Customer and Marketing Analytics – Lecture notes
Table of contents
Customer and Marketing Analytics – Lecture notes ........................................................................ 1
Lecture 1: Introduction .................................................................................................................... 2
Lecture 3: Measurement and scaling: reliability, validity, dimensionality............................................. 4
Lecture 4: Factor analysis and perceptual maps ..............................................................................10
Lecture 5: Market response models (multiple regression analysis) ....................................................14
Lecture 6: Mediation and moderation analysis .................................................................................20
Lecture 7: Predicting customer response (Logistic regression analysis) .............................................26
Lecture 9: Conjoint analysis ............................................................................................................32
,Lecture 1: Introduction
Marketing research
Why do firms do research in marketing? Marketeers use the “right” principle ‘to do’ marketing.
Get the right products to the right people at the right place at the right time at the right price
using the right promotion techniques. To be “right” in marketing: need for decision making
information that reduces uncertainty to aid in smarter managerial decision making.
The marketing system
- The task of marketing
management: price, product,
promotion, placement à target
market.
- The environment aFecting
marketing: economic
environment, competitive
environment, political and legal
environment, technological
environment, natural environment, social environment. Marketing strategy ßà
Customer value and behavior.
Marketing research is planning, collection, and analysis of data relevant to marketing decision
making and the communication of the results of this analysis to management. It can be micro-
level (individual) or macro-level (market) in nature. The value of marketing research:
- Decreased uncertainty.
- Increased likelihood of a correct decision.
- Improves marketing performance and resulting higher profits.
Identifying the problem and problem definition
A good problem definition is super important. “The formulation of the problem is often more
essential than its solution”. A good start is half the work.
Fundamental distinction
Marketing decision problem on the one hand, and on the other hand marketing research
problem are the fundamental distinctions.
- Marketing decision problem: asks what the decision-maker needs to do. Action oriented.
Focuses on the symptoms.
- Marketing research problem: asks what information is needed and how it can be
obtained. Information oriented. Focuses on the underlying causes.
The iceberg principle
Obvious measurable symptoms and you also have the real
business/decisions problems. See the picture à
Sample decision problem
- What should we do to increase our store traFic?
- How can we reduce consumer complaints about
our product?
- Which product line extension should we invest in?
- Should we reposition our brand with an emphasis
on raising prices?
Thinking outside the box, this because to look at another way at the problem.
, From decision problem to research problem
Olympics committee
Decision problem: What logo design should we use for the Olympics in London?
Research problem: How much do people like the diFerent logos?
Dating website
Decision problem: How can we optimize people usage on our website?
Research problem: How much do a person’s profile photos matter compared to the information
written in the profile?
à almost a perfect correlation. It is a linear line. This says that the higher rate their looks, the
higher rate their personality. Striking correlation! According to their users, “looks” and
“personality” were the same thing..
What’s a picture worth?
Type of analytics: (online) randomized experiment.
The picture and the text together and the picture alone. DV: overall rating (1 to 5 stars).
à “Your picture is worth that fabled thousand words, but your actual words are worth almost
nothing”.
Independent variable (way we present the information, the groups, levels, conditions, subgroups
of the variable). Level of measurement: nominal/categorical variable (levels: picture and texts vs
picture alone).
Dependent variable (depends on things that are not there, outcome variable): Overall rating.
Level of measurement:
Which type of statistical analysis is needed to answer the research question? T-test or one-way
anova. Overall rating could be a t-test.
Picture only vs picture and text, everything else in the universe. Well conducted we can derive
conclusions from it.
Classifying marketing research
By type of of data:
- Quantitative data: Focus on numbers, amendable to statistical analysis. Good for:
profiling detailed usage and behavior, highlighting variations between diFerent sub-
groups, precisely measuring consumer preferences for diFerent products and services,
measuring the exact priorities consumers attach to diFerent product features.
- Qualitative data: not connected with numbers. Good for: mapping the customer’s
overall range of behavior and attitudes, pinpointing the motivations behind people’s
behavior, stimulating new and creative ideas, providing a forum for fresh creative
thinking.
By research design:
- Exploratory design: research in which the major emphasis is on gaining ideas and
insights. Purposes: increase familiarity with problem, clarify concepts, develop specific
hypothese. Approaches: literature survey, experience/key informant survey, case
studies, focus groups.
- Descriptive design: often guided by an initial hypothesis. Purposes: describe the
characteristics of certain groups, estimate the propotion of people in a specified
population who behave in a certain way, examine associations between two or more
variables, make specific predictions.
- Causal design: research in which the major emphasis is on determining a cause-and-
eFect relationship. Descriptive research reveals associations between variables. Causal
research reveals associations between change in variables. Makes use of experiments:
laboratory experiments and field experiments.