The Marketing Analytics Simternship
Turnkey materials to add practical, hands-on learning to your course
The Marketing Analytics Bundle helps you prepare students to make data-driven marketing decisions using essential analytics tools, techniques, and strategies. This bundle includes the hands-on Stukent Marketing Analytics Simternship and the comprehensive “Marketing Analytics” courseware, two innovative resources that help you bring effective, hands-on learning into your course with less hassle!
The Stukent Marketing Analytics Simternship
Bring authentic, turnkey data sets into your classroom
This Marketing Analytics Simternship is an engaging way to increase students’ employability and prepare them for real-world roles.
The simulation asks your students to step into the role of a marketing analytics intern for a simulated e-commerce company. To succeed, your students must clean and analyze multiple datasets, identify insights, calculate metrics, run A/B tests, and select appropriate visuals to represent their findings. Students will also practice SQL interactions, which mimic the coding language used to interact with data banks.
Your students will master key analytics skills, including:
Collecting marketing data
Cleaning marketing data
SQL Queries
Creating reports
Optimizing campaigns
Conducting A/B tests
Data visualization
Presenting insights
Key simulation learning objectives
Over the course of nine rounds, your students will . . .
- Demonstrate an understanding of the processes and techniques of marketing data collection, analysis, and visualization
- Explain and apply the logic of optimization and attribution in marketing analytics
- Explain the terminology and tools of marketing analytics
- Apply the practical tools and techniques of marketing analytics
- Study and practice programming tools and structured query language
- Understand the roles of data technologies, data management systems, and data visualization in marketing
- Run field experiments in digital environments, including A/B testing
- Understand marketing mix models
Hands-on Learning without the Hassle
Stukent Simternships integrate with your favorite LMS platforms
Single Sign-on
Grade Book Syncing
Deep Linking
Rostering
Practice, Meet Pedagogy
Pair Your Simternship with Stukent Courseware
Stukent courseware aligns with your Simternship, giving your students a solid foundation for success.
Stukent Courseware
Courseware that puts classroom concepts into professional contexts
Stukent courseware goes beyond the limitations of the printed textbook, pairing powerful instructional resources for you with concise, annually updated text for students.
An Authoritative Text + Robust Instructional Resources
The Marketing Analytics Courseware
The “Marketing Analytics” courseware helps you give students a foundation in data analytics and develop skills they can use in their coursework and future careers. The text introduces students to marketing data collection, analysis, and visualization; the marketing mix; SQL; A/B testing; and how statistical models are essential for today’s data-driven marketers.
This courseware contains turnkey resources, such as auto-graded assessments, lesson plans, and lecture slide decks. With Stukent, you can teach your best course in less prep time!
An Authoritative Text + Robust Instructional Resources
The Marketing Analytics Courseware
The “Marketing Analytics” courseware helps you give students a foundation in data analytics and develop skills they can use in their coursework and future careers. The text introduces students to marketing data collection, analysis, and visualization; the marketing mix; SQL; A/B testing; and how statistical models are essential for today’s data-driven marketers.
This courseware contains turnkey resources, such as auto-graded assessments, lesson plans, and lecture slide decks. With Stukent, you can teach your best course in less prep time!
What’s Inside
Table of Contents
Introduces the fundamentals of marketing analytics, including data collection, analysis, visualization, and the growing demand for skilled professionals in the field.
Explores essential tools like spreadsheets, programming languages, and a comparison of Excel, R, and Python, while explaining variable types and their practical application.
Examines key data technologies, including relational and non-relational databases, MongoDB, Hadoop, and NoSQL, to support effective marketing analytics.
Introduces SQL as a critical tool for accessing, managing, and analyzing marketing data efficiently.
Explores first-, second-, and third-party data, inbound marketing strategies, data management platforms, and key data privacy regulations like GDPR and CCPA.
Covers tools for extracting and analyzing web-based data, including social listening tools, web analytics, and content analysis platforms.
Explains how to use data and cluster analysis to implement segmentation, targeting, and positioning strategies effectively.
Explores the principles and applications of A/B testing, including sample sizing, segmentation, tools, and key considerations for effective promotional campaigns.
Introduces experimental design, covering causal inference, participants, and the gold standard for conducting cause-and-effect analyses in marketing.
Explores the role of artificial intelligence, including machine learning, deep learning, generative AI, and case studies in transforming marketing applications.
Highlights the importance of data visualization, introduces essential tools, and demonstrates how visualization aids in communicating actionable insights.
Provides an overview of marketing metrics, strategies for using them effectively, and a focus on key performance indicators to evaluate campaign success.
Explains statistical techniques, including T-tests and ANOVA, to analyze A/B test results and experiments while emphasizing the scientific method.
Explores marketing mix modeling through regression analysis, focusing on diagnostics and evaluating the effectiveness of marketing strategies.
Introduces moderation analyses in marketing mix models, detailing variable types, interaction estimates, and advanced methods like spotlight and floodlight analysis.
Key courseware concepts
In this courseware, your students will ...
- Demonstrate an understanding of the processes and techniques of marketing data collection, analysis, and visualization
- Explain and apply the logic of optimization and attribution in marketing analytics
- Apply the practical tools and techniques of marketing analytics
- Study and practice programming tools and structured query language
- Engage in social listening and content analysis
- Explain the terminology and tools of marketing analytics
- Understand artificial intelligence, machine learning, and deep learning
- Understand the roles of data technologies, data management systems, and data visualization in marketing
- Run field experiments in digital environments, including A/B testing
- Understand marketing mix models
Embedded Educator Resources
Everything You Need to Teach
Your Best Course
- 15 chapters
- 15 auto-graded chapter quizzes
- 15 lesson plans
- 15 lecture slide sets
- Sample syllabus
- Sample course calendars
- Cumulative glossary for student reference
- Activities for online, in-person, and hybrid modalities
About the Author
Dr. Brennan Davis is Professor and Director of the Master of Science for Business Analytics program at the Orfalea College of Business at California Polytechnic State University. He has seven years of experience teaching the marketing core class, marketing research, and marketing analytics.
He specializes in connecting large datasets to answer questions in the domain of transformative consumer research. Professionally, Dr. Davis has eight years of experience in marketing management in the automotive and technology industries. In 2015, he received the Hood Professorship of Marketing in the Orfalea College of Business.
Dr. Davis’ work has been published in many journals, including the Journal of Public Policy and Marketing where he won the best paper award for the journal in 2014 from the American Marketing Association, and in the American Journal of Public Health where he won the best paper award in 2009 from the Robert Wood Johnson Foundation. He has also published in the Journal of Business Research and has working papers targeting other top academic marketing and consumer research journals.
