Ijeoma Onwumere

Principles of Marketing Analytics

Understand Data-Driven Decision-Making

• Gebundenes Buch

Produktbeschreibung

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.

Produktdetails

• Verlag: Kogan Page Ltd
• Seitenzahl: 336
• Erscheinungstermin: 3. Februar 2026
• Englisch
• Abmessung: 234mm x 156mm
• ISBN-13: 9781398623293
• ISBN-10: 1398623296
• Artikelnr.: 73873285

Autorenporträt

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.

Inhaltsangabe

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