Principles of Marketing Analytics

Understand Data-Driven Decision-Making
1. Auflage 2026
ISBN: 978-1-3986-2327-9
Verlag: Kogan Page

Buch, Englisch, 336 Seiten, Format (B × H): 170 mm x 240 mm, Gewicht: 667 g

This practical undergraduate textbook is ideal for building data-driven, analytical marketing skills.

Principles of Marketing Analytics is an introductory textbook for undergraduate and postgraduate marketing students. Ijeoma Onwumere takes readers from foundational principles to applied insights of marketing analytics, developing the analytical mindset and confidence to make evidence-based marketing decisions.

This textbook explains how data drives segmentation, targeting, campaign optimization, and forecasting, bridging marketing theory with analytical practice. Students will learn to collect, analyse and interpret data and explore how technologies such as machine learning and generative AI are transforming the discipline.

Designed for both classroom learning and independent study, this textbook aligns with undergraduate modules in marketing analytics and digital marketing. It includes:

- Frameworks including AIDA Model (Awareness, Interest, Desire, Action), CRO (conversion rate optimization) and TBL (triple bottom line) for applying analytics to marketing challenges
- Real-world examples from Netflix, Walmart, Airbnb, Sephora, Nike and more that connect theory and practice and shows how data-driven insights power measurable impact
- Exercises, discussion questions, and chapter summaries to consolidate learning
- Key terms list and key learning points for quick review
- Online resources for lecturers, including slides and a teaching guide

Whether studying marketing analytics or preparing for a data-informed career, Principles of Marketing Analytics equips students with the skills to make confident, data-driven marketing decisions.

Autoren/Hrsg.

Onwumere, Ijeoma

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Marktforschung
• Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

Chapter - 01: Introduction to marketing analytics: Defining the field Chapter - 02: Data collection and measurement: Best practices for collecting, organising, and storing marketing data; Chapter - 03: Key marketing metrics: Understanding the essential metrics for measuring marketing performance; Chapter - 04: Customer segmentation and targeting: Using data to identify and reach high-value customer segments; Chapter - 05: Marketing campaign optimization: Leveraging data for effective marketing campaigns; Chapter - 06: Social media analytics: Tracking social media performance and engaging with customers online; Chapter - 07: Web analytics: Analysing website traffic to optimize user experience; Chapter - 08: Predictive Modeling: Using data to forecast future marketing trends and outcomes; Chapter - 09: Marketing Attribution: Determining the effectiveness of different marketing channels and touchpoints; Chapter - 10: Machine Learning for Marketing: Leveraging AI to automate marketing tasks and improve decision-making; Chapter - 11: The Rise of Generative AI in Marketing: Exploring the potential of Generative AI

Über Autor(innen)

Ijeoma Onwumere is a lecturer and academic researcher in Fashion Business and Marketing analytics at Manchester Metropolitan University, UK. Her specific area of focus lies is digital marketing, marketing analytics, service quality, sustainability and business analytics.