1,288 1,468 2,687 5,023 8,972 11.0% 13.1% 12.8% 12.9%Deodorant 81 88 93 98 105 116 180 349 668 12.7% 9.1% 14.0% 11.9%

Average Annual Growth

Product WProduct XProduct YProduct Z

Product WProduct XProduct YProduct Z

WXYZ



For Additional Information:

Chris Holling, 416-682-7303

[email protected]

Thank you.

global consumer buying power: segmentation and forecasts prepared by chris holling, executive...

Documents

global consumer

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