Customer and marketing analytics lecture summary
Table of Contents
Lecture 1 Introduction ..................................................................................................... 2
Lecture 2 Basic statistical analysis ................................................................................ 10
Lecture 3 measurement and scaling: reliability, validity, dimensionality .................... 28
Lecture 4 Creating Perceptual Maps using Factor Analysis .......................................... 39
Lecture 5 Market response models (multiple regression analysis) ............................... 48
Lecture 6 mediation and moderation ........................................................................... 61
Lecture 7 & 8 Predicting Customer Response using Logistic Regression ...................... 70
Lecture 9 Understanding individual customer preferences using conjoint analysis ..... 82
,Lecture 1 Introduction
Course objectives
Main Goal: To acquire the knowledge and skills on how to approach marketing-related
problems from a rigorous, analytical, data-based perspective.
• Become acquainted with marketing research problems and the data used to address
these problems
• Obtain knowledge of the data analysis techniques that are commonly used by
marketing (research) practitioners and marketing academics
• Know when and why various techniques are used
• Apply these techniques in SPSS/Microsoft Excel and interpret the results to generate
actionable insights
Popularity of analytics in marketing
Use of marketing analytics in decision making (CMO Survey 2020).
Covid-19 and the state of marketing
“More than ever, the CMO is in the right position to bring the voice of the customer on the
table. This resides in the ability of the CMO to respond to three challenges: turning customer
data into actionable insights, creating relevant customer engagement and building the
organization that delivers. Without data sources connected from inside and outside the
organization and discipline in place for data quality, customer insights simply can’t
materialize. At the same time, carefully aligning technology and data with human values and
identity is a must for attracting customers.” Ruxandra Bandila, Marketing and Business
Development Director, Deloitte
,Analytics = most desirable skill (and largest talent gap)
Only 3.4% senior marketers believe they have the right talent to leverage full potential of
analytics.
The right talent requires connecting the dots between analytics and marketing practice.
Marketing research
Why do firms do research in marketing?
Marketers 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
The environment affecting marketing
Marketing research
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, making marketing shares
calculations for instance.
The value of marketing research:
• Decreased uncertainty
• Increased likelihood of a correct decision
• Improved marketing performance and resulting higher profits
Identifying the problem and problem definition
A good problem definition is super-duper important!
“The formulation of the problem is often more essential than its solution
Fundamental distinction
,The iceberg principle
Sample decision problems
• What should we do to increase our store traffic?
• 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?
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 different proposed logos?
Online dating: what’s a picture worth?
• Decision problem: How can we optimize people’s usage of our website?
Striking correlation! According to their users, “looks” and “personality” were the same
thing…
• Research problem: How much a person’s profile photos actually matter compared to
the information written in their profile?
• Type of Analytics: (Online) Randomized Experiment
, (Online) Randomized Experiment
“Your picture is worth that fabled thousand words, but your actual words are worth…almost
nothing.”
Classifying marketing research
By type of data
• Quantitative research
• Qualitative research
By research design
• Exploratory research
• Descriptive research
• Causal research
By data source
• Secondary data
o Syndicated research
• Primary data
By type of data
Qualitative
Not concerned 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
Quantitative
Focus on numbers, amendable to statistical analysis.
Good for:
• Profiling detailed usage and behavior
• Highlighting variations between different sub‐groups
• Precisely measuring consumer preferences for different products and services
• Measuring the exact priorities consumers attach to different product features
Table of Contents
Lecture 1 Introduction ..................................................................................................... 2
Lecture 2 Basic statistical analysis ................................................................................ 10
Lecture 3 measurement and scaling: reliability, validity, dimensionality .................... 28
Lecture 4 Creating Perceptual Maps using Factor Analysis .......................................... 39
Lecture 5 Market response models (multiple regression analysis) ............................... 48
Lecture 6 mediation and moderation ........................................................................... 61
Lecture 7 & 8 Predicting Customer Response using Logistic Regression ...................... 70
Lecture 9 Understanding individual customer preferences using conjoint analysis ..... 82
,Lecture 1 Introduction
Course objectives
Main Goal: To acquire the knowledge and skills on how to approach marketing-related
problems from a rigorous, analytical, data-based perspective.
• Become acquainted with marketing research problems and the data used to address
these problems
• Obtain knowledge of the data analysis techniques that are commonly used by
marketing (research) practitioners and marketing academics
• Know when and why various techniques are used
• Apply these techniques in SPSS/Microsoft Excel and interpret the results to generate
actionable insights
Popularity of analytics in marketing
Use of marketing analytics in decision making (CMO Survey 2020).
Covid-19 and the state of marketing
“More than ever, the CMO is in the right position to bring the voice of the customer on the
table. This resides in the ability of the CMO to respond to three challenges: turning customer
data into actionable insights, creating relevant customer engagement and building the
organization that delivers. Without data sources connected from inside and outside the
organization and discipline in place for data quality, customer insights simply can’t
materialize. At the same time, carefully aligning technology and data with human values and
identity is a must for attracting customers.” Ruxandra Bandila, Marketing and Business
Development Director, Deloitte
,Analytics = most desirable skill (and largest talent gap)
Only 3.4% senior marketers believe they have the right talent to leverage full potential of
analytics.
The right talent requires connecting the dots between analytics and marketing practice.
Marketing research
Why do firms do research in marketing?
Marketers 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
The environment affecting marketing
Marketing research
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, making marketing shares
calculations for instance.
The value of marketing research:
• Decreased uncertainty
• Increased likelihood of a correct decision
• Improved marketing performance and resulting higher profits
Identifying the problem and problem definition
A good problem definition is super-duper important!
“The formulation of the problem is often more essential than its solution
Fundamental distinction
,The iceberg principle
Sample decision problems
• What should we do to increase our store traffic?
• 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?
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 different proposed logos?
Online dating: what’s a picture worth?
• Decision problem: How can we optimize people’s usage of our website?
Striking correlation! According to their users, “looks” and “personality” were the same
thing…
• Research problem: How much a person’s profile photos actually matter compared to
the information written in their profile?
• Type of Analytics: (Online) Randomized Experiment
, (Online) Randomized Experiment
“Your picture is worth that fabled thousand words, but your actual words are worth…almost
nothing.”
Classifying marketing research
By type of data
• Quantitative research
• Qualitative research
By research design
• Exploratory research
• Descriptive research
• Causal research
By data source
• Secondary data
o Syndicated research
• Primary data
By type of data
Qualitative
Not concerned 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
Quantitative
Focus on numbers, amendable to statistical analysis.
Good for:
• Profiling detailed usage and behavior
• Highlighting variations between different sub‐groups
• Precisely measuring consumer preferences for different products and services
• Measuring the exact priorities consumers attach to different product features
