Marketing Research

 

Course code: MKT 375

Term and year: Fall 2024

Day and time: Tuesdays, 08:15-11:00

Instructor: PhDr. Ladislava Knihová, Ph.D., MBA

Instructor contact: ladislava.knihova@aauni.edu

Consultation hours: Tuesdays, 11:00-12:00

 

Credits US/ECTS	3/6	Level	Bachelor
Length	15 weeks	Pre-requisite	MKT 248, MTH 222
Contact hours	42 hours	Grading	Letter grade

1.   Course Description

 

This course, Marketing Research, is designed to equip students with the essential skills and knowledge needed to conduct effective marketing research in a dynamic business environment. Students will learn how to identify and define marketing problems, develop research objectives, and design appropriate research methodologies. The course emphasizes both qualitative and quantitative research techniques, providing a comprehensive understanding of how to collect, analyze, and interpret data to support informed decision-making in marketing.

 

Throughout the course, students will engage with real-world scenarios and case studies that illustrate the practical application of marketing research concepts. Interactive lectures, seminars, and hands-on activities will encourage students to actively participate in the learning process, fostering critical thinking and problem-solving skills. The course also integrates AI-driven tools and technologies, offering insights into how modern marketing research is evolving with advancements in artificial intelligence.

 

A key component of the course is the development of research proposals and the execution of research projects, both individually and in teams. These projects will allow students to apply theoretical knowledge to practical research problems, enhancing their ability to conduct thorough and effective research. By the end of the course, students will be able to design and implement marketing research studies, analyze data, and present findings in a clear and compelling manner.

 

This course is ideal for students who aspire to careers in marketing, business analytics, or any field where data-driven decision-making is crucial. It prepares students to navigate the complexities of the market, understand consumer behavior, and contribute to strategic marketing decisions through rigorous research, all while leveraging the ever-present influence of AI in modern marketing practices.

 

 

 

 

 

2.   Student Learning Outcomes

 

Upon completion of this course, students will be able to:

 

●        Comprehend and have a clear understanding of the relationship between market research and decision-making.

●        Comprehend and have a clear understanding of the processes used in formulating and conducting market research projects.

●        Place in context and lend perspective to the market conditions under which research may be undertaken and the impact of these conditions on the type of research to be conducted, including methodologies and project management.

●        Comprehend and clearly understand the range of qualitative and quantitative techniques and methods available in marketing research, including applicability and limitations.

●        Comprehend and clearly understand how to design market research to obtain actionable information as a decision support and make a Request for Proposal for a market research project.

●        Place in context and lend perspective to the language of marketing research as practitioners and business people use it.

●        Place in context and lend perspective to more common qualitative and quantitative techniques, including proposal/survey construction, data collection/fieldwork, analysis, and reporting.

 

3.   Reading Material

Required Materials

Required Materials (Selected Chapters or full text available for Download)

Main Textbooks

 

●        McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights (Twelfth edition). Wiley. (Selected Chapters available for download – link will be provided in NEO).

●        Male, S. (2024). AI Empowered: Revolutionizing Market Research. (Full text available for download – link will be provided in NEO).

 

Recommended Further Reading and Scientific Journals’ Articles

 

●        Kumar, V., Ashraf, A. R., & Nadeem, W. (2024). AI-powered marketing: What, where, and how? International Journal of Information Management, 77, 102783. https://doi.org/10.1016/j.ijinfomgt.2024.102783 (TM - Teacher’s material)

●        Kotler, P., Kartajaya, H., & Setiawan, I. (2024). Marketing 6.0: The future is immersive. Wiley.

●        Kumar, V., & Kotler, P. (2024). Transformative Marketing: Combining New Age Technologies and Human Insights. Palgrave Macmillan.

 

4.   Teaching methodology

In the course, the course teacher employs a combination of interactive lectures, seminars, and moderated discussions to create a highly engaging and dynamic learning environment. The interactive lectures are not just about presenting key concepts; they are designed to provoke thought and encourage active participation from students through questioning and dialogue. This approach helps students critically engage with the material and directly apply theoretical knowledge to real-world scenarios. Seminars are utilized to facilitate in-depth exploration of topics through collaborative activities, such as case studies and group discussions, allowing students to practice applying concepts in practical settings, which strengthens their understanding.

 

Furthermore, the course teacher incorporates student-led discussions, where students take the lead in guiding conversations while the teacher acts as a facilitator. This method encourages autonomy, critical thinking, and the development of leadership and communication skills among students. The inclusion of case studies supports these discussions by providing practical examples that students can analyze and debate, thereby enhancing their problem-solving and analytical abilities. These teaching methods have been chosen because they actively involve students in the learning process, foster critical thinking, and bridge the gap between theory and practice, effectively preparing students for the challenges they will face in the field of marketing research.

 

Multimodal Learning and Technology Integration - To accommodate different learning styles and enhance student engagement, the course design will employ multimodal learning. This approach incorporates various forms of media, such as videos, podcasts, and interactive online tools, to create a rich and diverse learning experience. Students will also engage creatively with AI-driven applications recommended by the course teacher, allowing them to create and distribute content that blends traditional learning with cutting-edge technology.

 

By employing these diverse methodologies, the course aims to create an engaging and immersive learning environment that prepares students to not only analyze but also demonstrate their own ability to influence data-driven decision-making. This is particularly relevant in the contexts of AI and marketing research. The course is designed to develop critical skills such as data analysis, interpretation of consumer insights, research design, and the application of AI tools in market research. These skills are essential for students to navigate real-world scenarios, where they will need to make informed decisions based on data and leverage emerging new-age technologies (NATs) to drive marketing strategies.

 

5.   Course Schedule

Date	Class Agenda
Week 1:   September 3rd	Topic: Introduction to Marketing Research and Its Role in Decision Making   Topics: Overview of the marketing research process, its importance, and its application in real-world scenarios. Activities: Understanding the fundamental concepts of marketing research and its support in effective decision-making in marketing-oriented organizations. Discussing the significance of research in addressing marketing challenges and opportunities. Research Task: Conduct a brief literature review on the role of marketing research in strategic decision-making within a specific industry of your choice. Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 1 - Steps in Creating Market Insights and the Growing Role of Marketing Analytics (pp. 1-21). AI Empowerment Focus: AI-Powered Problem Identification and Objective Setting: Discuss how AI can assist in identifying research problems by analyzing large datasets and help set precise research objectives. Reading 2: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Logit Group. Chapter 1 - Introduction to AI in Market Research (pp. 1-14) https://logitgroup.com/ai-empowered/
Week 2 September 10th	Topic:  Defining Research Problems and Setting Research Objectives   Topics: Learning how to accurately identify and articulate marketing problems. Exploring techniques for setting clear and achievable research objectives that guide the research process effectively. Activities: Group discussions on identifying research problems in various marketing scenarios. Workshops on drafting research objectives that are specific, measurable, achievable, relevant, and time-bound (SMART). Research Task: Develop a research problem statement and corresponding objectives for a hypothetical marketing research project in a chosen industry. Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 2 - Secondary Data: A Potential Big Data Input (pp. 23-34). AI Empowerment Focus: AI-Powered Problem Identification and Objective Setting: Discuss how AI can assist in identifying research problems by analyzing large datasets and help set precise research objectives. Reading 2: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Logit Group. Chapter 2 - General Best Practices for Using AI in Market Research (pp. 15-30) https://logitgroup.com/ai-empowered/ CW1: Pair-Work Task Title: Glossary of AI and Marketing Research Terms Submission: The completed PPT file (only in PowerPoint) must be uploaded to NEO by Monday of this week, no later than 11:59 am.
Week 3   September 17th	Topic:  Developing Research Briefs and Evaluating Research Proposals   Topics: Understanding the components of a comprehensive research brief and how to communicate research needs to stakeholders. Examining criteria and best practices for assessing and selecting appropriate research proposals. Activities: Practical exercises in drafting research briefs and mock evaluations of research proposals. Group discussions on the challenges and strategies in aligning research briefs with organizational goals. Research Task: Create a detailed research brief for a specific marketing issue, and evaluate a set of research proposals to determine the most suitable one for addressing the problem. Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 4 – Part I - Acquiring Data via a Questionnaire (pp. 73-76). AI Empowerment Focus: Leveraging AI to Evaluate Research Proposals: Learn how AI tools can automate and improve the evaluation of research proposals by assessing potential outcomes and matching objectives.   Reading 2: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Logit Group. Chapter 3 - Benefits and Shortfalls of AI in Market Research (pp. 31-42) https://logitgroup.com/ai-empowered/   CW1: Pair-Work Task Title: Glossary of AI and Marketing Research Terms Submission: The completed PPT file (only in PowerPoint) must be uploaded to NEO by Monday of this week, no later than 11:59 am.
Week 4   September 24th	Topic:  Research Design and Methodology Selection   Topics: Exploring various research designs (exploratory, descriptive, causal) and methodologies. Learning how to choose the most suitable approach based on research objectives and market conditions. Activities: Comparative analysis of different research designs through case studies. Workshops on matching research methodologies with specific objectives and market scenarios. Research Task: Develop a research plan outlining the design and methodology for a proposed marketing research project, justifying your choices based on the research objectives. Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 5 - Sample Design (pp. 99-125). AI Empowerment Focus: AI in Research Design and Methodology: Understand how AI can optimize the selection of research methodologies by predicting which approaches will yield the best results. Reading 2: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Logit Group. Chapter 4 - Vetting AI Practices in Market Research (pp. 43-56) https://logitgroup.com/ai-empowered/     CW1: Pair-Work Task Title: Glossary of AI and Marketing Research Terms Submission: The completed PPT file (only in PowerPoint) must be uploaded to NEO by Monday of this week, no later than 11:59 am.
Week 5   October  1st	Topic:  Qualitative Research Techniques: Methods and Applications Topics: Delving into qualitative research methods such as focus groups, in-depth interviews, and ethnography. Discussing their applicability, execution, and how they provide insights into consumer behavior and attitudes. Activities: Simulation exercises on conducting focus groups and interviews. Analysis of case studies where qualitative research has been pivotal in understanding consumer behavior. Group discussions on the strengths and limitations of various qualitative methods. Research Task: Design a qualitative research study, selecting appropriate methods to investigate a specific consumer behavior issue. Prepare a plan for executing this study, including participant selection, data collection techniques, and analysis strategies.   Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 7 - Qualitative Research (pp. 146-167). AI Empowerment Focus: AI-Enhanced Qualitative Research: Explore AI-driven techniques like natural language processing to analyze qualitative data more efficiently and deeply.   Reading 2: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Logit Group. Chapter 5 - AI for Enhancing Data Quality (pp. 59-74) https://logitgroup.com/ai-empowered/   Quiz No. 1: Foundations of Marketing Research and AI Concepts Test knowledge of key marketing research terminology and foundational AI concepts covered in weeks 1-4.   CW1: Pair-Work Task Title: Glossary of AI and Marketing Research Terms Submission: The completed PPT file (only in PowerPoint) must be uploaded to NEO by Monday of this week, no later than 11:59 am.
Week 6   October 8th	Topic: Quantitative Research Techniques: Methods and Applications   Topics: Examining quantitative research methods including surveys, experiments, and observation studies. Understanding how to collect and analyze numerical data to support marketing decisions. Activities: Hands-on workshops in designing surveys and experiments, along with exercises in data collection and interpretation. Group analysis of case studies to evaluate the impact of quantitative research on marketing strategies. Research Task: Develop a quantitative research plan, including the design of a survey or experiment, data collection strategy, and a framework for analyzing the results to address a specific marketing question. Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 6 - Traditional Survey Research (pp. 129-144). AI Empowerment Focus: AI-Powered Quantitative Data Analysis: Delve into the use of AI for handling large quantitative datasets, automating analysis, and improving accuracy.   Reading 2: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Logit Group. Chapter 6 - AI for Analysis and Summarizing (pp. 75-90) https://logitgroup.com/ai-empowered/ CW1: Pair-Work Task Title: Glossary of AI and Marketing Research Terms Submission: The completed PPT file (only in PowerPoint) must be uploaded to NEO by Monday of this week, no later than 11:59 am.
Week 7   October 15th	Topic: Online Marketing Research: The Growth of Mobile and Social Media Research / Revision: Sampling Methods and Data Collection Strategies Topics: Online Marketing Research/Mobile Reserch/Soial Media Research. Learning about different sampling techniques (probability and non-probability sampling) and determining appropriate sample sizes. Discussing effective data collection methods and managing fieldwork processes. Activities: Practical exercises in selecting appropriate sampling techniques for various research scenarios. Workshops on calculating sample sizes and planning data collection strategies. Simulations of fieldwork management and data collection challenges. Research Task: Design a sampling plan for a research project, including justification for the chosen sampling method and calculation of the sample size. Develop a data collection strategy that ensures reliable and valid data. Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 8 - Online Marketing Research: The Growth of Mobile and Social Media Research (pp. 171-183). AI Empowerment Focus: AI for Optimized Sampling and Data Collection: Discuss how AI can enhance sampling strategies by identifying optimal sampling methods and automating data collection processes.   Reading 2: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Logit Group. Chapter 8 - The Future of Market Research: Synthetic Research and Beyond (pp. 105-118) https://logitgroup.com/ai-empowered/ DEADLINE CW2: Micro-Team Task Title: Qualitative Research Execution and Analysis ●        To be uploaded to NEO by Monday of this week latest by 11:59 am. ●        Presentation (in class): 10-15 minute presentation summarizing the research findings and insights.
Week 8   October 22nd	CW2: Micro-Team Task Title: Qualitative Research Execution and Analysis       Presentations: In-class presentations will be conducted during the week following the assignment's submission, i.e. Week 8.
October 29th	Mid-term break
Week 9   November 5th	Topic: Measurement and Scaling in Marketing Research     Topics: Understanding concepts of measurement validity and reliability. Exploring various scaling techniques (Likert, semantic differential, rank-order) and their use in capturing consumer perceptions and preferences. Activities: Workshops on designing measurement instruments and applying different scaling techniques. Case studies that illustrate the application of scaling in real-world marketing research. Group discussions on the challenges of ensuring validity and reliability in measurement. Research Task: Develop a measurement instrument for a marketing research study, incorporating appropriate scaling techniques. Evaluate the instrument for validity and reliability, and propose ways to improve it. Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 3 - Measurement to Build Marketing Insight (pp. 36-68). AI Empowerment Focus: AI-Driven Measurement and Scaling: Learn about AI tools that ensure more accurate and reliable measurement and scaling in research, reducing human error.   Reading 2: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Logit Group. Chapter 9 - Case Studies and Applications (pp. 119-128) https://logitgroup.com/ai-empowered/ CW1: Pair-Work Task Title: Glossary of AI and Marketing Research Terms Submission: The completed PPT file (only in PowerPoint) must be uploaded to NEO by Monday of this week, no later than 11:59 am.
Week 10   November 12th	Topic: Questionnaire Design and Survey Construction   Topics: Learning principles of effective questionnaire design, including question wording, sequencing, and formatting. Discussing strategies to enhance response rates and data quality in survey research. Activities: Workshops on drafting and refining questionnaires, with peer reviews to improve question clarity and effectiveness. Simulations of survey distribution and response collection, focusing on strategies to maximize participation and data integrity. Research Task: Design a comprehensive questionnaire for a marketing research study, ensuring alignment with research objectives and consideration of factors that influence response rates. Test the questionnaire on a small sample and analyze the results for potential improvements. Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 4 – Part II - Acquiring Data via a Questionnaire (pp. 76-95). AI Empowerment Focus: AI in Survey Design and Optimization: Explore how AI can assist in designing more effective questionnaires and surveys by predicting respondent behavior and optimizing question flow.   Reading 2: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Log it Group. Chapter 6 - AI in Survey Design and Optimization (pp. 75-90).  https://logitgroup.com/ai-empowered/ CW1: Pair-Work Task Title: Glossary of AI and Marketing Research Terms Submission: The completed PPT file (only in PowerPoint) must be uploaded to NEO by Monday of this week, no later than 11:59 am.   CW1: Pair-Work Task Title: Glossary of AI and Marketing Research Terms Submission: The completed PPT file (only in PowerPoint) must be uploaded to NEO by Monday of this week, no later than 11:59 am.
Week 11   November 19th	Topic: Data Analysis Techniques for Qualitative Research   Topics: Exploring methods for analyzing qualitative data, such as thematic analysis and content analysis. Learning how to interpret and derive meaningful insights from non-numerical data. Activities: Workshops on conducting thematic and content analysis using sample qualitative data. Group discussions on the interpretation of qualitative data and the challenges of ensuring objectivity and depth in analysis. Research Task: Analyze a set of qualitative data (e.g., interview transcripts or open-ended survey responses) using thematic or content analysis techniques, and present the key findings and insights derived from the analysis. Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 10 – Marketing Analysis AI Empowerment Focus: AI Tools for Assisting in Qualitative Research: Introductuion to user-friendly AI tools that help organize, code, and analyze qualitative data, such as transcribing interviews (transcription software) or identifying common themes in responses.   Readings: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Logit Group. Chapter 7 - AI Tools for Qualitative Research (pp. 91-104). https://logitgroup.com/ai-empowered/   Quiz No. 2: Foundations of Marketing Research and AI Concepts Test knowledge of key marketing research terminology and foundational AI concepts covered throughout the entire course.   CW1: Pair-Work Task Title: Glossary of AI and Marketing Research Terms Submission: The completed PPT file (only in PowerPoint) must be uploaded to NEO by Monday of this week, no later than 11:59 am.
Week 12   November 26th	Topic: Data Analysis Techniques for Quantitative Research / Presenting Research Findings and Reporting   Activities: Workshops on performing basic quantitative data analysis, including data cleaning, summary statistics, and creating visualizations. This session will also focus on the correct use of terminology in describing statistical methods and results. Group exercises on preparing research reports and presenting findings effectively using graphs, charts, and tables, with an emphasis on accurate and precise language. Research Task: Analyze a quantitative dataset to generate key insights, create visualizations to support your findings, and prepare a concise report that effectively communicates the results using appropriate terminology. Reading 1: McDaniel, C. D., & Gates, R. H. (2021). Marketing research: Using analytics to develop market insights. Wiley. Chapter 12 - Data Processing and Basic Data Analysis (pp. 255-281).   AI Empowerment Focus: AI in Quantitative Data Analysis: Introduction to user-friendly AI-powered applications that assist in basic quantitative data analysis tasks, such as automating data cleaning, generating basic reports, and visualizing data trends.   Reading 2: Male, S. (2024). AI Empowered: Revolutionizing Market Research. The Logit Group. Chapter 8 - AI in Quantitative Data Analysis (pp. 105-118). https://logitgroup.com/ai-empowered/
Week 13   December 3rd	Topic: Overall semester wrap-up.   Last class discussion and summary of what we have learnt together. Group feedback for the final project.       CW3: FINAL PROJECT - Micro-Team Task – Part I Title: Quantitative Research Design and Reporting ●        Presentation (in class): Each micro-team will deliver a 10-15 minute presentation summarizing the research findings and insights.   ●        Note: This session is designated for the first group of micro-teams. The remaining micro-teams will present in Part II in Week 14. Students are required to divide themselves into two groups and inform the teacher of their group's assigned presentation week.
Week 14   December 10th	CW3: FINAL PROJECT – Micro-Team Task – Part II Title: Quantitative Research Design and Reporting ●        Presentation (in class): Each micro-team will deliver a 10–15-minute presentation summarizing the research findings and insights.   ●        Note: This session is designated for the second group of micro-teams. ●        Final Seminar Closing: After the presentations, we will have a final reflection and discussion to summarize the key takeaways from the course, celebrate the work completed, and address any remaining questions as we conclude our journey together in marketing research.

6.   Course Requirements and Assessment (with estimated workloads)

Assignment	Workload (hours)	Weight in Final Grade	Evaluated Course-Specific Learning Outcomes	Evaluated Institutional Learning Outcomes*
Class Participation	42	10%	Active participation in discussions and the ability to express thoughts and opinions. Preparation is critical, and devices like phones and PCs are restricted.	3
CW1: Glossary of AI and Market Research Terms (Pair Work)	20	25%	Create a glossary of key AI and market research terms. Enhance understanding of terminology and improve presentation skills through in-class presentations.	1, 2
Quiz No. 1	18	5%	Assess understanding of marketing research terminology and AI concepts covered in weeks 1-4.	1
CW2: Qualitative Research Study (Micro-Team Task)	25	25%	Conduct a qualitative research study, including data collection, analysis, and reporting. Focus on teamwork, research methodology, and practical application.	1, 2
Quiz No. 2	20	10%	Assess understanding of marketing research terminology and AI concepts covered throughout the entire course.	1
CW3: Quantitative Research Design and Reporting (Micro-Team Task)	25	25%	Design and execute a quantitative research study, analyze data, and present findings. Develop teamwork, data analysis skills, and effective communication.	1, 2
TOTAL	150	100%

 

*1 = Critical Thinking; 2 = Effective Communication; 3 = Effective and Responsible Action

 

Participation (CP: 10%): Participation is evaluated on the quality of your contribution to the learning experience of the class. Participating by actively responding to questions, asking questions, and engaging in class discussions will help you earn your participation grade. Simply attending every class is not participation. If you need more clarification, please ask your course leader what you can do to increase your participation.

 

●        Your participation grade will be evaluated (at the end of the course) as follows:

o   Outstanding (90-100%): Contributions provided important insights for the class. Arguments were well-supported (with evidence) and persuasively presented. If this student had not been a member, the class quality would have been significantly lower.

o   Good (80-89%): Contributions were on-target, reasonably well-supported and persuasive. If this student had not been a member, the class quality would have been slightly lower.

o   Attending Non-participant (70-79%): Contributed nothing to the class. The student attended every class but was silent and did not participate.

o   Repetitive (-10%): If a student's class comments were repetitious and obvious and did not add value to the class. That is, you will be penalised for 'airtime' without value.

o   Unsatisfactory (-20%): Unsatisfactory contribution occurs due to inadequate preparation. If this student had not been a class member, the quality of the discussions would have been enhanced.

 

Remember, the value and excitement of our seminar will be driven by the energy
and insights you bring—your contributions will make all the difference.

 

7.   Detailed description of the assignments

 

Assignment 1: Glossary of AI and Marketing Research Terms

 

Teacher's Instructions for CW1: Glossary of AI and Marketing Research Terms

  

 

Objective:

The purpose of this recurring assignment is to help students continuously develop a comprehensive understanding of key terms related to Marketing Research and Artificial Intelligence (AI). By regularly researching, defining, and presenting these terms, students will deepen their grasp of the concepts and their applications in the field of Marketing Research.

 

Assignment Description:

●        Pair Work: Students will work in pairs to create a glossary consisting of 5-10 key terms related to AI and Marketing research. Each week, terms should be selected from the course materials covered in the preceding weeks.

●        Term Selection: For each assignment, students should select min. 5 terms specifically related to marketing research techniques. Terms should reflect the most important concepts introduced during the course and from the designated readings, incl. the incorporation of AI.

●        Glossary Format: Each term should be clearly defined, followed by a brief explanation (approximately 50-100 words) of its significance in the context of marketing research. Where relevant, provide examples or case studies to illustrate the term's application.

●        Presentation: In addition to the written glossary, each pair will prepare a brief (5-7 minute) in-class presentation using PowerPoint slides. During the presentation, students should explain their selected terms, demonstrate their understanding, and be prepared to answer questions from peers and the instructor.

Submission Guidelines:

●        Format: The assignment requires only a PowerPoint presentation. The glossary and explanations should be integrated into the slides.

●        Length: The presentation should include 10 slides, with each slide dedicated to one of the selected terms. Each term should have an explanation and context presented concisely on the slide.

●        File Upload: The PowerPoint presentation must be uploaded to the designated link on NEO by the Monday of the week in which the assignment is due, no later than 11:59 am.

●        In-Class Presentation: Presentations will take place during the week the assignment is due. Each pair should be prepared to present their glossary to the class and engage in a brief Q&A session.

 

Deadline:

●        Submission: The glossary document and PowerPoint slides must be submitted by Monday of the week the assignment is due, no later than 11:59 am.

●        Presentation: In-class presentations will be conducted during the week the assignment is due.

 

 

Assignment 1 Assessment Criteria Breakdown

 

 

	Assessment criteria	%
1	Content: Accuracy and completeness of definitions, relevance of selected terms, and depth of understanding demonstrated in explanations.	40%
2	Presentation: Clarity, organization, and effectiveness of the in-class presentation. Ability to engage with the audience and answer questions.	30%
3	Research and Examples: Use of appropriate examples or case studies to illustrate the terms.	20%
4	Professionalism and Timeliness: Adherence to formatting guidelines, timely submission of materials, and overall professionalism in both the written and presented work.	10%
	Total	100%

 

 

Instructions for Assignment 2 & Assignment 3: Research Proposal Development

 

Teacher's Instructions for CW2 and CW3: Research Proposal Development

Objective:
Students divided into micro-teams will develop a comprehensive research proposal that identifies a specific marketing problem. This proposal should clearly outline the research objectives, the methodology you plan to use, and the sampling strategy that will be employed to gather data.

Task Requirements:

1. Identify a Marketing Problem:
• Choose a marketing problem that is relevant to your field of interest or current industry trends.
• Clearly define the problem, providing context and explaining why it is significant.
2. Outline Research Objectives:
• Develop clear and concise research objectives that address the identified marketing problem.
• Ensure that your objectives are specific, measurable, achievable, relevant, and time-bound (SMART).
3. Select Research Methodology:
• Describe the research methodology you will use to achieve your objectives.
• Explain whether you will use qualitative, quantitative, or mixed methods and justify your choice.
• Include details on data collection methods (e.g., surveys, interviews, focus groups) and how they will help in addressing the research objectives.
4. Develop a Sampling Strategy:
• Outline the sampling strategy you will use for your research.
• Specify your target population and explain how you will select your sample.
• Discuss the sample size and justify your choices based on the research objectives and methodology.

Additional Notes:

●        Support Materials: You may refer to the course textbook, lecture notes, and any additional resources provided on NEO to guide your proposal development.

●        Questions: If you have any questions or need clarification, please reach out to the course teacher via email or during office hours before the submission deadline.

 

 

 

Assignment 2: Qualitative Research Execution and Analysis

 

 

Teacher's Instructions for CW2: Quantitative Research Execution and Analysis

The goal of this assignment for micro-teams is to collaboratively design and execute
a qualitative research study. The focus will be on data collection and thematic analysis, enabling students to explore the depth and complexity of qualitative data and present their findings in a coherent and insightful manner.

Task Requirements:

1. Selecting the Research Proposal:
• Choose a Proposal: Within your micro-team, select one research proposal developed according to the teacher's instructions „Research Proposal Development“. This will form the basis of your qualitative research study.
• Refine the Research Problem: Ensure that the selected research problem is suitable for a qualitative approach. Refine the problem statement as needed to align with qualitative research methods.
2. Designing the Qualitative Study:
• Develop Research Questions: Based on the refined problem, develop clear and open-ended research questions that guide your qualitative inquiry.
• Plan Data Collection: Determine the qualitative data collection methods you will use, such as semi-structured interviews, focus groups, or observations. Justify your choice of methods and explain how they will help you explore the research problem.
• Sampling Strategy: Define your approach to selecting participants for the study. Describe your target population, sampling method, and the rationale behind your sample size.
3. Conducting Data Collection and Analysis:
• Collect the Data: Implement your data collection plan, ensuring that you gather rich, detailed qualitative data that addresses your research questions.
• Thematic Analysis: Analyze the collected data using thematic analysis. Identify key themes, patterns, and insights that emerge from the data. Be thorough in your analysis, ensuring that it captures the complexity and nuances of the qualitative data. Start early! Collecting data takes time!
4. Presentation of Findings:
• Prepare a PowerPoint Presentation: Summarize your research process, data analysis, and key findings in a clear and organized PowerPoint presentation. Your presentation should effectively communicate the depth of your qualitative insights.
• Deliver the Presentation in Class: Each micro-team will present their findings in a 10-15 minute in-class presentation. The presentation will be followed by a discussion where you will need to answer questions and demonstrate a deep understanding of your research.

Submission Guidelines

●        Format: The assignment requires a PowerPoint presentation (digital only).

●        Length: The presentation should include a title slide, followed by slides that cover the research problem, research questions, methodology, sampling strategy, data analysis, and key findings and their interpretation.

●        Deadline: The PowerPoint slides must be submitted by Monday of the week the assignment is due to NEO, no later than 11:59 am.

●        File Naming Convention: Ensure that your file is named according to the following format: LastName_FirstName_CW3_QualitativeResearchProposal

●        Presentation: In-class presentations will be conducted during the week the assignment is due, i.e.

●         

Assignment 2 Assessment Criteria Breakdown

 

	Assessment criteria	%
1	Clarity and Relevance: Is the marketing problem clearly identified and relevant? Are the research objectives well-defined and aligned with the problem?	30%
2	Methodological Rigor: Are the data collection methods appropriate and well-justified? Is the thematic aDnalysis thorough and insightful?	30%
3	Sampling Strategy: Is the sampling strategy well-planned and suitable for the research? Does it consider the target population effectively and ensure a diverse and relevant sample?	20%
4	Presentation Quality: Is the PowerPoint presentation clear, organized, and visually engaging? Does it effectively communicate the key elements of the proposal?	20%
	Total	100%

By completing this assignment, students will demonstrate their ability to conduct and present a rigorous qualitative research study, applying qualitative methods to real-world marketing problems.

Assignment 3: Quantitative Research Design and Reporting

Teacher's Instructions for CW3: Quantitative Research Design and Reporting

 

The goal of this assignment for micro-teams is to collaboratively design and execute
a quantitative research study. In this assignment, teams will move from planning to execution, conducting a full quantitative study, analyzing the data, interpreting and presenting the findings.

 

Task Requirements:

 

1. Refining the Research Proposal:

 

• Choose a Proposal: Within your micro-team, select one research proposal developed according to the teacher's instructions „Research Proposal Development “. This will form the basis of your quantitative research study. Ensure the research problem, objectives, and methodology are well-defined and relevant to the current market context.
• Refine and Finalize: Refine the research questions and objectives as needed, making sure they are precise and align with the quantitative methods you plan to use.
1. Designing the Research Methodology:
• Select Appropriate Methods: Choose quantitative methods (e.g., surveys, experiments, observational studies) that will allow you to collect the necessary data to address your research questions.
• Develop a Data Collection Plan: Outline the process for gathering data, including the tools and techniques you will use. Ensure your data collection methods are valid, reliable, and ethical.
2. Implementing the Sampling Strategy:
• Define Your Sample: Clearly identify the target population and describe the sampling technique you will use (e.g., random sampling, stratified sampling). Justify the sample size and ensure it is sufficient to generate reliable results.
• Execute the Sampling Plan: Implement the sampling strategy, ensuring that the sample is representative of the target population.
3. Data Collection and Analysis:
• Collect the Data: Conduct the data collection as per your plan. Ensure the data gathered is accurate, relevant, and sufficient to meet the research objectives.
• Analyze the Data: Use statistical tools and techniques to analyze the collected data. Focus on interpreting the results in relation to your research objectives. Look for trends, patterns, and significant findings. Ensure that your findings are presented using clear and effective visual tools to enhance understanding and communication of the data insights.

 

5. Presentation of Findings:
• Prepare a PowerPoint Presentation: Summarize the entire research process, from the problem statement and objectives to data analysis and key findings. Ensure the presentation is clear, concise, and visually engaging. Ensure that your findings are presented using clear and effective visual tools to enhance understanding and communication of the data insights.
• Deliver the Presentation in Class: Each micro-team will present their findings in a 10-15 minute in-class presentation. Following the presentation, be prepared to answer questions and engage in a discussion with your peers and instructor.

 

 

Submission Guidelines

●        Format: The assignment requires a PowerPoint presentation (digital only).

●        Length: The presentation should include a title slide, followed by slides that cover the research problem, research questions, methodology, sampling strategy, data analysis, and key findings and their interpretation.

●        Deadline: The PowerPoint slides must be submitted by Monday of the week the assignment is due to NEO, no later than 11:59 am.

●        File Naming Convention: Ensure that your file is named according to the following format: LastName_FirstName_CW3_QualitativeResearchProposal

●        Presentation: In-class presentations will be conducted during the week the assignment is due. Each micro team will deliver a 10-15 minute presentation summarizing the research findings and insights, to be presented in class in Week 13 or Week 14.

●         

 

Assignment 3 Assessment Criteria Breakdown

 

	Assessment criteria	%
1	Clarity and Relevance: Is the research problem clearly identified and relevant? Are the research objectives well-defined and aligned with the problem?	30%
2	Methodological Rigor: Is the research methodology appropriate and well-justified? Are the data collection methods valid and reliable?	30%
3	Data Analysis and Findings: Is the data analysis thorough and aligned with the research objectives? Are the findings clearly presented and insightful?	20%
4	Presentation Quality: Is the PowerPoint presentation clear, organized, and visually engaging? Does it effectively communicate the key elements of the research?	20%
	Total	100%

 

Additional Notes:

●        Support Materials: Utilize course textbooks, lecture notes, and any additional resources provided on NEO to guide your research project.

●        Questions: If you have any questions or need clarification, please contact the teacher via email or during office hours before the submission deadline

 

 

8.   General Requirements and School Policies

General requirements

All coursework is governed by AAU’s academic rules. Students are expected to be familiar with the academic rules in the Academic Codex and Student Handbook and to maintain the highest standards of honesty and academic integrity in their work. Please see the AAU intranet for a summary of key policies regarding coursework.

Course specific requirements

There are no special requirements or deviations from AAU policies for this course.