Elgar Encyclopedia of Marketing Analytics
Introduction
Call for entries; Deadline 15 Sep 2024
INTEREST CATEGORY: MARKETING RESEARCH
POSTING TYPE: Calls: Other
Posted by: Scott Erickson
Call for Entries
Elgar Encyclopedia of Marketing Analytics
Editors
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. 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. 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. 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. 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. 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). 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. 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. 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:
Scott Erickson and Tracey Renzullo
Co-Editors Elgar Encyclopedia of Marketing Analytics
Email: MAEncyclopedia@gmail.com
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.
September 15: Deadline for submission of written entries from authors.
October 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 September 15, 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
- Account-based marketing (ABM)/marketing automation
- ANOVA
- Apps and data
- Artificial intelligence
- 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
- Clustering
- Commercial data (e.g. Nielsen)
- Competitive Intelligence Data
- Content analysis
- Content management
- Correlation
- Cross-tabulation
- Customer Journey
- Customer lifetime value
- Customer metrics
- Customer relationship management (CRM)
- Customer satisfaction
- 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
- Descriptive analytics
- Descriptive marketing research
- 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)
- Digital monitoring products (e.g. Adobe Audience Manager)
- Direct Marketing
- Ecommerce data
- Email management
- Ethics and Data Collection
- Ethnography
- EU General Data Privacy Regulation
- Experimental design
- Experimental design (repetitive)
- Exploratory marketing research
- Focus groups
- 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)
- 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
- Prescriptive analytics
- Programming (e.g. R, Python)
- Psychographic data
- Qualitative data analysis
- Quantitative data
- Regression (linear, multiple, R-squared, moderation, interaction)
- Relational databases (e.g. SQL)
- Sales Funnel
- Sales Modelling and Forecasting
- Search
- Sentiment analysis
- Social listening
- Social media
- Spreadsheets (e.g. Excel)
- Stakeholders
- Statistical significance
- Strategic significance of data
- Structured data
- Summary statistics
- Surge analytics
- Survey/questionnaires
- Tabulation
- Test markets
- Transactional data
- Traffic Sources of web data
- Training Programs/Education for Data Analytics Professionals
- T-tests
- Unstructured data
- Web data
- Website analytics (e.g. Google Analytics)
- Word clouds
- Word counts
.