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Marketing Management –II (MK102)
Session 7
Previous Session: Marketing Research Process
Source: Malhotra and Dash (6e)
Conclusive/Confirmatory
Exploratory
Research Design
Descriptive Causal
1. Pilot Surveys
2. Qualitative Research
Direct: FGDs & In-
Depth Interviews
Indirect: Projective
techniques
3. Secondary data
(Qualitative)
3. Case Study Analysis
1. Secondary data
(Quantitative)
2. Surveys
3. Observations
1. Experiments
Previous Session
Source: Malhotra and Dash (6e)
Conclusive/Confirmatory
Exploratory
Research Design
Descriptive Causal
1. Pilot Surveys
2. Qualitative Research
Direct: FGDs & In-
Depth Interviews
Indirect: Projective
techniques
3. Secondary data
(Qualitative)
3. Case Study Analysis
1. Secondary data
(Quantitative)
2. Surveys
3. Observations
1. Experiments
Necessary Conditions for Causality
1. Concomitant Variation
2. Time Order of Occurrence
3. Absence of Other Possible Causal Factors
X Y
Y
Advertising Experiment at
Restaurant Grades
Controlling Extraneous Variables
Randomisation:
o Random
assignment of
test units to
treatment
conditions
Matching:
o Comparing test units
on key background
variables before
assigning to treatment
conditions
Example: Matching
stores (on sales, size,
etc.) before varying
customers’ service
Statistical Control:
o Measuring
extraneous variables
& adjusting for their
effects through
statistical analysis
Example: ANCOVA
Design Control
o Use of
experiments
designed to
control specific
extraneous
variables
Qualtrics Experiment
https://iima.au1.qualtrics.com/jfe/form/SV_5gvZ2otZYh3bfng
Sample Questionnaire
1. Consent Form
2. Treatment Conditions/Control (Size of the gift menu: 3 gifts vs. 6 gifts)
3. Dependent Variable (Choice )
4. Manipulation Check (Perceived size of the gift menu)
5. Controls (Liking towards Gift)
6. Basic Information (Age, Gender)
7. Debriefing
Validity in Experimentation
Internal Validity:
o Whether manipulation of IVs actually caused
observed effects on DVs.
o Control of extraneous variables is a
necessary condition
External Validity:
o Whether cause-and-effect
relationships found in the experiment
can be generalized
o To what populations, settings, times,
IVs, and DVs can results be projected?
Lab
Experiments
Field
Experiments
Lab vs Field Experiments
Factor Laboratory Field
Environment Artificial Realistic
Control High Low
Demand artifacts High Low
Internal validity High Low
External validity Low High
Time Short Long
Number of units Small Large
Ease of implementation High Low
Cost Low High
Source: Malhotra and Dash (6e)
Conclusive/Confirmatory
Exploratory
Research Design
Descriptive Causal
1. Pilot Surveys
2. Qualitative Research
Direct: FGDs & In-
Depth Interviews
Indirect: Projective
techniques
3. Secondary data
(Qualitative)
3. Case Study Analysis
1. Secondary data
(Quantitative)
2. Surveys
3. Observations
1. Experiments
Limitations of Experiments
1. Experiments can be time consuming
2. Experiments are often expensive
3. Experiments can be difficult to administer
4. Competitors may deliberately contaminate results of field experiments
Source: Malhotra and Dash (6e)
Data Collection
Online Offline
Questionnaire Preparation
Softwares Online Data Collection
Platforms
Source: Malhotra and Dash (6e)
Data Collection
Online Offline
Step 5
Step 4
Step 3
Step 2
Step 1
Source: Malhotra and Dash (6e)
1. Descriptive
2. T-test
3. ANOVA
4. Regression Analysis
MBA Salaries
Context
Marie Dear: An aspiring MBA applicant, interested in the starting salaries of graduating
students.
Questions:
1. How much can students expect to make on graduation?
2. Are there any variables (e.g., gender, native language, quartile,
GMAT score, etc.) that affect the starting salaries of students?
3. Did students like the MBA program offered by the college?
Source: Malhotra and Dash (6e)
1. Descriptive
2. T-test
3. ANOVA
4. Regression Analysis
Thank You

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marketing - MK102_Session 7_2023_Final.pdf

  • 1. Marketing Management –II (MK102) Session 7
  • 2. Previous Session: Marketing Research Process Source: Malhotra and Dash (6e) Conclusive/Confirmatory Exploratory Research Design Descriptive Causal 1. Pilot Surveys 2. Qualitative Research Direct: FGDs & In- Depth Interviews Indirect: Projective techniques 3. Secondary data (Qualitative) 3. Case Study Analysis 1. Secondary data (Quantitative) 2. Surveys 3. Observations 1. Experiments
  • 3. Previous Session Source: Malhotra and Dash (6e) Conclusive/Confirmatory Exploratory Research Design Descriptive Causal 1. Pilot Surveys 2. Qualitative Research Direct: FGDs & In- Depth Interviews Indirect: Projective techniques 3. Secondary data (Qualitative) 3. Case Study Analysis 1. Secondary data (Quantitative) 2. Surveys 3. Observations 1. Experiments
  • 4. Necessary Conditions for Causality 1. Concomitant Variation 2. Time Order of Occurrence 3. Absence of Other Possible Causal Factors X Y Y Advertising Experiment at Restaurant Grades
  • 5. Controlling Extraneous Variables Randomisation: o Random assignment of test units to treatment conditions Matching: o Comparing test units on key background variables before assigning to treatment conditions Example: Matching stores (on sales, size, etc.) before varying customers’ service Statistical Control: o Measuring extraneous variables & adjusting for their effects through statistical analysis Example: ANCOVA Design Control o Use of experiments designed to control specific extraneous variables
  • 7. Sample Questionnaire 1. Consent Form 2. Treatment Conditions/Control (Size of the gift menu: 3 gifts vs. 6 gifts) 3. Dependent Variable (Choice ) 4. Manipulation Check (Perceived size of the gift menu) 5. Controls (Liking towards Gift) 6. Basic Information (Age, Gender) 7. Debriefing
  • 8. Validity in Experimentation Internal Validity: o Whether manipulation of IVs actually caused observed effects on DVs. o Control of extraneous variables is a necessary condition External Validity: o Whether cause-and-effect relationships found in the experiment can be generalized o To what populations, settings, times, IVs, and DVs can results be projected? Lab Experiments Field Experiments
  • 9. Lab vs Field Experiments Factor Laboratory Field Environment Artificial Realistic Control High Low Demand artifacts High Low Internal validity High Low External validity Low High Time Short Long Number of units Small Large Ease of implementation High Low Cost Low High
  • 10. Source: Malhotra and Dash (6e) Conclusive/Confirmatory Exploratory Research Design Descriptive Causal 1. Pilot Surveys 2. Qualitative Research Direct: FGDs & In- Depth Interviews Indirect: Projective techniques 3. Secondary data (Qualitative) 3. Case Study Analysis 1. Secondary data (Quantitative) 2. Surveys 3. Observations 1. Experiments
  • 11. Limitations of Experiments 1. Experiments can be time consuming 2. Experiments are often expensive 3. Experiments can be difficult to administer 4. Competitors may deliberately contaminate results of field experiments
  • 12. Source: Malhotra and Dash (6e) Data Collection Online Offline Questionnaire Preparation Softwares Online Data Collection Platforms
  • 13. Source: Malhotra and Dash (6e) Data Collection Online Offline Step 5 Step 4 Step 3 Step 2 Step 1
  • 14. Source: Malhotra and Dash (6e) 1. Descriptive 2. T-test 3. ANOVA 4. Regression Analysis
  • 16. Context Marie Dear: An aspiring MBA applicant, interested in the starting salaries of graduating students. Questions: 1. How much can students expect to make on graduation? 2. Are there any variables (e.g., gender, native language, quartile, GMAT score, etc.) that affect the starting salaries of students? 3. Did students like the MBA program offered by the college?
  • 17. Source: Malhotra and Dash (6e) 1. Descriptive 2. T-test 3. ANOVA 4. Regression Analysis