Summary is really detailed, but unfortunately it doesn't adhere to the same stucture as the course did this year.
By: isaschuit • 1 year ago
By: ToonRSM • 2 year ago
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Includes practice questions that are useful for the exam
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BM02MM CONSUMER MARKETING RESEARCH
1 INTRODUCTION & MARKETING RESEARCH PROCESS
LECTURE 31-8-2021
SECTION 1: Course Introduction
Course introduction: objectives and organization
Workshops: R practice sessions = not mandatory! You have to sign up via link in the slides.
Deeper concept in books:
- Malhotra et al., Marketing Research: An applied approach
- Other book
Not mandatory! Just for better understanding
Grading:
1. Two group assignments → groups of 5. Deadline group enrolment = 7th September
2. Exam = October 21
Assignment groups CMR → there you should add your group -> assign yourself into the groups.
Questions?
- Read available documents on canvas
- Read discussion board
- New question on discussion board
- Reach out by email
SECTION 2: The Marketing Research Process
Marketing research = the systematic and objective identification, collection, analysis, dissemination of
INFORMATION for improving decision making related to solution of problems and opportunities in marketing.
Analysing data = main focus of this class.
Marketing research = a process
1. Collect and organize data
2. Analyse it
3. Evaluate & distribute it accurately and on time
4. To marketing decision makers
DATA → INFORMATION → KNOWLEDGE → WISDOM
Focus: moving van raw data to information in this class.
The process:
1. Problem definition
2. Research approach
1
, 3. Research design
4. Data collection
5. Data analysis
6. Report & present
(1) Problem definition
From marketing decision problem (focussed on ACTION) to marketing research problem (focussed on
UNDERSTANDING):
- Decision problem: how should we position our product on supermarkets?
- Marketing research problem:
(2) Research approach
- Exploratory research = rule-based of data driven
- Explanatory research goal = guided by theory
Explanatory research models:
1. Main effect: IV influences DV
2. Moderation: IV moderates DV
3. Mediation: how/ why such an effect occurs
Always ask yourself: what is driving what? What is the relationship between variables.
Main effect:
VB. experiment portion size
- Size of consumption = DV
- Portion size = IV
Hypothesis should include the direction of the effect! “Portion size positively influence consumption amount”
Moderation effect:
Another variable will affect the strength of the direction of your relationship of the IV -> DV.
VB. if you get a huge salad you will not eat it all, if you get a huge portion of fries you eat all of it. So the
relation is moderated. The positive effect is greater for unhealthy food, than for healthy food. The differences
are bitter for French fries, not for salads.
- Size of consumption = DV
- Portion size = IV
- Food healthiness (salad) = moderation
BUT the moderator is also an independent variable! But mostly you start with the main effect and then look at
something that changes this relationship.
Mediation effect:
- The value for money
- Vb. portion size -> value for money (normative) -> consumption amount
2
,The mediation effect is in between the IV and DV. It positively effects the portion size on consumption amount.
A larger portion provides higher value for money -> increase consumption.
This is what you normally do in master thesis: mediation effect. How do we test these relationships?
(3) Research design
Determines the information that need’s to answer a specific research question or test the developed
conceptual model and hypotheses.
Take into account:
- Nature of issue (online/ offline)
- Nature of respondents (vb participants)
- Context
Types of design:
1. Exploratory design = qualitative/ quantitative exploration (less structured, vb. focus group)
2. Conclusive design = descriptive/ causal design (more structured, vb. test by experiment)
Example experiment:
- IV= in a student cafeteria participant get either small or large portion of French fries. RANDOMLY
assigned!
- DV = the consumption amount is computed with the weight of the French fries left on the tray
(4) Data collection
We won’t have time to collect data ourselves for this class.
1. Secondary data (collected for some other purpose than the problem at hand) → before you collect
your own data see what data is out there.
a. External: governmental or companies that share data online
b. Internal: consumer data
2. Primary data (collected primarily for purposes of problem at hand)
a. Quantitative methods = survey, panels, descriptive data
b. Qualitative methods = interviews, focus groups, ethnography
c. Causal research model = lab and field experiments (websites, types of fonts, A/B testing with
clicks, changing the position of the button/ colour, what does it do with your behaviour?)
We will use statistics but it is NOT a statistic class. No time to explain the statistics. We will focus the most on
quantitative methods. The qualitative methods can ben in the exam!!
(6) Report & Present
Critical step!! Practice throughout the program:
3
, - Written report
- Powerpoint presentation
This makes an impact! VB. to change decision making of a manager.
Results of each stage of the marketing research process should be reported!
Practice for your thesis. Look at the PowerPoints how you should phrase results/ hypotheses etc.
Exam does not include R!! But for the assignments you do need to use R. More focussed on the interpretation
of R results, than the formula/ computation of for example a T-test.
SECTION 3: Introduction to R
The course is mainly about marketing research, not R! We use R, but now learn you everything about it. Do not
expect to be proficient. We cover data analysis in marketing research.
Vectors -> we can enter something with a “c”. So let’s say I input your age after the c → vector you use for
character values, numerical values as variables. Zie regel 13-16 of code in R.
You can use a vector as a variable by:
city <- c(“Amsterdam”, “Rotterdam”, “Utrecht”)
Math functions is also possible in R (regel 18-22).
Nchar function → for 3 cities Amsterdam, Rotterdam, Utrecht this function summarizes the outcomes of the 3
cities. Het geeft aan hoeveel karakters de steden (letters) bevatten. Dus 9, 9 en 7.
Load packages & open data.
Head -> first 6 lines of variables
Summary = samenvatting van dataset
All of the variables are numeric (see right side of the R code). So make gender a factor variable (not numeric!)
in line 66.
WORKSHOP 1-9-2021
Uitleg over pakketten installeren / working directory setten.
2 BASIC DATA ANALYSIS
LECTURE 6-1-2021
SECTION 1: Statistical principles – Levels of measurement
Level of measurements:
1. Nominal -> yes/ no -> represent categories
2. Ordinal -> order between the categories, vb. rank beers on taste
3. Interval -> the intervals are equal (differences in ratings), vb. rate Duvel on scale 1 to 5
4. Ratio -> the zero is meaningful, vb. how much income, than zero is meaningful because it means you
don’t have a job/ salary
4
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