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Author: Dan Zarrella
Publisher: Wiley
ISBN: 9781118138274
Category : Business & Economics
Languages : en
Pages : 208
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Book Description
Scientific marketing research delivers proven marketing tactics and tips The Science of Marketing applies a scientific approach to the way businesses and brands approach marketing. It uses a combination of marketing, statistical, and psychological research to explain why and, more importantly, how, companies should adapt marketing strategies such as blogging, social media, email marketing, and webinars to achieve maximium results. The book contradicts what the author calls the "unicorns and rainbows" strategy that simply encourages companies to love their customers and hug their followers. Instead, the book offers more substantial, proven tactics and tips gathered through scientific research and techniques. Lists what time of day and what day of the week the most retweets occur Explains why weekends are best for Facebook sharing, which blog posts lead to comments, why early mornings are best for emails, and how to blog to acquire links Describes how to avoid crowding your content The Science of Marketing provides the research and tools to help you make a stronger impact in the digital marketing space.
Author: Dan Zarrella
Publisher: Wiley
ISBN: 9781118138274
Category : Business & Economics
Languages : en
Pages : 208
Get Book
Book Description
Scientific marketing research delivers proven marketing tactics and tips The Science of Marketing applies a scientific approach to the way businesses and brands approach marketing. It uses a combination of marketing, statistical, and psychological research to explain why and, more importantly, how, companies should adapt marketing strategies such as blogging, social media, email marketing, and webinars to achieve maximium results. The book contradicts what the author calls the "unicorns and rainbows" strategy that simply encourages companies to love their customers and hug their followers. Instead, the book offers more substantial, proven tactics and tips gathered through scientific research and techniques. Lists what time of day and what day of the week the most retweets occur Explains why weekends are best for Facebook sharing, which blog posts lead to comments, why early mornings are best for emails, and how to blog to acquire links Describes how to avoid crowding your content The Science of Marketing provides the research and tools to help you make a stronger impact in the digital marketing space.
Author: Russell S Winer
Publisher: World Scientific
ISBN: 9814596493
Category : Business & Economics
Languages : en
Pages : 528
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Book Description
The field of marketing science has a rich history of modeling marketing phenomena using the disciplines of economics, statistics, operations research, and other related fields. Since it is roughly 50 years from its origins, The History of Marketing Science is a timely review of the accomplishments of marketing scientists in a number of research areas. Different research areas of marketing science, such as Pricing, Internet Marketing, Diffusion Models, and Advertising, are treated to a highly readable and easy-to-digest historical analysis by the contributing authors. Each chapter provides a chronological timeline of key historical developments in the area of marketing science covered. Readers of other disciplinary backgrounds outside of economics, statistics, and operations research will be more than able to appreciate the development of marketing science as a field of research and its pioneers through the book. Contents:The History of Marketing Science: Beginnings (Scott A Neslin and Russell S Winer)Methods:Brand Choice Models (Gary J Russell)Conjoint Analysis (Vithala R Rao)Innovation Diffusion (Eitan Muller)Econometric Models (Dominique M Hanssens)Market Structure Research (Steven M Shugan)Stochastic Models of Buyer Behavior (Peter S Fader, Bruce G S Hardie and Subrata Sen)Management:Advertising Effectiveness (Gerard J Tellis)Branding and Brand Equity Models (Tulin Edem and Joffre Swait)Distribution Channels (Richard Staelin and Eunkyu Lee)Customer Relationship Management (CRM) (Scott A Neslin)Digital and Internet Marketing (Wendy W Moe and David A Schweidel)New Products Research (Donald R Lehmann and Peter N Golder)Organizational Buying Behavior (Gary L Lilien)Pricing (Russell S Winer)Sales Force Productivity Models (Murali K Mantrala)Sales Promotions (Kusum L. Ailawadi and Sunil Gupta) Readership: Students of marketing science; researchers in the science of marketing; and general public interested in 50 years of marketing science history. Key Features:Provides a roadmap of the development of 16 areas of marketing science that is useful from a historical perspective and identifies the important gaps in the literature that can provide an impetus for future researchA great resource for the main consumers of the academic marketing research literature: doctoral students, faculty, and marketing science practitioners in consulting firms and companiesEmphasizes both the role and the importance that pioneers in marketing science have had in the rapid development of the field over the past 50 yearsKeywords:Marketing;Marketing Science;Marketing Models;Quantitative Analysis;History of Marketing
Author: George Schwartz
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 548
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Book Description
Author: Jimmy Vee
Publisher: John Wiley & Sons
ISBN: 1118045386
Category : Business & Economics
Languages : en
Pages : 287
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Book Description
If you’re an entrepreneur, business owner, or sales professional, Gravitational Marketing offers a simple method for attracting customers without the hassle of traditional manual sales labor. If you want to sell more and work less, this book exposes the principles of easily and effortlessly attracting customers without cold calling, prospecting, or begging for business. With Gravitational Marketing, you can finally stop chasing customers and let them come to you.
Author: Yoon Hyup Hwang
Publisher: Packt Publishing Ltd
ISBN: 178934882X
Category : Computers
Languages : en
Pages : 448
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Book Description
Optimize your marketing strategies through analytics and machine learning Key FeaturesUnderstand how data science drives successful marketing campaignsUse machine learning for better customer engagement, retention, and product recommendationsExtract insights from your data to optimize marketing strategies and increase profitabilityBook Description Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies. This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R. By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business. What you will learnLearn how to compute and visualize marketing KPIs in Python and RMaster what drives successful marketing campaigns with data scienceUse machine learning to predict customer engagement and lifetime valueMake product recommendations that customers are most likely to buyLearn how to use A/B testing for better marketing decision makingImplement machine learning to understand different customer segmentsWho this book is for If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! It will be beneficial to have some basic knowledge of either Python or R to work through the examples. This book will also be beneficial for beginners as it covers basic-to-advanced data science concepts and applications in marketing with real-life examples.
Author: Mirza Rahim Baig
Publisher: Packt Publishing Ltd
ISBN: 1800563884
Category : Computers
Languages : en
Pages : 637
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Book Description
Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily.
Author: Tommy Blanchard
Publisher: Packt Publishing Ltd
ISBN: 1789952107
Category : Computers
Languages : en
Pages : 420
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Book Description
Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key FeaturesStudy new techniques for marketing analyticsExplore uses of machine learning to power your marketing analysesWork through each stage of data analytics with the help of multiple examples and exercisesBook Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learnAnalyze and visualize data in Python using pandas and MatplotlibStudy clustering techniques, such as hierarchical and k-means clusteringCreate customer segments based on manipulated data Predict customer lifetime value using linear regressionUse classification algorithms to understand customer choiceOptimize classification algorithms to extract maximal informationWho this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.
Author: Grahame Robert Dowling
Publisher: Oxford University Press, USA
ISBN: 9780199269617
Category : Business & Economics
Languages : en
Pages : 476
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Book Description
The book blends the art of marketing (implementing programs to attain and retain customers) with the science of marketing (what we know from research about markets, customer behavior, etc.) to provide insight for marketing managers about how to implement marketing more effectively to both create and capture the value of the offers they make to their target customers. In the process, it questions the usefulness of some of the more recent marketing fads. Clearly written and presented the book is ideal for advanced and professional students of marketing as well as marketing professionals.
Author: D. Forbes
Publisher: Springer
ISBN: 1137502045
Category : Performing Arts
Languages : en
Pages : 254
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Book Description
In this groundbreaking book, author David Forbes explains human motivation and provides ways that marketers can effectively reach the consumer. The book uses decades of psychology research and the author's own tool, the Forbes Matrix that identifies, organizes, and explains the nine core motivations.
Author: Mike Grigsby
Publisher: Kogan Page Publishers
ISBN: 0749474181
Category : Business & Economics
Languages : en
Pages : 248
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Book Description
Who is most likely to buy and what is the best way to target them? Marketing Analytics enables marketers and business analysts to answer these questions by leveraging proven methodologies to measure and improve upon the effectiveness of marketing programs. Marketing Analytics demonstrates how statistics, analytics and modeling can be put to optimal use to increase the effectiveness of every day marketing activities, from targeted list creation and data segmentation to testing campaign effectiveness and forecasting demand. The author explores many common marketing challenges and demonstrates how to apply different data models to arrive at viable solutions. Business cases and critical analysis are included to illustrate and reinforce key concepts throughout. Beginners will benefit from clear, jargon-free explanations of methodologies relating to statistics, marketing strategy and consumer behaviour. More experienced practitioners will appreciate the more complex aspects of data analytics and data modeling, discovering new applications of various techniques in every day practice. Readers of Marketing Analytics will come away with a firm foundation in markets analytics and the tools they need to gain competitive edge and increase market share. Online supporting resources for this book include a bank of test questions as well as data sets relating to many of the chapters.
