Course Code :  MARK5826

Year :  2023

Term :  Term 3

Teaching Period :  T3

Delivery Mode :  In Person

Delivery Format :  Standard

Delivery Location :  Kensington

General Course Information

Course Code :  MARK5826

Year :  2023

Term :  Term 3

Teaching Period :  T3

Is a multi-term course? :  No

Faculty :  UNSW Business School

Academic Unit :  School of Marketing

Delivery Mode :  In Person

Delivery Format :  Standard

Delivery Location :  Kensington

Campus :  Sydney

Study Level :  Postgraduate

Units of Credit :  6

Useful Links

Handbook ClassTimetable

Course Details & Outcomes

Course Description

Today’s data-rich environment and advances in big data analytics have enabled product idea generation from the crowd, innovative “data”-based products or services development, and   effective marketing of new product ideas on crowdfunding platforms. Now, “data” itself may form part of the “core material” of new products or services.

This course integrates the principles of product development with data analytics and human-

centered enterprise design-thinking process by covering (1) new product idea generation using   natural language processing such as sentiment analysis or topic modelling to analyse product    reviews, (2) new product roadmap planning using the design-thinking (3) data product or service development such as book recommendation algorithms, and a virtual personal assistant (e.g.,    chatbot), (4) product attribute optimisation using A/B test or conjoint analysis, (5) product

demand forecasting, and (6) advertising new product ideas on crowdfunding platforms.

For course projects, students will exercise hands-on data analytics using Python and build data   products (e.g., chatbots) using IBM Watson Assistant as well as plan product roadmap using the design-thinking process template (e.g., Mural). No prior knowledge of Python or IBM Watson

Assistant is needed.

Course Aims

This course is offered as part of the Marketing stream until 2018 and Marketing Analytics stream from 2019 in the MCom degree.

Basic statistical knowledge and skills (up to typical regression analysis) is assumed before

starting this course. The pre-requisite for this course is COMM5005, COMM5011, ECON5248 or equivalents.

MARK5826 integrates the principal of product development and big data analytics from new product idea generation and marketing new product idea, to data product development and   product management. The aim is to produce marketing data scientists who can work as

Marketing, Product and Brand Managers, Entrepreneurs, or Business Analyst.

MARK5826 offers data analytics toolbox for new product idea generation and development,

while MARK5813 and MARK6102 courses conceptual foundation and qualitative approach. Next,

MARK5822 covers overall marketing analytics. But, MARK5826, 5827, and 5828 focuses on specifc data analytics for product, customer, and advertising-related decision making, respectively.

Relationship to Other Courses

Course Learning Outcomes

Learning and Teaching Technologies

Moodle - Learning Management System | Zoom

Learning and Teaching in this course

This course aims to deliver new data product development using both hard and soft skills. For hard skills, this course will introduce (1) text analytics to generate product ideas from product review data, (2) product recommendation algorithm as one example of data product, and (3)

Product A/B test. You will also learn how to build a chatbot using a technical platform (e.g., IBM Watson Assistant). Students will have many opportunities to exercise those data analytics and   product development via lab quizzes and projects. The step-by-step guidelines will be given.

Next is soft skills. Students will use the human-centred enterprise design-thinking process

template, Mural, to identify customer needs and plan product roadmap. Also, your group will

design a conversation fow frst to get the big picture about your data product (e.g., chatbot). In   addition, this course emphasizes the importance of data communication using visualization and prototype tools. These data communication efforts help students understand the big picture,

stimulate discussion with team members, develop a plausible hypothesis, and deliver the

business value of their data analytics results. Furthermore, students will investigate qualitative (and quantitative) answers from market research for a product test.

Other Professional Outcomes

Learning and Teaching Technologies

Moodle - Learning Management System | Zoom

Learning and Teaching in this course

This course aims to deliver new data product development using both hard and soft skills. For hard skills, this course will introduce (1) text analytics to generate product ideas from product review data, (2) product recommendation algorithm as one example of data product, and (3)

Product A/B test. You will also learn how to build a chatbot using a technical platform (e.g., IBM Watson Assistant). Students will have many opportunities to exercise those data analytics and   product development via lab quizzes and projects. The step-by-step guidelines will be given.

Next is soft skills. Students will use the human-centred enterprise design-thinking process

template, Mural, to identify customer needs and plan product roadmap. Also, your group will

design a conversation fow frst to get the big picture about your data product (e.g., chatbot). In   addition, this course emphasizes the importance of data communication using visualization and prototype tools. These data communication efforts help students understand the big picture,

stimulate discussion with team members, develop a plausible hypothesis, and deliver the

business value of their data analytics results. Furthermore, students will investigate qualitative

(and quantitative) answers from market research for a product test.

Additional Course Information

To successfully complete this course, effective communication between us is vital. I will use

Moodle to send you information between you need to check it regularly. If you have any general question about the course, please post on Q&A or discuussion forum. Specifc questions are

best dealt with during the lecture, consultation times or by appointment. Please use your

student-email to communicate with me. I will not open your email coming from yahoo, hotmail,   gmail, and the like, even if it gets through the spam flters, as I will not know you are a student.    Student-email messages get frst priority in being answered. Please note any question related to the tutorials should be frst addressed to your respective tutors. All emails should state your

name, zID and course MARK5826 plus the class you are enrolled in i.e. your tutorial time, to enable us to respond appropriately.

All correspondence will be answered within 2 working days (i.e. not weekends or nights).

Assessments

Assessment Structure

Assessment Details

Customer Problem Identifcation – Individual Report

Assessment Overview

You will identify customer problems using natural language processing such as sentiment analysis or topic modelling.

Detailed Assessment Description

This assessment provides the opportunity to identify customer problems from product review data and generate new product or service ideas.

After customers purchase and use products or services, they share their experience in an online product review platform. Many companies try to identify customer problems and their unmet

needs from large-scale product review data by using natural language processing such as topic modelling and sentiment analysis. The recent AI methods allow us to categorize text data

automatically by doing topic modelling and labelling together, although it is not perfect yet. Your task is to identify customer problems using both an AI machine and Human’s manual labelling    and generate new product or service ideas.