Table Of ContentDigital Analytics for Marketing
This comprehensive book provides students with a “grand tour” of the tools needed
to measure digital activity and implement best practices for using data to inform
marketing strategy. It is the fi rst text of its kind to introduce students to analytics
platforms from a practical marketing perspective.
Demonstrating how to integrate large amounts of data from web, digital, social,
and search platforms, this helpful guide offers actionable insights into data analysis,
explaining how to “connect the dots” and “humanize” information to make effective
marketing decisions. The authors cover timely topics, such as social media, web
analytics, marketing analytics challenges, and dashboards, helping students to make
sense of business measurement challenges, extract insights, and take effective
actions. The book’s experiential approach, combined with chapter objectives,
summaries, and review questions, will engage readers, deepening learning by helping
them to think outside the box.
Filled with engaging, interactive exercises and interesting insights from industry
experts, this book will appeal to students of digital marketing, online marketing, and
analytics. A companion website features an instructor’s manual, test bank, and
PowerPoint slides.
Marshall Sponder holds a dual appointment as a Faculty Lecturer at Zicklin School
of Business, Baruch College, USA, where he teaches digital analytics, text analytics,
and Internet marketing to graduate and undergraduate students, and as an Associate
Professor of Professional Practice at Rutgers Business School, USA.
Gohar F. Khan is a Senior Lecturer at the University of Waikato, New Zealand. His
research interests include social media analytics, social media adoption/use, and
network analysis. His work on social media and information systems has appeared in
several refereed journals, conference proceedings, and books.
“Digital Analytics for Marketing explores the increasingly murky world of social media
data, providing a comprehensive and practical framework for understanding and
analyzing data from a variety of social media marketing channels. A must-read for
digital marketing enthusiasts.”
Stuart Dillon, University of Waikato, New Zealand
“Data analytics is one of the most signifi cant techniques for modern business
organizations to attain and sustain their competitive advantages. This book deals
deeply with various data analytics on the Internet including web, social media, and
mobile analytics. This is a must-read for beginners as well as experts who are eager to
learn the strategic use of data analytics for marketing.”
Hangjung Zo, Korea Advanced Institute of Science and Technology, South Korea
“This book is an excellent survey of the digital analytics world, providing a solid
foundation to the breadth of platforms, tools, and apps. Sponder and Khan
demonstrate how digital analytics is used for research by public entities and
businesses to understand population and consumer behavior, and how this leads to
improvement in population, quality of life, and/or increasing market share and profi t.”
Alan Barnett, Baruch College, USA
“In order to have an informed perspective on where we are and where we’re going, it’s
imperative that we know from where it is we came. In Digital Analytics for Marketing,
Marshall Sponder and Gohar F. Khan tackle a meaty subject and condense it into
salient, palatable chunks for all levels. Required reading for the digital practitioner and
technologist.”
Barry J. Fleming, VP, Digital, MPA – The Association of Magazine Media, USA
Digital Analytics
for Marketing
Marshall Sponder and Gohar F. Khan
First published 2018
by Routledge
711 Third Avenue, New York, NY 10017
and by Routledge
2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN
Routledge is an imprint of the Taylor & Francis Group, an informa business
© 2018 Taylor & Francis
The right of Marshall Sponder & Gohar F. Khan to be identifi ed as authors of this work
has been asserted by them in accordance with sections 77 and 78 of the Copyright,
Designs and Patents Act 1988.
All rights reserved. No part of this book may be reprinted or reproduced or utilised in
any form or by any electronic, mechanical, or other means, now known or hereafter
invented, including photocopying and recording, or in any information storage
or retrieval system, without permission in writing from the publishers.
Trademark notice: Product or corporate names may be trademarks or registered
trademarks, and are used only for identifi cation and explanation without intent to infringe.
Library of Congress Cataloging-in-Publication Data
A catalog record for this book has been requested
ISBN: 978-1-138-19067-2 (hbk)
ISBN: 978-1-138-19068-9 (pbk)
ISBN: 978-1-315-64091-4 (ebk)
Typeset in Helvetica Neue
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Visit the companion website at www.routledge.com/cw/sponder.
Dedication
Special thanks to my wife JoAnn Lefebvre and my son Adam Sponder.
This book happened, partly due to my faculty chair at Zicklin School of Business,
David Luna, introducing me to Sharon Golan, an acquisitions editor at Routledge/
Taylor & Francis in March 2014. Professor David Luna has provided invaluable
support, and helped to create a great working environment in the department of
Marketing and International Business at Baruch College. Since April 2014 the idea this
manuscript gradually developed into its fi nal form. Alan Barnett, Karthik Sridhar, and the
Dean of International Studies, Myung-Soo Lee—my marketing department colleagues
at Baruch—provided valuable advice and support as I began to write this manuscript.
And the contributions of my friends Adi Andrei and Hitomi Sakamoto in London helped
me to cement the data methodologies used in various parts of this book. I would
also like to thank my colleagues at Rutgers Business School, Jennifer Fine, Joseph
Schaffer, Lei Lei, Yaw Mensah, Ashwani Mong Richard Metzger, Ruqqayya Maudoodi,
and Peter Methot for the support they have provided in support of the Rutgers
Business School/Mason Gross School of the Arts course “Social Media for the Arts”
that I author and teach. Social Media for the Arts has been the crucible that merged
many of ideas of the Art/Technology merger that makes this book so different than
others about Analytics.
As the manuscript moved towards completion, I discovered the work of Professor
Gohar F. Khan and his Seven Layers of Social Media Analytics book one summer night
while searching on Google. I was impressed with what I saw and bought a copy of
his book immediately. One thing led to another, and Gohar became the co-author of
this book, and I am very grateful for that. Gohar’s contributions broadened the scope
of the manuscript and deepened its academic underpinnings—a win-win in the fullest
sense of the term.
Finally, I want to think some of my most talented students at Baruch College and
Rutgers University who provided valuable editorial support and insights, along with a
window into the millennial mind, such as Nate Harris, Rachit Mehta, Taylor Frankel,
Sierra Laney, and Sharon Clott. These students continued to support and inspire me
to create a book aimed at the next generation of analysts, thinkers, and business
leaders.
Contents
List of Figures and Tables ix
Manuscript Class Reviewers at Zicklin School of Business and
Rutgers University, and Other Academic Chapter Reviewers xiii
Preface xv
1 The Evolution of Digital Analytics and the Internet 1
2 Search Engines and the Internet 19
3 Social Media History 55
4 Digital Analytics Industry Players 71
5 Basic Web Analytics and Web Intelligence 83
6 Advanced Web Analytics and Web Intelligence 115
7 Understanding and Working with Third-Party Data 145
8 An Introduction to Social Media Analytics 167
9 Leveraging Social Media Content and Analytics 189
10 Advanced Text Analytics and Algorithms 225
11 Geo-Location Analytics 261
12 Social Media Actions Analytics 283
13 Social Media Hyperlink Analytics 297
14 Network Analysis and Social Network Mapping 313
15 Mobile Analytics 337
16 Aligning Digital Media with Business Strategy 349
17 Applying Digital Analytics to a Social Network 369
Index 381
Figures and Tables
Figures
PR1 Parts of the core curriculum and electives xviii
PR2 The fi rst Analytics Selfi e, July 2014, Baruch College Web Analytics
graduate class xx
PR3 Rutgers University, Social Media for the Arts course growth, 2012–2017 xx
PR4 Class growth in online presence in Social Media, Fall 2016 xxiii
1.1 Structured vs. unstructured data 2
1.2 URI structure 9
1.3 Evolution of Digital Analytics 13
1.4 Digital ad spending worldwide, 2015–2020. Data derived from eMarketer 15
2.1 Essential functions of a Web search engine 23
2.2 PageRank algorithm ranking example 27
2.3 Building blocks of Search Engine Optimization 29
2.4 Online and offl ine customer acquisition strategies 30
2.5 Digital marketing mix process and strategy 38
2.6 Search formulation process 41
2.7 Ellen’s selfi e at the 2014 Academy Awards 46
2.8 Demandmetrics Digital Analytics for Marketing SEO Maturity Assessment 51
3.1 Social media timeline 58
5.1 The spectrum of Web Analytics 85
5.2 Moving from objectives to digital strategies 88
5.3 Analytics Cycle of Improvement 90
5.4 Moving from Web Analytics data to business insights 90
5.5 KBRs and KPIs 91
5.6 Intermediate Metrics and their impact on Return on Investment 100
5.7 Web Analytics tracking pixel and data collection mechanism 103
5.8 Web Analytics tracking process 104
5.9 Marketing KPIs used by US B2B marketers 108
5.10 Top eight data sources of US digital marketers in 2015 109
5.11 Visualization of Google Analytics multi-channel funnel attribution and ROI 110
5.12 Comparing direct-path and point-based path analysis 111
5.13 Customizing reports for different types of stakeholders 112
6.1 Web data analytics ecosystem 116
6.2 Managing the process for Big Data Analytics adoption 121
6.3 Questions to ask when understanding if a website implementation is
successful 122
6.4 Defi ning the “perfect metric” 124
6.5 Example of behavioral segmentation on an e-commerce website 125
6 .6 Segmentation types in Web Analytics 126
6.7 Marketing funnel for a health club e-commerce site 128
6.8 How Web Analytics records Web referrals 129
6.9 Cross domain tracking in Web Analytics 131
6.10 Web Analytics method of calculating time spent on a page
(and of a visit/session) 132
6.11 Adding page scoring to specifi c pages of a website 133
