Principles of Marketing Analytics: Understand Data-Driven Decision-Making

by Ijeoma Onwumere

Overview

This introductory textbook demystifies the complex field of marketing analytics, taking students on a journey from fundamental concepts to practical insights.

Ideal for undergraduate students, beginning to learn marketing analytics, Principles of Marketing Analytics covers:

- Data collection and measurement
- Customer segmentation and targeting
- Marketing campaign optimization
- Machine learning for marketing
- Forecasting future marketing trends

As well as web analytics, social marketing analytics and exploring the potential of generative AI for A/B testing and customer engagement. Learn how to implement data-driven marketing strategies through practical exercises and valuable insights. Online resources include PowerPoint slides and a guide for lecturers, and in-text features include a glossary, key learning points and real-world examples from companies such as Netflix and Airbnb.

Product Details

ISBN-13:	9781398623293
Publisher:	Kogan Page, Ltd.
Publication date:	02/24/2026
Pages:	336
Product dimensions:	6.14(w) x 9.21(h) x 0.00(d)

About the Author

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.

Table of Contents

** 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