Marktonderzoek
➔ Onderzoeken hoe we het best aan marketing kunnen doen.
➔ ‘Marketing without data is like driving with you eyes closed.’
Module 1: Introduction to Marketing Research
& From Marketing Research Problem/ Opportunity to Marketing Research Design
Chapter 1: Introduction to marketing research
1. Definition of marketing research (AMA)
2. Marketing research proces: 6 stages
• Stage 1: Problem definition:
➢ Business problem/ opportunity
➔ Defined based on interactions between
o Environmental context of the problem/
opportunity
o Management decision problems
o Marketing research problems
• Stage 2: Research approach developed: !!!
➢ Key is to have some theoretical foundations (i.e., academic literature): As a foundation for the
research design
➔ In oder to, to help you decide
o What (e.g., concepts) should be measured
o How it should be measured (i.e., appropriate scales)
o More: e.g., how to collect data, how to analyse data, how to report findings, etc.
• Stage 3: Research design developed:
➢ Goal: a blue-print for conducting the marketing research project
o Finall Conceptual Framework: what to measure (which variable?), how to measure (scaling)?
o How to obtain data (= sample decisions such who, how many, which type of sample)
o How to handle the data:
▪ Type of Analysis (exploratory, descriptive, causal)
▪ Analysis flow/ procedure (e.g., missing values, bias tests, handling categorical variables,
test measurement instrument, sample descriptives, correlation table, descriptive
statistics, collinearity tests, regression, moderation analyses, etc.)
, • Stage 4: Fieldwork or data collection:
➢ Goals: collecting the required data
o Both secondary (e.g., database, literature, past research, etc.) and primary data
o Primary data could be by means of both qualitative (e.g., in-depth interviews -> cijfers) and
quantitative (e.g., questionnaire -> tekst) research
• Stage 5: Data preparation and analysis:
➢ Data preparation
o Includes the editing, coding, transcription and verification of the data
➢ Analysis
o Qualitative research techniques (e.g., Topic modeling)
o Quantitative research techniques (e.g., regression)
• Stage 6: Report preparation and presentation/ knowledge dissemination:
➢ Written
o A report -> goed nadenken wie u klant is/ visueel sterk!
o Make it appealing, include tables and figures (that stand on themselves), give (action-oriented)
key-take aways, report limitations, give recommendations …
o Use appendices (for methodological details)
➢ Spoken
o A presentation
o Make it managerial appealing, include discussion and Q&A
➔ Roland Rust: “What should companies know & do differently based on the insights obtained from
your results?
Chapter 2: Defining the marketing research problem and developing a research approach
3. Process of defining a marketing research problem/opportunity
4. Importance of strong theorethical foundation
5. A research model (conceptual framework): verbal, graphical and analytical model & research questions &
research hypotheses
➔ Wisselwerking tussen deze drie topics
,➔ Example by Bart Lavière: Robotics in hotels?
1. Environmental cotext: potential problems/ opportunity
• HOTEL setting: bestaande situatie beter begrijpen
o Zijn klanten tevreden over hun hotel ervaring, en waarom (niet)? Welke aspecten zijn
belangrijk, en welke niet? Scoren we goed op de dingen die belangrijk zijn?
o Zijn klanten trouw en zijn ze bereid engagementsgedragingen (bv aanbevelingen, feedback) te
doen, en waarom (niet)? Wat zijn de drivers?
o Is de website van ons hotel optimaal, en hoe beinvloedt deze de atttitude van klanten, en hun
intenties?
o Zijn klanten tevreden over de behandeling van hun klachten? En wat zijn de gevolgen?
o …
• HOTEL setting: nieuwe situatie begrijpen
o Moeten we in robotics investeren? Hoe staan onze klanten daar tegenover? Wat zijn
belangrijke factoren die atttitude en gedrag/intenties bepalen?
o Welke design features of robot kenmerken moeten we kiezen ifv een optimale
klantenervaring?
o Nieuw interieur? Nieuwe menukaart? Herinrichting kamer: zal de klant het goed vinden?
o …
• One potential opportunity?
o HOTEL setting: Moeten we in robotics investeren? Hoe staan onze klanten daar tegenover?
Wat zijn belangrijke factoren die atttitude en gedrag/intenties bepalen?
o Evidence from practice:
− Henn na hotel (Japan): Iconic, humanoid and animal service robots substituting
employees.
− Hilton Hotel (US): Iconic service robot augmenting employees.
− Mariott Ghent: Iconic Robot Mario (currently unemployed: because of broken arm).
− Andromeda Oostende: Iconic robot at the lobby.
2. Literature (secondary data)
1) Seminal theoretical models and their key constructs
• What do academic scholars say about Technology Acceptance and Usage (Intentions)?
o Davis (1989):
− Created scales for 2 key constructs in Technology Edoption:
▪ PU: Perceived usefulness (= gaat het effectief zijn)
(e.g., Electronic mail enables me to accomplish tasks more quickly; Electronic
mail allows me to accomplish more work than would otherwise be possible)
▪ PEOU: Perceived ease of use (= gebruiksgemak)
(e.g., I find it cumbersone to use the electronic mail system)
▪ And linked it to Usage Intentions (= intenties om te gebruiken)
(e.g., I predict that I will use it on a regular basis in the future)
− Notes:
▪ Context = employees at work
▪ Technology = electronic mailsystems
, o Davis (1993): TAM: Technology Acceptance Model
− Dependent = Actual usege (self-deported)
▪ On average, I use electronic mail: (pich most accurate answer below)
➢ Don’t use it at all.
➢ Less than once a week.
➢ About once a week.
➢ Several times each week.
➢ About once each day.
➢ Several times each day.
▪ How many hours do you usually spend each week using the system: …
− Introduce Attitude as mediator
− Consider different technologies
− Notes:
▪ Context = employees at work
▪ Technology = electronic mail system (0) vs. text editor (1)
− Remark: Models can be used for testing new technologies that (i) you recently
adopted, or (ii) you haven’t adopted yet.
➔ Groen = nieuw
➔ * = er is een relatie/ + = positieve relatie/ - = omgekeerde relatie/ volle lijn =
veronderstelling/ stippelijn = extra relaties afgeleid uit data.
➔ Onderzoeken hoe we het best aan marketing kunnen doen.
➔ ‘Marketing without data is like driving with you eyes closed.’
Module 1: Introduction to Marketing Research
& From Marketing Research Problem/ Opportunity to Marketing Research Design
Chapter 1: Introduction to marketing research
1. Definition of marketing research (AMA)
2. Marketing research proces: 6 stages
• Stage 1: Problem definition:
➢ Business problem/ opportunity
➔ Defined based on interactions between
o Environmental context of the problem/
opportunity
o Management decision problems
o Marketing research problems
• Stage 2: Research approach developed: !!!
➢ Key is to have some theoretical foundations (i.e., academic literature): As a foundation for the
research design
➔ In oder to, to help you decide
o What (e.g., concepts) should be measured
o How it should be measured (i.e., appropriate scales)
o More: e.g., how to collect data, how to analyse data, how to report findings, etc.
• Stage 3: Research design developed:
➢ Goal: a blue-print for conducting the marketing research project
o Finall Conceptual Framework: what to measure (which variable?), how to measure (scaling)?
o How to obtain data (= sample decisions such who, how many, which type of sample)
o How to handle the data:
▪ Type of Analysis (exploratory, descriptive, causal)
▪ Analysis flow/ procedure (e.g., missing values, bias tests, handling categorical variables,
test measurement instrument, sample descriptives, correlation table, descriptive
statistics, collinearity tests, regression, moderation analyses, etc.)
, • Stage 4: Fieldwork or data collection:
➢ Goals: collecting the required data
o Both secondary (e.g., database, literature, past research, etc.) and primary data
o Primary data could be by means of both qualitative (e.g., in-depth interviews -> cijfers) and
quantitative (e.g., questionnaire -> tekst) research
• Stage 5: Data preparation and analysis:
➢ Data preparation
o Includes the editing, coding, transcription and verification of the data
➢ Analysis
o Qualitative research techniques (e.g., Topic modeling)
o Quantitative research techniques (e.g., regression)
• Stage 6: Report preparation and presentation/ knowledge dissemination:
➢ Written
o A report -> goed nadenken wie u klant is/ visueel sterk!
o Make it appealing, include tables and figures (that stand on themselves), give (action-oriented)
key-take aways, report limitations, give recommendations …
o Use appendices (for methodological details)
➢ Spoken
o A presentation
o Make it managerial appealing, include discussion and Q&A
➔ Roland Rust: “What should companies know & do differently based on the insights obtained from
your results?
Chapter 2: Defining the marketing research problem and developing a research approach
3. Process of defining a marketing research problem/opportunity
4. Importance of strong theorethical foundation
5. A research model (conceptual framework): verbal, graphical and analytical model & research questions &
research hypotheses
➔ Wisselwerking tussen deze drie topics
,➔ Example by Bart Lavière: Robotics in hotels?
1. Environmental cotext: potential problems/ opportunity
• HOTEL setting: bestaande situatie beter begrijpen
o Zijn klanten tevreden over hun hotel ervaring, en waarom (niet)? Welke aspecten zijn
belangrijk, en welke niet? Scoren we goed op de dingen die belangrijk zijn?
o Zijn klanten trouw en zijn ze bereid engagementsgedragingen (bv aanbevelingen, feedback) te
doen, en waarom (niet)? Wat zijn de drivers?
o Is de website van ons hotel optimaal, en hoe beinvloedt deze de atttitude van klanten, en hun
intenties?
o Zijn klanten tevreden over de behandeling van hun klachten? En wat zijn de gevolgen?
o …
• HOTEL setting: nieuwe situatie begrijpen
o Moeten we in robotics investeren? Hoe staan onze klanten daar tegenover? Wat zijn
belangrijke factoren die atttitude en gedrag/intenties bepalen?
o Welke design features of robot kenmerken moeten we kiezen ifv een optimale
klantenervaring?
o Nieuw interieur? Nieuwe menukaart? Herinrichting kamer: zal de klant het goed vinden?
o …
• One potential opportunity?
o HOTEL setting: Moeten we in robotics investeren? Hoe staan onze klanten daar tegenover?
Wat zijn belangrijke factoren die atttitude en gedrag/intenties bepalen?
o Evidence from practice:
− Henn na hotel (Japan): Iconic, humanoid and animal service robots substituting
employees.
− Hilton Hotel (US): Iconic service robot augmenting employees.
− Mariott Ghent: Iconic Robot Mario (currently unemployed: because of broken arm).
− Andromeda Oostende: Iconic robot at the lobby.
2. Literature (secondary data)
1) Seminal theoretical models and their key constructs
• What do academic scholars say about Technology Acceptance and Usage (Intentions)?
o Davis (1989):
− Created scales for 2 key constructs in Technology Edoption:
▪ PU: Perceived usefulness (= gaat het effectief zijn)
(e.g., Electronic mail enables me to accomplish tasks more quickly; Electronic
mail allows me to accomplish more work than would otherwise be possible)
▪ PEOU: Perceived ease of use (= gebruiksgemak)
(e.g., I find it cumbersone to use the electronic mail system)
▪ And linked it to Usage Intentions (= intenties om te gebruiken)
(e.g., I predict that I will use it on a regular basis in the future)
− Notes:
▪ Context = employees at work
▪ Technology = electronic mailsystems
, o Davis (1993): TAM: Technology Acceptance Model
− Dependent = Actual usege (self-deported)
▪ On average, I use electronic mail: (pich most accurate answer below)
➢ Don’t use it at all.
➢ Less than once a week.
➢ About once a week.
➢ Several times each week.
➢ About once each day.
➢ Several times each day.
▪ How many hours do you usually spend each week using the system: …
− Introduce Attitude as mediator
− Consider different technologies
− Notes:
▪ Context = employees at work
▪ Technology = electronic mail system (0) vs. text editor (1)
− Remark: Models can be used for testing new technologies that (i) you recently
adopted, or (ii) you haven’t adopted yet.
➔ Groen = nieuw
➔ * = er is een relatie/ + = positieve relatie/ - = omgekeerde relatie/ volle lijn =
veronderstelling/ stippelijn = extra relaties afgeleid uit data.
