Predictive Marketing

Easy Ways Every Marketer Can Use Customer Analytics and Big Data

Author: Omer Artun,Dominique Levin

Publisher: John Wiley & Sons

ISBN: 1119037360

Category: Business & Economics

Page: 272

View: 4893

Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness. In reality most marketers still practice one-size-fits-all marketing. Predictive analytics can finally make personalized marketing a reality – by making it easy and automated. Predictive marketing is for the first time accessible to all marketers, not just to those at large corporations. In fact, many smaller organizations are leap-frogging their larger counterparts with innovative programs. This book will offer marketers in organizations large and small a great primer of “predictive analytics for marketers” as well as practical tips and strategies to get started immediately. The book will feature many success stories from across the customer lifecycle: how to use machine-learning technologies to improve customer acquisition, customer growth and how to identify and re-engage customers at risk or lapsed customers.

Predictive Marketing

Easy Ways Every Marketer Can Use Customer Analytics and Big Data

Author: Omer Artun,Dominique Levin

Publisher: John Wiley & Sons

ISBN: 1119037336

Category: Business & Economics

Page: 272

View: 2008

Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.

Predictive Marketing

Easy Ways Every Marketer Can Use Customer Analytics and Big Data

Author: Omer Artun,Dominique Levin

Publisher: John Wiley & Sons

ISBN: 1119037328

Category: Business & Economics

Page: 272

View: 4664

Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.

Marketing Data Science

Modeling Techniques in Predictive Analytics with R and Python

Author: Thomas W. Miller

Publisher: FT Press

ISBN: 0133887340

Category: Business & Economics

Page: 225

View: 8656

Now , a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications. Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes: The role of analytics in delivering effective messages on the web Understanding the web by understanding its hidden structures Being recognized on the web – and watching your own competitors Visualizing networks and understanding communities within them Measuring sentiment and making recommendations Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.

Predictive Analytics for Marketers

Using Data Mining for Business Advantage

Author: Barry Leventhal

Publisher: Kogan Page Publishers

ISBN: 0749479949

Category: Business & Economics

Page: 272

View: 4669

Predictive analytics has revolutionized marketing practice. It involves using many techniques from data mining, statistics, modelling, machine learning and artificial intelligence, to analyse current data and make predictions about unknown future events. In business terms, this enables companies to forecast consumer behaviour and much more. Predictive Analytics for Marketers will guide marketing professionals on how to apply predictive analytical tools to streamline business practices. Including comprehensive coverage of an array of predictive analytic tools and techniques, this book enables readers to harness patterns from past data, to make accurate and useful predictions that can be converted to business success. Truly global in its approach, the insights these techniques offer can be used to manage resources more effectively across all industries and sectors. Written in clear, non-technical language, Predictive Analytics for Marketers contains case studies from the author's more than 25 years of experience and articles from guest contributors, demonstrating how predictive analytics has been used to successfully achieve a range of business purposes.

Predictive Analytics

The Power to Predict Who Will Click, Buy, Lie, or Die

Author: Eric Siegel

Publisher: John Wiley & Sons

ISBN: 1119145686

Category: Business & Economics

Page: 368

View: 2644

"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive Analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated — and Hillary for America 2016 plans to calculate — the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.

Predicting Market Success

New Ways to Measure Customer Loyalty and Engage Consumers With Your Brand

Author: Robert Passikoff

Publisher: John Wiley & Sons

ISBN: 0470088796

Category: Business & Economics

Page: 256

View: 6376

Praise for Predicting Market Success "Predicting Market Success has come at the right time for major companies. The value of understanding the dimensions of your brand's unique appeal and strength of preference is indispensable for brand strategy today. This book is well worth your time." —Joseph T. Plummer, Chief Research OfficerThe Advertising Research Foundation "In the competitive world of branding, understanding what drives consumer loyalty is the cornerstone of a brand's continued success. Passikoff's market-driven insights on how to obtain, analyze, and utilize loyalty metrics will help you make strategic, brand-enhancing decisions." —Seth M. Siegel, Cochairman, The Beanstalk Group "Passikoff is the guy who can explain to me why people buy certain things from certain companies, even though other things by other companies seem just as good. With his great feel for pop culture and almost philosophical outlook, he understands what makes consumers tick-and stick." —Lenore Skenazy, syndicated columnist "Loyalty is a key component of the strength of a brand and brand equity, and Passikoff understands loyalty like few others. In this book, he captures the essence of loyalty and branding in a practical way-showing how loyalty drives profitability." —Erich Joachimsthaler, Chairman, Vivaldi Partners "If you want a business book that will make you feel justified, complimented, and comfortable, don't read this. If you want a book to challenge your beliefs about brand marketing right down to the core, you can't afford not to." —John Gaffney, Executive Editor, Peppers & Rogers Group

Effective CRM Using Predictive Analytics

Author: Antonios Chorianopoulos

Publisher: John Wiley & Sons

ISBN: 1119011558

Category: BUSINESS & ECONOMICS

Page: 392

View: 6205

A step-by-step guide to data mining applications in CRM. Following a handbook approach, this book bridges the gap between analytics and their use in everyday marketing, providing guidance on solving real business problems using data mining techniques. The book is organized into three parts. Part one provides a methodological roadmap, covering both the business and the technical aspects. The data mining process is presented in detail along with specific guidelines for the development of optimized acquisition, cross/ deep/ up selling and retention campaigns, as well as effective customer segmentation schemes. Additionally, some of the most useful data mining algorithms are explained in a simple and comprehensive way for business users with no technical expertise. In part two, some of the most useful data mining algorithms are explained in a simple and comprehensive way for business users with no technical expertise. Part three is packed with real world case studies which employ the use of three leading data mining tools: IBM SPSS Modeler, RapidMiner and Data Mining for Excel. Case studies from industries including banking, retail and telecommunications are presented in detail so as to serve as templates for developing similar applications. Key Features: Includes numerous real-world case studies which are presented step by step, demystifying the usage of data mining models and clarifying all the methodological issues. Topics are presented with the use of three leading data mining tools: IBM SPSS Modeler, RapidMiner and Data Mining for Excel. Accompanied by a website featuring material from each case study, including datasets and relevant code. Combining data mining and business knowledge, this practical book provides all the necessary information for designing, setting up, executing and deploying data mining techniques in CRM. Effective CRM using Predictive Analytics will benefit data mining practitioners and consultants, data analysts, statisticians, and CRM officers. The book will also be useful to academics and students interested in applied data mining.

Artificial Intelligence Marketing and Predicting Consumer Choice

An Overview of Tools and Techniques

Author: Steven Struhl

Publisher: Kogan Page Publishers

ISBN: 0749479566

Category: Business & Economics

Page: 272

View: 2659

The ability to predict consumer choice is a fundamental aspect to success for any business. In the context of artificial intelligence marketing, there are a wide array of predictive analytic techniques available to achieve this purpose, each with its own unique advantages and disadvantages. Artificial Intelligence Marketing and Predicting Consumer Choice serves to integrate these widely disparate approaches, and show the strengths, weaknesses, and best applications of each. It provides a bridge between the person who must apply or learn these problem-solving methods and the community of experts who do the actual analysis. It is also a practical and accessible guide to the many remarkable advances that have been recently made in this fascinating field. Online resources include bonus chapters on AI, ensembles and neural nets, and finishing experiments, plus single and multiple product simulators.

Predictive Analytics For Dummies

Author: Dr. Anasse Bari,Mohamed Chaouchi,Tommy Jung

Publisher: John Wiley & Sons

ISBN: 1119267013

Category: Business & Economics

Page: 456

View: 6684

Use Big Data and technology to uncover real-world insights You don't need a time machine to predict the future. All it takes is a little knowledge and know-how, and Predictive Analytics For Dummies gets you there fast. With the help of this friendly guide, you'll discover the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data. In no time, you'll learn how to incorporate algorithms through data models, identify similarities and relationships in your data, and predict the future through data classification. Along the way, you'll develop a roadmap by preparing your data, creating goals, processing your data, and building a predictive model that will get you stakeholder buy-in. Big Data has taken the marketplace by storm, and companies are seeking qualified talent to quickly fill positions to analyze the massive amount of data that are being collected each day. If you want to get in on the action and either learn or deepen your understanding of how to use predictive analytics to find real relationships between what you know and what you want to know, everything you need is a page away! Offers common use cases to help you get started Covers details on modeling, k-means clustering, and more Includes information on structuring your data Provides tips on outlining business goals and approaches The future starts today with the help of Predictive Analytics For Dummies.

Virtual & Augmented Reality For Dummies

Author: Paul Mealy

Publisher: John Wiley & Sons

ISBN: 1119481422

Category: Computers

Page: 352

View: 9327

An easy-to-understand primer on Virtual Reality and Augmented Reality Virtual Reality (VR) and Augmented Reality (AR) are driving the next technological revolution. If you want to get in on the action, this book helps you understand what these technologies are, their history, how they’re being used, and how they’ll affect consumers both personally and professionally in the very near future. With VR and AR poised to become mainstream within the next few years, an accessible book to bring users up to speed on the subject is sorely needed—and that’s where this handy reference comes in! Rather than focusing on a specific piece of hardware (HTC Vive, Oculus Rift, iOS ARKit) or software (Unity, Unreal Engine), Virtual & Augmented Reality For Dummies offers a broad look at both VR and AR, giving you a bird’s eye view of what you can expect as they continue to take the world by storm. * Keeps you up-to-date on the pulse of this fast-changing technology * Explores the many ways AR/VR are being used in fields such as healthcare, education, and entertainment * Includes interviews with designers, developers, and technologists currently working in the fields of VR and AR Perfect for both potential content creators and content consumers, this book will change the way you approach and contribute to these emerging technologies.

The Revenue Acceleration Rules

Supercharge Sales and Marketing Through Artificial Intelligence, Predictive Technologies and Account-Based Strategies

Author: Shashi Upadhyay,Kent McCormick

Publisher: John Wiley & Sons

ISBN: 1119372070

Category: Business & Economics

Page: 192

View: 4201

Turn data into revenue in the B2B marketing sphere The Revenue Acceleration Rules is a unique guide in the business-to-business space, providing a clear framework for more effective marketing in an accounts-based environment. Written by a veteran in the predictive marketing sphere, this book explains how strategies typically used on the consumer end can be tailored to drive revenue in B2B sales. Industry experts offer advice and best practices, using real-world examples to illustrate the power of analytics and on-the-ground implementation of predictive ABM initiatives. Covering the complete spectrum from "why?" to "how?", this book provides an invaluable resource for B2B marketers seeking a step forward in the rapidly-evolving marketplace. Business-to-business sales makes up roughly 45 percent of the economy, and the power of predictive marketing has been proven time and again in the consumer sphere. This guide is the only resource to merge these two critical forces and provide clear guidance for the B2B space. Supercharge your demand waterfall Align marketing and sales Learn best practices from industry experts Grow revenue with account-based marketing Predictive marketing reveals the small clues that speak to big trends. While B2B diverges from consumer marketing in a number of ways, the central demand for value remains; analytics helps you stay ahead of the curve, streamline the marketing to sales funnel, and increase ROI. Strengthen the relationships you already have, attract new accounts, and prioritize accurately to turn contacts into leads, and leads into customers. Your data can be your biggest marketing asset, and The Revenue Acceleration Rules shows you how to leverage it into revenue.

Data-Driven Marketing

The 15 Metrics Everyone in Marketing Should Know

Author: Mark Jeffery

Publisher: John Wiley & Sons

ISBN: 0470504544

Category: Business & Economics

Page: 298

View: 2777

Praise for Data-Driven Marketing "To paraphrase the old adage: 'Half of marketing dollars are effective, we just don't know which half!' This book changes the marketing game so you'll really know what's working and what's not. The 15 metrics, along with the case examples, are an authoritative toolkit for making better decisions to create new markets, drive revenue, increase customer satisfaction, and improve profitability." —John M. Boushy, former CEO, Ameristar Casinos, Inc. "A groundbreaking combination of research, frameworks, and pragmatic advice for both controlling and radically improving marketing. A must-read for the entire marketing organization, from the CMO to the front lines." —Barry Judge, Executive Vice President and Chief Marketing Officer, Best Buy "Business-to-consumer marketing and business-to-business marketing are very different. Through detailed examples, this outstanding book shows how to apply data-driven marketing in both worlds for real results. This book is for anyone in business, not just marketing, who wants to step up the performance of their marketing." —David G. Bills, Senior Vice President and Chief Marketing and Sales Officer, DuPont "Every year, baseball teams go to places like Florida and Arizona to run through the basics which are the cornerstone of performance excellence. This book is the marketing equivalent of taking all those ground balls. An essential read for every marketer who cares about—and wants to improve upon—the science of their craft." —Derek Ungless, Executive Vice President and Chief Marketing Officer, DSW Shoe Warehouse

Marketing Analytics

Data-Driven Techniques with Microsoft Excel

Author: Wayne L. Winston

Publisher: John Wiley & Sons

ISBN: 1118417305

Category: Computers

Page: 720

View: 5777

Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data. This expert book offers the perfect solution. Written by data analysis expert Wayne L. Winston, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results. Practical exercises in each chapter help you apply and reinforce techniques as you learn. Shows you how to perform sophisticated business analyses using the cost-effective and widely available Microsoft Excel instead of expensive, proprietary analytical tools Reveals how to target and retain profitable customers and avoid high-risk customers Helps you forecast sales and improve response rates for marketing campaigns Explores how to optimize price points for products and services, optimize store layouts, and improve online advertising Covers social media, viral marketing, and how to exploit both effectively Improve your marketing results with Microsoft Excel and the invaluable techniques and ideas in Marketing Analytics: Data-Driven Techniques with Microsoft Excel.

Learning Predictive Analytics with Python

Author: Ashish Kumar

Publisher: Packt Publishing Ltd

ISBN: 1783983272

Category: Computers

Page: 354

View: 1327

Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python About This Book A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Get to grips with the basics of Predictive Analytics with Python Learn how to use the popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Who This Book Is For If you wish to learn how to implement Predictive Analytics algorithms using Python libraries, then this is the book for you. If you are familiar with coding in Python (or some other programming/statistical/scripting language) but have never used or read about Predictive Analytics algorithms, this book will also help you. The book will be beneficial to and can be read by any Data Science enthusiasts. Some familiarity with Python will be useful to get the most out of this book, but it is certainly not a prerequisite. What You Will Learn Understand the statistical and mathematical concepts behind Predictive Analytics algorithms and implement Predictive Analytics algorithms using Python libraries Analyze the result parameters arising from the implementation of Predictive Analytics algorithms Write Python modules/functions from scratch to execute segments or the whole of these algorithms Recognize and mitigate various contingencies and issues related to the implementation of Predictive Analytics algorithms Get to know various methods of importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and numpy Create dummy datasets and simple mathematical simulations using the Python numpy and pandas libraries Understand the best practices while handling datasets in Python and creating predictive models out of them In Detail Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form - It needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Learning to predict who would win, lose, buy, lie, or die with Python is an indispensable skill set to have in this data age. This book is your guide to getting started with Predictive Analytics using Python. You will see how to process data and make predictive models from it. We balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and numpy. You'll start by getting an understanding of the basics of predictive modeling, then you will see how to cleanse your data of impurities and get it ready it for predictive modeling. You will also learn more about the best predictive modeling algorithms such as Linear Regression, Decision Trees, and Logistic Regression. Finally, you will see the best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. Style and approach All the concepts in this book been explained and illustrated using a dataset, and in a step-by-step manner. The Python code snippet to implement a method or concept is followed by the output, such as charts, dataset heads, pictures, and so on. The statistical concepts are explained in detail wherever required.

Advanced Customer Analytics

Targeting, Valuing, Segmenting and Loyalty Techniques

Author: Mike Grigsby

Publisher: Kogan Page Publishers

ISBN: 0749477164

Category: Business & Economics

Page: 264

View: 340

Advanced Customer Analytics provides a clear guide to the specific analytical challenges faced by the retail sector. The book covers the nature and scale of data obtained in transactions, relative proximity to the consumer and the need to monitor customer behaviour across multiple channels. The book advocates a category management approach, taking into account the need to understand the consumer mindset through elasticity modelling and discount strategies, as well as targeted marketing and loyalty design. A practical, no-nonsense approach to complex scenarios is taken throughout, breaking down tasks into easily digestible steps. The use of a fictional retail analyst 'Scott' helps to provide accessible examples of practice. Advanced Customer Analytics does not skirt around the complexities of this subject but offers conceptual support to steer retail marketers towards making the right choices for analysing their data.

The End of Advertising

Why it Had to Die, and the Creative Resurrection to Come

Author: Andrew Essex

Publisher: N.A

ISBN: 0399588515

Category: Business & Economics

Page: 240

View: 8324

"One of the most successful admen of recent years throws down the ultimate challenge to his profession: innovate or perish. The ad apocalypse is upon us. Today millions are downloading ad-blocking software, and still more are paying subscription premiums to avoid ads. This $600 billion industry is now careening toward outright extinction, after having taken for granted a captive audience for too long, leading to lazy, overabundant, and frankly annoying ads. Make no mistake, Madison Avenue: Advertising as we know it is over. In this short, bound-to-be controversial manifesto, Essex offers both a wake-up call and a road map to the future. With trenchant wit and razor-sharp insights, he presents an essential new vision of where the smart businesses could be headed, to the cheers of advertisers and consumers alike"--

Cutting-edge Marketing Analytics

Real World Cases and Data Sets for Hands on Learning

Author: Rajkumar Venkatesan,Paul Farris,Ronald T. Wilcox

Publisher: Pearson Education

ISBN: 0133552527

Category: Business & Economics

Page: 300

View: 894

Master practical strategic marketing analysis through real-life case studies and hands-on examples. In Cutting Edge Marketing Analytics, three pioneering experts integrate all three core areas of marketing analytics: statistical analysis, experiments, and managerial intuition. They fully detail a best-practice marketing analytics methodology, augmenting it with case studies that illustrate the quantitative and data analysis tools you'll need to allocate resources, define optimal marketing mixes; perform effective analysis of customers and digital marketing campaigns, and create high-value dashboards and metrics. For each marketing problem, the authors help you: Identify the right data and analytics techniques Conduct the analysis and obtain insights from it Outline what-if scenarios and define optimal solutions Connect your insights to strategic decision-making Each chapter contains technical notes, statistical knowledge, case studies, and real data you can use to perform the analysis yourself. As you proceed, you'll gain an in-depth understanding of: The real value of marketing analytics How to integrate quantitative analysis with managerial sensibility How to apply linear regression, logistic regression, cluster analysis, and Anova models The crucial role of careful experimental design For all marketing professionals specializing in marketing analytics and/or business intelligence; and for students and faculty in all graduate-level business courses covering Marketing Analytics, Marketing Effectiveness, or Marketing Metrics

The Power of Cognitive Marketing: IBM Watson Marketing Insights

Author: Theresa Morelli,Colin Linsky,IBM Redbooks

Publisher: IBM Redbooks

ISBN: 0738456047

Category: Computers

Page: 22

View: 3056

How do you keep the pulse of your customers today? Customers are leaving more clues than ever on what they want and need. However, the ability to get a singular view, observe trends and changes in behavior, and then respond proactively is not as simple as it seems. It can often feel like shooting at a moving target. IBM® Watson Marketing Insights provides marketing analysts with a dynamic view of customer behavior and the power of predictive insights without requiring analytics skills. Presented in an interactive visual format, marketers receive a daily feed of insights and prioritized recommendations that allow them to quickly and easily identify the most impactful areas for targeted marketing outreach. This IBM RedguideTM publication introduces the IBM Watson Marketing Insights solution and highlights the business value of the solution. It provides a high-level architecture and identifies key components of the architecture.

Practical Predictive Analytics

Author: Ralph Winters

Publisher: Packt Publishing Ltd

ISBN: 1785880462

Category: Computers

Page: 576

View: 7147

Make sense of your data and predict the unpredictable About This Book A unique book that centers around develop six key practical skills needed to develop and implement predictive analytics Apply the principles and techniques of predictive analytics to effectively interpret big data Solve real-world analytical problems with the help of practical case studies and real-world scenarios taken from the world of healthcare, marketing, and other business domains Who This Book Is For This book is for those with a mathematical/statistics background who wish to understand the concepts, techniques, and implementation of predictive analytics to resolve complex analytical issues. Basic familiarity with a programming language of R is expected. What You Will Learn Master the core predictive analytics algorithm which are used today in business Learn to implement the six steps for a successful analytics project Classify the right algorithm for your requirements Use and apply predictive analytics to research problems in healthcare Implement predictive analytics to retain and acquire your customers Use text mining to understand unstructured data Develop models on your own PC or in Spark/Hadoop environments Implement predictive analytics products for customers In Detail This is the go-to book for anyone interested in the steps needed to develop predictive analytics solutions with examples from the world of marketing, healthcare, and retail. We'll get started with a brief history of predictive analytics and learn about different roles and functions people play within a predictive analytics project. Then, we will learn about various ways of installing R along with their pros and cons, combined with a step-by-step installation of RStudio, and a description of the best practices for organizing your projects. On completing the installation, we will begin to acquire the skills necessary to input, clean, and prepare your data for modeling. We will learn the six specific steps needed to implement and successfully deploy a predictive model starting from asking the right questions through model development and ending with deploying your predictive model into production. We will learn why collaboration is important and how agile iterative modeling cycles can increase your chances of developing and deploying the best successful model. We will continue your journey in the cloud by extending your skill set by learning about Databricks and SparkR, which allow you to develop predictive models on vast gigabytes of data. Style and Approach This book takes a practical hands-on approach wherein the algorithms will be explained with the help of real-world use cases. It is written in a well-researched academic style which is a great mix of theoretical and practical information. Code examples are supplied for both theoretical concepts as well as for the case studies. Key references and summaries will be provided at the end of each chapter so that you can explore those topics on their own.