1 of 16

Welcome!

Discovering opportunities & Forecasting demand

Dr. Satyendra Singh

Professor, Marketing & International Business

Conference Chair, ABEM Conference

University of Winnipeg, CANADA

s.singh@uwinnipeg.ca

2 of 16

Issues with international marketing research

Secondary data

Primary data

Estimating foreign demand/opportunities

Analyzing/Interpreting research information

Communicating with decision makers

2

3 of 16

Top 20 marketing research firms (in million)

3

4 of 16

Secondary data

Problem definition

Availability of data

No government agency, proxy, language barrier

Reliability of data

Too optimistic government, false data reporting, match production with sales

Comparability of data

Old data, data in different categories—definition of superstore, manager

Validating secondary data

Judgment validity—check for correlations e.g. diapers and babies

4

5 of 16

Primary data

Ability to communicate opinions

Must have the product, understand usefulness

Willingness to respond

Males, socially desirable answers, suspicious researcher, political interference

Sampling in field surveys

Sampling problems, no street names, no house nos., no accurate maps, outdated tel. directory, limited use of questionnaire/tel. method, lack of demographic details

Language and comprehension

Language barrier, equivalent concept eg def of family, literacy, back translation and parallel translation, conservative responses (Japan vs. USA)

5

6 of 16

Estimating market demand

Historical data, if available

Production + Import

Expert opinion for size and growth

Poll experts, sales managers, distributors, consultants, govt officials

Triangulation—compare estimates produced by different sources

Analogy (chain-ratio method)

Establish correlation between product and GDP/sales/…

6

7 of 16

Trend Cyclical Seasonal

7

Irregular demand ??

8 of 16

Analyzing and interpreting research information

Cultural understanding -- local interpreter

Adaptive research methodology -- more pictures, focus group

Skeptical about primary or secondary data

Correlate with other sources—governments…

8

9 of 16

Demand Forecasting: Values and Lifestyle (VALS - USA)�Motivation and resources

Thinkers

Reflective

Informed

Content

Believers

Literal

Loyal

Moralistic

Innovators

Take-charge

Sophisticated

Curious

Survivors

Nostalgic

Constrained

Cautious

Achievers

Goal oriented

Brand conscious

Conventional

Strivers

Contemporary

Imitative

Style conscious

Experiencers

Trend setting

Impulsive

Variety seeking

Makers

Responsible

Practical

Self-sufficient

9

10 of 16

Demand Forecasting: Values and Lifestyle (VALS - JAPAN) �Life orientation and Social Change

Innovator segments show a distinct and individualistic self-concept, high Levels of involvement and activity in areas of personal interest, and enthusiasm for innovations.

Adapter segments tend to follow the trends started by the Innovators in their interest areas, but at moderate levels of involvement and activity.

Pragmatic segments show slightly below average involvement and activity; flexible behavior, few distinct interests, and avoidance of risk.

Sustainers show low levels of activity, a focus on the past, and resistance to social change and innovations

10

11 of 16

Managing culture barrier in international marketing research

11

12 of 16

Group Exercise

Q1. Discover VALS (at least 5 segments) for any one country in Africa, Asia, Middle East, Far East, and South America.

Q2. These VALS / lifestyle-based segments should be based on 2 primary dimensions (X and Y axis).

Q3. Justify the selection of dimensions and segments. And link them to forecasting demand (ie #, %...) for each segment with justification.

Please email your file to s.singh@uwinnipeg.ca with group no and “Forecasting” in the subject line

12

13 of 16

Group activity

Q1. What is the difference between India and China sales? Comment.

Q2. Forecast demand for the next 4 weeks for both countries.

Q3. Justify the forecasting method.

Q4. Write any assumptions, if any, when using forecasting methods.

13

14 of 16

Group Exercise

Q1. Predict demand for Tyres in 2021?

Q2. Do you find seasonality?

Q3. Do you find cycle?

Q4. Do your find randomness?

Year

Snowfall (inches)

Demand for tyres

2011

25.6

2050

2012

27.6

1944

2013

22.4

2250

2014

24

1700

2015

28.2

1842

2016

22.2

2404

2017

23.4

1756

2018

25.2

1780

2019

23.8

2144

2020

24.6

1862

2021

26

 ??

14

15 of 16

Questions?�s.singh@uwinnipeg.ca

16 of 16