Business Research

1. DATA COLLECTION METHODS
AND QUESTIONNAIRE
DESIGNING
( SCALES)
Session 1
SHONALI GHOSH

2. CONTENT
• DATA COLLECTION METHODS
• PRIMARY
• QUALITATIVE
• QUANTITATIVE
• OBSERVATION
• MEASUREMENT
• SECONDARY
• PRINCIPLES OF QUESTIONNAIRE DESIGNING
.
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3. THINGS TO REMEMBER
• Ask questions during intervals – time after each subtopic.
• Please note down questions
• Respond to questions I might ask; please be respectful of others’ opinions
• Be on mute , unmute when you have a question.
• Two breaks of 10 min each ( after an hour)
• Try and finish by 6 pm – keep 15 min for any question s you might have additionally
.
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4. A QUICK RECAP OF WHAT YOU
KNOW!
• Market research is about problem solving -
marketing , business or social.
• This can be done through – analyzing information
already available or asking questions to relevant
consumers/ customers
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5. • A paint manufacturer has developed a new premium paint finish, with
demonstrable superiority for wooden surfaces. He wishes to
ascertain acceptability of the product.
• A company has developed fruit based drinks in 3 blended flavours.
• Strawberry and orange
• Peach and grapes
• Watermelon, apple and grapes
He wishes to decide which 2 to launch
• A hindi daily that was a leader is facing stagnant sales and losing
share. Its current share is about 40% from 60%. Wants to reclaim
leadership position.
• A chain of ice cream parlours wants to set up outlets in a new city.
Property brokers have identified 5 shops available. Which should the
first 3 be given cost is not a constraint.
• What king of communication can we use in rural schools to teach
children to wash hands after defecation?
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6. BETTER RESEARCH
DESIGNS
Better Research Designs
Better Research Designs
Better Research Designs

7. LENS : DEGREE OF
CRYSTALLIZATION OF RESEARCH
QUESTION
• EXPLORATORY ( Define a marketing problem or a hypothesis)
• CONCLUSIVE ( Resolve a marketing problem or hypotheses)
• DESCRIPTIVE/DIAGNOSTIC
• CAUSAL
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8. • A paint manufacturer has developed a new premium paint finish, with
demonstrable superiority for wooden surfaces. He wishes to
ascertain acceptability of the product.
• A company has developed fruit based drinks in 3 blended flavours.
• Strawberry and orange
• Peach and grapes
• Watermelon, apple and grapes
He wishes to decide which 2 to launch
• A hindi daily that was a leader is facing stagnant sales and losing
share. Its current share is about 40% from 60%. Wants to reclaim
leadership position.
• A chain of ice cream parlours wants to set up outlets in a new city.
Property brokers have identified 5 shops available. Which should the
first 3 be given cost is not a constraint.
• What king of communication can we use in rural schools to teach
children to wash hands after defecation?
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EXPLORATORY OR CONCLUSIVE??

9. DATA COLLECTION METHODS TO
ADDRESS THESE RESEARCH
DESIGN QUESTIONS
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10. INTRODUCTION TO
PRIMARY RESEARCH
QUALITATIVE
QUANTITATIVE

11. KEY DIFFERENCES
• QUALITATIVE RESEARCH:
• Gain insights / understanding
• To develop hypotheses
• Understand linkages
• Does not seek to measure
• How, why, Why not?
• QUANTITATIVE RESEARCH:
• To validate hypotheses ( Yes, No)
• To measure absolute and relative indicators
• Who, What, When
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12. QUALITATIVE RESEARCH
What is its application?
• Providing in-depth understanding of consumer
beliefs, attitudes and behavior
• Understanding consumer language &
identifying parameters that can be used for
mapping consumer attitude and behaviour
• Understanding dynamics of industry & key
issues (expert interactions)
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13. QUANTITATIVE RESEARCH
Application areas
• Ranking ideas and concepts
• Making volume projections
• Evaluating relative and absolute strength of
products, concepts, advertising,
promotions, and packaging
• Pricing decisions
• Consumer segmentation within a category
• Measuring habits and practices
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14. HIGHLIGHTING DIFFERENCES
Quali Quanti
Objective Describe,
Understand
Measure,
Track
“Questions” Why, why not
How
What
When
How Much
Method Indirect response
Unstructured
Small Sample, depth
Direct
Questions
Structured
Large sample,less depth
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15. POINT TO REMEMBER...
• QUALITATIVE OR QUANTITATIVE:
• NOT SUBSTITUTES
• BUT COMPLEMENTARY
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16. BASICS OF QUALITATIVE
RESEARCH

17. THE TECHNIQUES
COMMONLY USED:
•FOCUS GROUPS
•ONE-ON-ONE DEPTH
INTERVIEWS
•OBSERVATIONS
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18. FOCUS GROUPS - OPTIONS
• Normal 8-10 respondents, discussion
• Mini groups (4-6 respondents)
• Extended discussions
• Reconvened groups
• Creativity groups
• Peer groups
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19. FOCUS GROUPS - DYNAMICS
WORKS BEST IF HOMOGENEITY HAS BEEN
MAINTAINED:
•AGE
•INCOME
•GENDER
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20. DEPTH INTERVIEW - OPTIONS
• One-on-ones
• Paired / couple interviews
• Family interviews
• Triadic interviews
• Allows in depth probing + confrontational
techniques : users vs non users, likers vs dislikers.
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21. PROJECTIVE TECHNIQUES
• Projective techniques are indirect and unstructured methods of
investigation which have been developed by psychologists
• Use projection of respondents for inferring about underline motives, urges
or intentions which cannot be secured through direct questioning as the
respondent either resists or cannot reveal
• Word Association : Gain feedback on new brand names, uncovering
product or brand attributes, and building a picture of how a product is
positioned.
• Sentence , story completion :Completed quickly, to capture initial thoughts
before the response is rationalized. This encourages creative thinking and
can uncover thoughts and attitudes associated with various situations.
• Photo / Picture sort :Photo sorts is a technique in which participants are
presented with a stack of photos or images. They are then asked to pick
those that they most associate with a brand or attribute. Effective in gaining
insight into emotions that might not have immediately come to mind
• Colors , scenery, emojis,
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22. PROJECTIVE TECHNIQUES
• Brand Personification /Obituary : Became human, celebrity, animal ….
Personality of the brand , What will you miss or wont
• Role Play : Customer Service ( good and bad)
• Courtroom Drama: Strengths and weaknesses of a brand / product
• Time machine : Trend catching
• Withdrawal Technique : Life without product or brand. What
difference will it make?
• Moodboards : Participant do design the mood board
using products like magazines, newspapers, color-pens, glitter-pens,
and fabrics etc. Understand feeling and emotions
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23. OBSERVATIONS - ADVANTAGES
• Access to real behavior
• Opportunity to explore actions which respondents may forget or
might be unaware off
• Understanding the dynamics in real life
• Helps identify customer service elements, communication inputs,
merchandising and shelf display , buyer behaviour ( sku’s),
product bundling …
• Physical – manual ( static situation)
• Accompanied shopping
• Mystery Shopping
• Video Observation
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24. CHOOSING THE BEST
TECHNIQUE
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FOCUS GROUPS DEPTH INTERVIEWS
When interactions are
limited .
Pre school children on
breakfast cereals
When interactions of the
participants will spark
new thoughts
Physicians discussing
treatment procedures
Value of the
Interaction
When subject matter is so
sensitive that few
respondents would speak
openly in a group setting
Safe sex practices followed
When subject matter is
such that participants will
not withhold information
or temper remarks
Decision making on cars
Sensitivity
of the
subject

25. CHOOSING THE BEST
TECHNIQUE
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FOCUS GROUPS DEPTH INTERVIEWS
When turn around time is
not critical and budget
allows the higher costs of
execution and reporting
When turn around time is
critical and need to
economise
Cost and
Timing
Permits greater depth of
response per individual;
also use when subject is
complex and respondents
are very knowledgeable.
Attitudes to mobile
communication
Assumes most
respondents can say all
that they know in 30 -40
minutes
Group conducted among
women on use of prepared
cake mixes
Depth of
Information
per
respondent

26. CHOOSING THE BEST
TECHNIQUE
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FOCUS GROUPS DEPTH INTERVIEWS
Use when respondents
geographically dispersed
Assumes that an
acceptable number of
respondents can be
assembled in one
location
Logistics

27. 
BASICS OF QUANTITATIVE
RESEARCH

28. VARIOUS DESIGNS POSSIBLE
AROUND TWO THEMES...
• Descriptive research that aim to collect info:
• Demographic, lifestyle
• Beliefs, attitudes, behaviour (past/intended)
• Experimental research that aims to measure
impact of stimulus on response:
• Concept test - product/advt./Idea
• Product test - use/clinics
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29. SOME EXAMPLES...
Q: inputs for improvement in newspaper X
Q: impact of a new execution for a cola ad?
Q: willingness to continue online classes?
Q: % people aware of how covid is transmitted?
Q: which of the 12 shoe polishes is liked most?
Q: which of the two car models is preferred?
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30. SOME EXAMPLES...
Q: demographic profile of middle class households
Q: profile of ford fiesta, SX 4, honda city owners for
marketing verna in mumbai
Q: satisfaction post purchase of LG refrigerator
Q: ipad buyers satisfaction with product
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31. SECONDARY RESEARCH
Use of previously existing resources
to meet your research objectives

32. • An approximate answer is good enough to take decisions
• Approximate answers can be got through logic and some
secondary data (may be, sometimes a bit of luck! - Remember
fate favours the brave)
IN MANY REAL LIFE MARKETING
SITUATIONS...
33
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33.  Internal company data
 Government publications
 Trade / industry associations
 Newspapers / magazines / trade journals
 International publications ( euromonitor)
 Syndicated sources
 TAM – TELEVISION RATING POINTS
 IRS – INDIAN READERSHIP SURVEY
 RETAIL AUDIT
 HOUSEHOLD PANEL
 TGI
 E COM REPORTS
SOURCES OF SECONDARY RESEARCH :
BIG DATA
34
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34.  ADVANTAGES
◦ Low cost
◦ Lesser time / effort involved
◦ Gives broad perspective / develop hypothesis
 DISADVANTAGES
◦ Data may not be aligned to the research objectives
◦ Data may be out dated
◦ Data may not be in desired manner
◦ Not fully conversant with the methodology
adopted
ADVANTAGES AND
DISADVANTAGES OF
SECONDARY RESEARCH
35
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35. BREAK!
15 MINUTES
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36. QUESTIONNAIRE DESIGN
37

37. PROCESS INVOLVED...
LISTING OF INFORMATION NEED

INSTRUMENT DESIGN

DATA COLLECTION
38

38. INFORMATION AREAS - How it
influences instrument design?
• A exhaustive listing of "what" should be
collected
• Determined by research objectives - "why" is
the information needed ?
39

39. 2. RESEARCH INSTRUMENT -
WHAT IT ESSENTIALLY DOES?
• A measurement tool intended to collect required information most
accurately - "reliable & valid"
Example:
• "32% preferred bournvita as against 22% for boost"
• “Average consumption of butter in upper income households in
approx. 40 gms per day"
• "20% object to the campaign slogan"
40

40. DATA COLLECTION PROCESS - What
implications on instrument?
• Aimed at collecting information with
minimal error:
• Interviewer carelessness, bias, interpretation,
training level etc.
• Respondent ego, humility, fatigue,
commitment etc.
• Method of administering: mailer, personal -
home/CLT/intercept, telephonic, internet etc.
41

41. WATCH OUT FOR “INFORMATION
POLLUTION”
INFORMATION
INFORMATION
TOO LITTLE
INFORMATION
INFORMATION
INFORMATION
INFORMATION
Just Right
INFORMATION
INFORMATION
INFORMATION
INFORMATION
INFORMATION
INFORMATION
INFORMATION
Too much
42

42. QUESTIONNAIRE DESIGN -
SCALES
43

43. The ABCs of attitudes:
 The Affective Component (based on feelings or overall
evaluation) Feelings of like or dislike
 The Behavioral Component (likely action toward object; e.g.
from a consumer behavior point of view, the consumer’s
intention to buy a product) Intention to behave
 The Cognitive Component (based on beliefs; what you
think about a marketing stimulus) – Information
possessed
Three components of
attitudes
44

44. Classifies data according to a
category only.
E.g., which color people select.
Colors differ qualitatively not
quantitatively.
A number could be assigned to each
color, but it would not have any value.
The number serves only to identify
the color.
No assumptions are made that any
color has more or less value than any
other color.
Nominal scale
45

45.  Assign subjects to groups or categories
 No order or distance relationship
 No arithmetic origin
 Only count numbers in categories
 Only present percentages of categories
 Chi-square most often used test of
statistical significance
Nominal scale
46

46. Sex Social Class
Marital status Days of the week (months)
State Seasons
Ethnic group Types of restaurants
Brand choice Religion
Education: Graduate+, College, not grduate, upto Class 12
Other examples
Coded as “0” Coded as “1”
47

47. Classifies data according to some
order or rank
With ordinal data, it is fair to say that
one response is greater or less than
another.
E.g. if people were asked to rate the
hotness of 3 chili peppers, a scale of
"hot", "hotter" and "hottest" could be
used. Values of "1" for "hot", "2" for
"hotter" and "3" for "hottest" could be
assigned.
Ordinal scale
The gap between the items is unspecified. 49

48. Can include opinion and
preference scales
Median but not mean
No unique, arithmetic origin
Items cannot be added
In marketing research practice,
ordinal scale variables are often
treated as interval scale variables
Ordinal scale
50

49. Ordinal Scale
Small medium large
Quality
Satisfaction
T- shirt sizes
Examples
Rank Team Matches Points
1 Australia 28 3658
2 South Africa 29 3451
3 India 40 4705
4 Pakistan 28 3182
5 New Zealand 24 2714
6 England 31 3401
7 Sri Lanka 30 3184
8 West Indies 24 2178
9 Bangladesh 32 1494
10 Ireland 10 190
11 Zimbabwe 20 273
12 Kenya 7 75
51

50. Please rank the news programs offered in the following four
networks based on your preference.(1 for most preferred, 4 for
least preferred).
_____ Times Now
_____ NDTV 24X7
_____ Republic TV
_____ Star News
52

51. Assumes that the measurements are made
in equal units.
i.e. gaps between whole numbers on the scale
are equal.
e.g. Fahrenheit and Celsius temperature scales
An interval scale does not have to have a
true zero. e.g. A temperature of "zero" does
not mean that there is no temperature...it is
just an arbitrary zero point.
Can’t perform full range of arithmetic
equations. 40 degrees is not twice as hot as
20 degrees
Permissible statistics: count/frequencies,
mode, median, mean, standard deviation
Interval scale
53

52. How likely are you to visit Inorbit Mall within the next six months? (Please
select one answer)
Definitely will not visit___ 1
Probably will not visit ___2
May or may not visit ___3
Probably will visit ___4
Definitely will visit ___5
Interval scale
54

53. Similar to interval scales except that
the ratio scale has a true zero value.
E.G. The time something takes
Allows you to compare differences
between numbers.
Permits full arithmetic operation.
If a housewife buys 4 cakes of soap ,
then it is twice as many as 2 cakes.
Ratio scale
55

54. • Indicates actual amount of variable
– Shows magnitude of differences between points on scale
– Shows proportions of differences
• All statistical techniques useable
• Most powerful with most meaningful answers
• Allows comparisons of absolute magnitudes
Ratio scale
56

55. 0
1
2
3
4
5
6
7
Examples
height, weight, age,
length
time
income
market share
1.What is your annual income before
taxes? Rs……
2. How far is your college from
home?
_______ kilometres
57

56. Primary scales of measurement
Nominal Names
assigned to
eclairs
Ordinal Rank order of
preference
First Place Second
Place
Interval Taste rating on a 1-
5 Scale
4.8 4.5 4.2
Ratio No. of eclairs will
buy at a time 2.8 2.6 2.5
Third Place
58

57. Paired
compariso
n
Rank
order
Constan
t sum
Comparativ
e scales
Non-comparative
scales
Continuo
us rating
scales
Itemized
rating
scales
Stapel
Semantic
differential
Likert
A CLASSIFICATION OF SCALING
TECHNIQUES
SCALING TECHNIQUES
Others
59

58. TYPES OF SCALING
TECHNIQUES
 COMPARATIVE SCALES
• Involve the respondent directly comparing stimulus objects.
• e.g. How does Pepsi compare with Coke on sweetness
•ADVANTAGES :
•small diff between objects can be captured because
respondent is forced to choose
•Easily understood and applied
•Carryover effects reduced ( if CDM is rated on a 5 pt. scale and
then Nestle is rated. Will Nestle ratings be affected?)
•DISADVANTAGES
•Inability to generalise beyond compared items. ( Compared A, B, C.
No inference on D)
60

59. TYPES OF SCALING
TECHNIQUES
 COMPARATIVE SCALES
 NON-COMPARATIVE SCALES
• Respondent scales each stimulus object independently of other
objects
•e.g. How would you rate the sweetness of Pepsi on a scale
of 1 to 5?
•Also called Monadic scales
61

60. Comparative scales:
paired comparison items
• A and B
• A and C
• A and D
• B and C
• B and D
• C and D
• No. of comparisons would be [n(n-1)]/2
If we have blends of coffee A, B, C and D, we would have
respondents compare
–usually limited to 15 comparisons
62

61. Comparative scales:
paired comparison items
• If we have 3 brands of eclairs , we would ask :
• Please tell me overall , thinking of Nestle and CDM
, which one do you prefer overall ?
• Nestle or CDM?
• Similarly ask for CDM vs Candyman and
Candyman vs Nestle.
63

62. Allocate a total of 100 points among the following soft-drinks depending on
how much you like each; the more you like each soft-drink, the more points
you should allocate to it. (Please check that the allocated points add to 100.)
Coca-Cola _____ points
7-Up _____ points
Mirinda _____ points
Fanta _____ points
Pepsi-Cola _____ points
100 points
COMPARATIVE SCALES: CONSTANT
SUM SCALES
64

63. Please divide 100 points among the following aspects that a person may
use to decide upon selecting a particular bank. Please distribute the
points so that you give more points to the aspect that you consider more
imp ortant t to you in the selection of a bank
Hours of service ________________
Friendliness _______________
Distance from home ________________
Investment services ________________
Parking facilities __________________
Comparative scales:
constant sum scales
65

64. Rank the following soft-drinks from 1 (best liked ) to 5 (least liked) according to
your taste preference:
Coca-Cola _____
7-Up _____
Fanta _____
Pepsi-Cola _____
Mountain Dew _____
√ Top and bottom rank choices are ‘easy’
√ Middle ranks are usually most ‘difficult’
Comparative scales:
Rank order scales
66

65. Needs fewer items to be ranked as compared to Paired
comparison ( n-1).
Provides ordinal data
 Easily understood – but not suitable for large number of
test products
If transitivity is assumed , then can be transformed into
paired preference and vice versa.
Transitivity
A>B and B>C , then A>C
Comparative scales:
rank order scales
67

66. Paired
compariso
n
Rank
order
Constan
t sum
Comparativ
e scales
Non-comparative
scales
Continuo
us rating
scales
Itemized
rating
scales
Stapel
Semantic
differential
Likert
A classification of scaling techniques
SCALING TECHNIQUES
Others
68

67. Continuous scale
• How would you rate this class to other
classes of MR this term ?
The worst The Best
X
X
Non comparative scale
•Respondent places a mark on a continuous line. So does
not have to select from given codes.
•Coding is a problem even in online qres.
69

68. NON-COMPARATIVE SCALE
VERSION 1
Worst Best
VERSION 2
Worst Best
10 20 30 40 50 60 70 80 90 100
VERSION 3
Worst
Very
Bad Bad nor Good Very Good Best
VERSION 4
Worst
Very
Bad Bad nor Good Very Good Best
10 20 30 40 50 60 70 80 90 100
70

69. Itemized Rating Scales
Semantic
Differential
scale
The Likert scale
Stapel scale
71

70. Modern Store
Low prices
Unfriendly staff
Narrow product
range
Attractive Schemes
Old- fashioned store
High prices
Friendly staff
Wide product range
Unattractive Schemes
SEMANTIC DIFFERENTIAL SCALE
Most often is a 5 pt or 7 pt scale.
Bipolar – with opposite meanings or either side, separated by boxes at
equal intervals. The assumption is of an ‘equal interval’ scale – so
arithmetic operations possible
72

71. SEMANTIC DIFFERENTIAL SCALE
The basic analysis is calculating mean scores by assigning weights to
boxes.
Modern Store Old- fashioned store
5 4 3 2 1
Weight No. of Resp
Modern 5 40 200
4 30 120
3 20 60
2 10 20
1 10 10
Old Fashioned Total 110 410
Mean score 410/110 3.73
73

72. LIKERT SCALE ( VERBAL SCALES)
Strongly
disagree
Disagree Neither
agree nor
disagree
Agree Strongly
agree
Cost is the most important
consideration when buying a
new car
1 2 3 4 5
Usually used to measure attitudes
74

73. •Very important
•Important
•Moderately important
•Of little importance
•Unimportant
•Very important
•Moderately important
•Unimportant
•Very good
•Good
•Acceptable
•Poor
•Very poor
•Extremely poor
•Below average
•Average
•Above average
•Excellent
•Good
•Fair
•Poor
IMPORTANCE
QUALITY
How important is price to you when purchasing jeans?
How would you rate the quality of Dell laptops?
75

74. LIKELIHOOD How likely will you be to purchase a car in the next 6
months?
•Definitely
•Very probably
•Probably
•Possibly
•Probably not
•Very probably not
•Likely
•Unlikely
76
•Definitely
•Probably
•May or may not
•Probably not
•Definitely not

75. Stapel scale
+5
+4
+3
+2
+1
quality
-1
-2
-3
-4
-5
+5
+4
+3
+2
+1
service
-1
-2
-3
-4
-5
Rank TGIF on quality and
service
Unipolar scale
No neutral point or zero.
Analysed same way as
Semantic
Diff.
Difficult to understand??
77

76. Select a plus number for words that you think
describes the store accurately. The more
accurately you think the work describes the
store, the larger the plus number you should
choose.
Select a minus number for words you think do
not describe the store accurately. The less
accurately you think the word describes the
store, the larger the minus number you should
choose,
Therefore, you can select any number from +5
for words that you think are very accurate all
the way to -5 for words that you think are very
inaccurate.
A Stapel scale for measuring a store’s image
Lifestyle
+5 +5 +5
+4 +4 +4
+3 +3 +3
+2 +2 +2
+1 +1 +1
HIGH POOR WIDE
QUALITY SERVICE VARIETY
-1 -1 -1
-2 -2 -2
-3 -3 -3
-4 -4 -4
-5 -5 -5
78

77. SOME BASIC CONSIDERATIONS
WHEN SELECTING A SCALE
Balanced versus
non-balanced
alternatives
Number of
categories
Odd or even number
of scale categories
Forced versus non-forced
choice
Labelled vs End anchored 79

78. Odd
Strongly agree _____
Agree _____
Neither Agree, nor Disagree
_____
Disagree _____
Strongly disagree _____
Even
Strongly agree_____
Agree _____
Disagree _____
Strongly disagree___
ODD VERSUS EVEN
 If neutral responses likely, use odd
number
If want to force responses : even
80

79. Balanced vs. Unbalanced
 In general, scales tend to be balanced to
allow for a neutral position
If we know that skew is likely , then use
an unbalanced scale for discrimination (
user satisfaction)
Excellent
Very Good
Good
Poor
Very Poor
Extremely Poor
Excellent
Very Good
Good
Somewhat Good
Poor
Very Poor
81

80. Forced vs. Unforced
Forced
Extremely reliable ___
Very reliable ___
Somewhat reliable ___
Somewhat unreliable ___
Very unreliable ___
Extremely unreliable ___
Unforced
Extremely reliable ___
Very reliable ___
Somewhat reliable ___
Somewhat unreliable ___
Very unreliable ___
Extremely unreliable ___
Don’t know ___
 If resp are likely not to have an opinion then unforced.
If unwilling to disclose then forced ( users opinion can be forced),
unless its an attribute that wasn’t in their consciousness.
82

81. Labeled vs. End anchored
Labeled
Excellent _____
Very good _____
Fair _____
Poor _____
Very Poor _____
End Anchored
Excellent _____
_____
_____
_____
Poor _____
 Labelled scales – less ambiguous .
However , scale points have to be right- else skew reading
End anchored subject to respondent interpretation.
83

82. Labeled
Excellent _____
Very good _____
Fair _____
Poor _____
Very poor _____
Excellent _____
Very good _____
Fair _____
Poor _____
Very poor _____
Issue with verbal scales when transformed into Interval
:Intervals may not reflect the ssemantic mmeaning of the
Adjectives
Intervals are
not equal
Intervals are
not equal 84

83. Number of scale points
5 Point
Excellent _____
_____
_____
_____
Poor _____
10 Point
Excellent _____________
_____________
_____________
_____________
_____________
_____________
_____________
_____________
_____________
_
____________
Poor
 Range : 3 – 7 ; 5 most common
If respondent is knowledgeable about – more points can be used.
If the attribute has nuances – more scale point. ( two favorite
restaurants)
If there is very different real differences between test objects – more
scale points
85

84. CHARACTERISTICS OF GOOD
MEASUREMENT SCALES
1. RELIABILITY
• The degree to which a measure accurately captures
a true outcome without error
• Synonymous with repetitive consistency
2. VALIDITY
• The degree to which a measure faithfully represents
the underlying concept (it asks the right questions)
3. SENSITIVITY
• The ability to discriminate meaningful differences
between attitudes. The more categories the more
sensitive (but less reliable)
86

85. VALIDITY AND RELIABILITY
 Reliability can be more easily determined than
validity
 If it is reliable, it may or may not be valid
( Tailor measuring you for a coat , when you want a
jacket)
 If a measure is valid, it may or may not be reliable
( He is measuring you for a jacket , but the measurement
may or may not be correct)
 If it is not reliable, it cannot be valid
 If it is not valid, it may or may not be reliable
87

86. Reliability and Validity
Neither Reliable
Nor Valid
Reliable But
Not Valid
Reliable
And Valid
88

87. Example of low validity, high
reliability
• Scale is perfectly accurate, but is capturing the
wrong thing; for example, it correctly measures
consumers’ interest in a brand rather than
intention to buy.
ASKED
How interested would you
say you are in …..Brand?
•Definitely not interested
•Probably not Interested
•May or May not be
interested
•Probably interested
•Definitely interested
INSTEAD OF
How likely would you say
you are in
BUYING…..Brand?
•Definitely not buy
•Probably not buy
•May or May not buy
•Probably buy
•Definitely buy 89

88. Example of validity, low reliability
• Scale measures consumers’ intention to buy,
but poorly worded items, sloppy administration,
data entry errors lead to random errors in data
ASKED
How likely would you say
you are in
BUYING…..Brand?
•Definitely not buy
•Probably
•May or May buy
•Probably
•Definitely buy
INSTEAD OF
How likely would you say
you are in
BUYING…..Brand?
•Definitely not buy
•Probably not buy
•May or May not buy
•Probably buy
•Definitely buy
90
ASK

89. DATA COLLECTION METHODS
AND QUESTIONNAIRE
DESIGNING
( SCALES)
Session 1
END
SHONALI GHOSH