Teaching Marketing Analytics
Introduction
Melding Theory, Practice and Hands-on Applications, Edited book; Deadline now 31 Oct2024
INTEREST CATEGORY: TEACHING AND LEARNING, MARKETING RESEARCH
POSTING TYPE: Revisits
Posted by: Scott Erickson
Call for Entries
Teaching Marketing Analytics
Melding Theory, Practice and Hands-on Applications
ÌýEditor:
Scott Erickson, Charles A. Dana Professor of Marketing, Ithaca College
Teaching Marketing Analytics will be a new offering in the Elgar Guides to Teaching series from Edward Elgar Publishing.Ìý The volume will provide guidance from experienced marketing analytics instructors, concerning teaching marketing analytics within the context of both new and older approaches to planning data collection, executing the plan, and analyzing and employing the results.
Marketing analytics is a relatively young discipline, taught in the context of traditional marketing research vs. new and rapidly changing practical applications.Ìý Long-time instructors of marketing research sometimes find itÌý hard to keep up with the rapid advances in the field and changes in practice.Ìý More recently trained instructors often know the current tools but might not understand the theoretical context and how these tools fit with more traditional approaches like focus groups and surveys.Ìý And marketing analytics is an area in which numerous commercial providers have their own training platforms.Ìý Whether and how to incorporate widely used analytics software into courses, including formal certifications, is another question facing all instructors.Ìý This book seeks input from marketing analytics instructors on how they handle these and other issues surrounding this fast-moving field.
The book would cover teaching current courses in marketing analytics now very popular in Business School curricula but almost unheard of ten years ago.Ìý As a recently launched course, marketing analytics comes with some baggage from previous courses it replaced and faces the prospect of a rapidly changing list of pertinent content and training needs of employers.Ìý That leaves those who teach it in something of a grey area as to what should be included in the course and how it should be taught.
Marketing analytics came out of more traditional marketing research courses.Ìý One area for contributions to the book is continuing to cover basic, traditional project research topics in an analytics environment.Ìý Topics such as:
- Exploratory design (e.g. focus groups, ethnography)
- Descriptive design (e.g. surveys), and
- Causal/Experimental design (e.g. test marketing)
Project research is still done, of course, but how to do and how it still contributes to marketing decision-making is sometimes lost in a course totally focused on newer analytics topics.
A second area for contributions would be core analytics areas on which to focus.Ìý Within a marketing analytics emphasis, topics can include:
- Sources of data for analysis (customer behavior, including digital; transactions; product use; direct and indirect communications tracking; etc.
- Analytics definitions (big data, cloud computing)
- Database structure and use (SQL) and analysis tools (R, Python)
- Statistical concepts (measurement theory, summary statistics, tracking and presentation as with dashboards)
- Predictive analytics (correlation, clustering, neural networks, artificial intelligence)
And any other relevant areas.Ìý These kind of topics can take up an entire course or more, so how much to include in a marketing analytics course is a key question.
A third area could encompass marketing applications of analytics concepts.Ìý This could go in many directions, depending on contributor interests, but topics such as:
- Customer lifetime value
- A/B testing
- Tracking the customer journey/lifecycle
- SEO/SEM
- Website design and optimization
- Inbound marketing
and many others can be explored in individual chapters or as part of individual chapters (e.g. product design applications, customer interactions applications).
A fourth area would include using external certifications as part of the course.Ìý These are ubiquitous, encompass real-world experiences, both students and employers value them on resumes, and so they are an important part of a number of instructors’ analytics courses.Ìý Applications such as:
- Google search
- Google Analytics
- Salesforce
- Marketing automation platforms like Pardot, Hubspot, and Adobe/Marketo
- Visualization (Tableau, SAS Viya)
- Statistical analysis (R, Python, SPSS)
and numerous others can be effective parts of courses and guidance from experienced instructors on how to incorporate them would be a valuable contribution to the book.
Finally, one-off topics are also of interest.Ìý Business-to-consumer (B2C) vs. business-to-business (B2B) applications are quite different, and instructors emphasizing one area might not be as familiar with the possibilities in the other.Ìý Ethics and regulation, especially concerning personal data and now artificial intelligence (AI), are also important topics that might be covered.Ìý Data sources (publicly available vs. collected as part of the course) and use might also be included here though may also come up in other areas.ÌýÌý Other suggested contributions are welcome.
Entries:
The book will consist of selected chapters ranging between 6,000 and 10,000 words.Ìý Details on format will be provided to potential contributors.Ìý To ensure editorial integrity and foster diverse perspectives, the Editors request that authors peer-review two entries from other contributors for every entry they submit.
Interested contributors can send an initial 250-word outline that contains a precis of the content they wish to submit, and why it is important to include in the book. Please send these initial entries and further enquiries to:
Scott Erickson
Editor, Elgar Teaching Marketing Analytics
Email: mateaching2024@gmail.com,
or directly at gerickson@ithaca.edu
Deadlines
2024
January/May – Solicitation of authors to write and peer-review chapters for the book.
Commitment from authors, editor will distribute Contributors Agreements to each author.
October 31: Deadline for submission of written entries from authors.
November: Distribution of entries to peer-reviewers.
December 31: Deadline for editor to complete review of peer-reviewed submission, provide feedback on entries.
2025
March 1: Deadline for rewrites and resubmissions
April 30: Deadline for editor to complete final revisions and submit manuscript to publisher.
As above, all entries are due on May 31, 2024, but can be sent at any time before that.
The referencing system for in-text citations is (Author, Year). To refer to a specific page it is (Author, Year: p. 166). The reference list should follow the Harvard style ()