Dont Ask a Silly Question

1
Dont Ask a Silly Question

• Using Analytics for Business Insight

2
Welcome/Intro

• Andrew Parsons
• Associate Professor of Marketing at Massey
  University.
• Taught Marketing Research for over a decade.
• Been involved in the industry for nearly 20
  years.
• Catherine Bentham
• Lecturer, Marketing at The University of
  Auckland.
• Taught Marketing Research and Statistics for the
  last 6 years.
• Currently undertaking a PhD in Marketing
  Research.

3
Agenda
Persuasion to Positioning

• Descriptives vs. Analytics
• Usefulness vs. Ease of Use
• Setting up analytics with ease
• Secondary data
• Questionnaire design
• Analytic tools
• Finding a solution
• Beer market example

4
Dont ask a silly question

• Increasing need for market research to provide
  decision support and help develop marketing
  strategies.
• Traditional research has simplistically
  studied the market, which is a result of poor
  technology and increased regulation.
• CEO Farm equipment company.
• Only by asking intelligent questions will we be
  able to produce helpful and intelligent strategic
  insights.

5
Descriptives vs. Analytics
?
?
?
?
?
6
Why is all of this Important???

• Example
• Situation based segmentation
• Persuasion vs. Positioning

7
Secondary Data

• Spend a little time up front.
• Success is 99 percent preparation, if you set
  yourself up for winning, rarely will you fail.
• Michael Smith in The Inside Edge, by Peter James

8
Secondary Data

• Gain customer and competitive intelligence
• Talk to internal decision makers (in their
  language)
• Talk to qual researchers
• Talk to industry experts - suppliers, retailers
• Talk to customers
• Do a little desk research the internet is a
  powerful source
• Stats New Zealand, Investor relations sites,
  management profiles, speeches, press releases,
  employment opportunities.

9
Questionnaire Design

• List your objectives
• What kind of relationships do you wish to
  explore?
• How appropriate is it to adapt questions from a
  previous questionnaire?
• What kinds of data are required to achieve
  objectives?
• Produce table of objectives
• Summary Statements
• Used to sum up respondents overall opinions
• Important for prediction/ exploration of
  relationships

10
Questionnaire Design

• Scales
• Consistency vs. reverse coding
• Think about variation
• Categorical vs. ratings
• 10, 7, 5 or 3 point scales
• Importance
• Ratings vs. rankings

11
Questionnaire Design

• Question Writing Pitfalls
• Missing questions
• Irrelevant questions
• Response categories
• Level of variation
• Are all response categories mutually exclusive
  and collectively exhaustive
• Demographics/psychographics
• Are there any other mistakes in the
  questionnaire?
• Double-barrelled questions
• Leading questions
• Difficult to understand

12
Questionnaire Design

• Demographics vs. Psychographics
• What are you asking these for?
• What is knowing this going to contribute to the
  understanding for the client?

13
Questionnaire Design

• MR Traditionally Measures 2 Things
• Attitudes A, B, C
• Characteristics
• Psychographics/Lifestyles Etc
• Where do these fit in?

14
The Tools

• Backwards Research
• What are the questions you need to answer?
• What do you wish to achieve?
• Prediction
• Positioning
• Relationships and Differences
• Identify Underlying Concepts

15
The Tools

• Many different tools
• Tools differ due to two main reasons
• Different objectives (e.g., positioning vs.
  relationships)
• Different data format (e.g., categorical vs.
  continuous)
• This is the key to understanding all analytic
  choices.

16
The Tools

• Now dont panic, its probably just your job to
  know the ingredientsthe analyst will produce
  this for you.
• Prediction
• Prediction of a continuous variable
• Multiple Regression
• Conjoint Analysis (trade-offs)
• Prediction of a categorical variable
• Logistic Regression
• Discriminant Analysis

17
The Tools

• Positioning
• To group segments for people and produce a
  perceptual map
• Multidimensional Scaling
• To group people into segments
• Cluster analysis

18
The Tools

• Relationships and Differences
• Categorical Variables
• Cross Tabulations and Associated Tests
• Continuous Variables
• Correlation
• Continuous Dependent Variable
• Hypothesis Tests
• Analysis of Variance (ANOVA)
• Analysis of Covariance (ANCOVA)
• Multiple ANOVA (MANOVA)
• Multiple ANCOVA (MANCOVA)

19
The Tools

• Identify Underlying Concepts
• Factor Analysis

20
Lets Try This

• Example The beer market

Please note All information presented in this
example is created for purposes of demonstration
and in no way based on reality.
21
Example The Beer Market
Research Questions
Questions in Survey
Proposed Analysis
Objective
Section
To understand the position of Carlton Draught in
comparison to other international beers.
Which of the following international beers are
you aware of? (list) ?Categorical

• Secondary data analysis
• Awareness question in survey

Who are the other beers in the market space?
One
Which attributes do you consider to be associated
with the various beers? ?Continuous

• Secondary research
• Qual research
• Perceptual Map

What are the positioning attributes?
Two
22
Example The Beer Market
Research Questions
Section
Questions in Survey
Proposed Analysis
Objective
To understand the position of Carlton Draught in
comparison to other import beers.
Divide 100 points between attributes in terms of
their importance when you choose a
beer. ?Continuous

• Interpretation of attributes (descriptives)
  

Salience of attributes.
Two
Characteristics of individuals -demographics
-psychographics -situation ?Continuous and
Categorical

• Secondary research
• Qual research

Does the market segment?
Three

• Cluster individuals on attribute salience and
  profile clusters on characteristics

What are the bases of this segmentation?
23
Example The Beer Market

• Does the market segment?
• Are there different groupings within the data
  with different perceptions?
• What are the bases for the segmentation?
• Construct a basic cluster analysis of individuals
  and profile the clusters.

24
Position of Carlton Draught in comparison to
other International beers.
Construct a perceptual map for each segment
High Quality/Seen Drinking
Truly International Brand
Value for Money
25
Position of Carlton Draught in comparison to
other International beers.
Use correlations to interpret the dimensions on
the perceptual map
26

• How do Carlton Draught really position
  themselves??????