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Call for Entries

Elgar Encyclopedia of Marketing Analytics

ÌýEditors:

1. Scott Erickson, Charles A. Dana Professor of Marketing, Ithaca College

Tracey Renzullo, Marketing Professor and Program Head, British Columbia Institute of Technology

The Elgar Encyclopedia of Marketing Analytics is a single-volume encyclopedia in a new and exciting series offered by Edward Elgar Publishing.

This volume will provide relatively concise encyclopedic coverage of the discreet subfield of marketing analytics.Ìý We aim to capture a comprehensive set of diverse perspectives on both traditional marketing research and how it has emerged as the contemporary field of marketing analysis.Ìý The work will accomplish this objective with easy-access entries and references to assist scholars, researchers, and practitioners as they search for seminal content in this important, rapidly changing field.

The editors wish to create a volume that provides readers with key foundational, theoretical, and applied concepts in the field of marketing analytics, including but not limited to data sources and generation, monitoring and reporting, statistical analysis and data mining, and predictive analytics.Ìý We are also interested in contributions covering how more traditional topics such as exploratory, descriptive, and experimental research have been tailored to big data and analytics environments.

We encourage contributions from both scholars and practitioners.Ìý While the basis of the book is theoretical perspectives and how contemporary marketing analytics fits core concepts in the discipline, much of the growth in the field has also come from digital solutions provided by commercial organizations.Ìý Entries from digital providers are welcome but should be written from the perspective of a class of products (e.g. customer relationship management) rather than a specific brand (e.g. Salesforce).Ìý While examples of the practitioner’s specific products can and should be part of any such chapter, they should not read as an explicit sales pitch.Ìý Entries concerning unique or noteworthy applications of marketing analytics at a specific brand or company are also encouraged.

Entries:

The single-volume Encyclopedia will consist of around 200,000 to 300,000 words that reflect selected entries from authors who respond to this call, or specially commissioned entries. Authors may choose to contribute one or more entries. The editors seek entries that provide a concise summary of the most relevant accumulated knowledge on a subject or concept. We expect that the length of entries will vary but, as a guide, more complex entries should be 2,000-3,000 words, while less complex entries (e.g., the definition of a key concept) as little as 1,000 words.

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. Authors will be entitled to post the pre-print version of their entry on their own website and institutional repository after a six-month embargo period. For those interested, there will also be an option to publish a limited number of entries Open Access for a fee.

Organization of entries will be alphabetical though the editors will develop additional organizing principles to ensure both appropriate coverage and to aid contributors and readers in navigating the many avenues of this complex field.Ìý We are appending an initial list that interested contributors can consult. We also encourage contributors to propose their own entries not on our list for consideration. 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 Encyclopedia. Please send these initial entries and further enquiries to:

1. Scott Erickson and Tracey Renzullo

Co-Editors Elgar Encyclopedia of Marketing Analytics

Email: MAEncyclopedia@gmail.com

gerickson@ithaca.edu (direct)

Deadlines

2023

November/December — Solicitation of authors to write and peer-review entries for the encyclopedia.

2024

January/June – Continue solicitation of authors to write and peer-review entries for the Encyclopedia.

Commitment from authors, co-editors will distribute Contributors Agreements to each author.

November 30: Deadline for submission of written entries from authors.

December 15: Distribution of entries to peer-reviewers.

2025

February 15: the Deadline for Co-editors to complete their review of peer-reviewed submissions.

March 30: Deadline for Co-editors to provide feedback on entries.

May 30: Deadline for rewrites and resubmissions.

August 31: Deadline for Co-editors to complete final revisions and submit manuscript to publisher.

Final Entries and Due Date:

All final entries are due on November 30, 2024, but can be sent at any time before that. Please follow the structure below:

Title

Introduction and brief overview of the topic, figure/author/researcher, or concept.

Discussion and application

Critical summary and conclusion

Name of Author (right indent)

References and selected further readings.

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 ()

Call for Entries

Elgar Encyclopedia of Marketing Analytics

Suggested Topics List

A/B testing	Assigned
Account-based marketing (ABM)/marketing automation
ANOVA	Assigned
Apps and data
Artificial intelligence	Assigned
B2B Data Types
Bayesian statistics
Big Data
Board of Directors role and liability in data governance
Brand awareness
Brand metrics
Brand preference
Breach of data
Business Intelligence
California Consumer Protection Act
Campaign analytics
Causal/experimental marketing research
Click-through rates/conversions	Assigned
Clustering
Commercial data (e.g. Nielsen)
Competitive Intelligence Data
Content analysis	Assigned
Content management
Correlation	Assigned
Cross-tabulation	Assigned
Customer Journey
Customer lifetime value
Customer metrics
Customer relationship management (CRM)
Customer satisfaction	Assigned
Customer segmentation based on data
Cybersecurity data science
Dashboards
Data and analytics strategy
Data analysis tools
Data applications and use (e.g. Netflix, Spotify)
Data audit
Data cleaning
Data driven organizations
Data and decision making
Data and the cloud
Data and sports
Data engineering
Data integration
Data management platforms
Data literacy
Data mining
Data privacy and protection
Data quality and validation
Data ransom attacks
Data reporting
Data security versus accessibility
Data sources – internal
Data sources – external
Data visualization
Deep learning
Demographic data	Assigned
Descriptive analytics
Descriptive marketing research	Assigned
Decision Tree
Development metrics
Diagnostic analytics
Digital metrics (click-through rate, conversion rate, inbound links, referral traffic, bounce rate, return visitors rate, average time on website, average page views, cost per lead, ROI)	Assigned
Digital monitoring products (e.g. Adobe Audience Manager)
Direct Marketing
Ecommerce data
Email management	Assigned
Ethics and Data Collection	Assigned
Ethnography
EU General Data Privacy Regulation
Experimental design
Experimental design (repetitive)
Exploratory marketing research	Assigned
Focus groups	Assigned
Fraud
Global Data
Google Adwords/Paid Search
Google Analytics
Government data
Inbound marketing
Insights derived from data
Intent Data
Interviews
Key performance indicators (KPI’s)
K-means clustering
Lead Generation
Loyalty programs
Machine learning
Marketing analytics
Marketing automation
Martech stack
Measurement concepts (nominal, ordinal, interval, ratio)	Assigned
Media ratings/circulation
Mobile data
Mobile design
Monitoring data
Most valuable pages
Neural networks
Non-relational databases (e.g. Hadoop)
Online content counts
Organizational structure
Podcasts
Predictive analytics	Assigned
Prescriptive analytics
Programming (e.g. R, Python)
Psychographic data	Assigned
Qualitative data analysis	Assigned
Quantitative data
Regression (linear, multiple, R-squared, moderation, interaction)
Relational databases (e.g. SQL)
Sales analytics	Assigned
Sales Funnel
Sales Modelling and Forecasting
Search
Sentiment analysis
Social listening	Assigned
Social media
Spreadsheets (e.g. Excel)
Stakeholders
Statistical significance	Assigned
Strategic significance of data
Structured data
Summary statistics
Surge analytics
Survey/questionnaires	Assigned
Tabulation
Test markets
Transactional data
Traffic Sources of web data
Training Programs/Education for Data Analytics Professionals
T-tests	Assigned
Unstructured data
Web data
Website analytics (e.g. Google Analytics)
Word clouds
Word counts