Machine Learning For Marketing

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Machine Learning For Marketing

Author : Hiroshi Mamitsuka
ISBN : 4991044529
Genre : Business & Economics
File Size : 27.17 MB
Format : PDF, Kindle
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Machine learning, now a central part of artificial intelligence, would be a driving force to change the current world to a more autonomous society. This impact of machine learning appears in many fields, for example, science, engineering, finance, agriculture, to name a few. Marketing is rather behind this trend, while marketing has a lot of potential applications for machine learning. In other words, marketing may change into more autonomous scientific work by using data and also proper formulation of each application into a machine learning problem. This book focuses on two major, traditional paradigms of marketing: target marketing and relationship marketing. Then it is revealed that each of numerous aspects of the two marketing paradigms can be formulated into a machine learning problem. That is, for each problem, a machine learning model can be built and parameters of the model can be estimated/optimized from given data. For example, an important objective of target marketing can be interpreted as a problem of finding a customer segment, which has a plenty of customers but no competitors. This problem can be formulated into a machine learning problem for which a model is built and model parameters can be estimated from given data. This book, for each machine learning problem setting, always builds a simpler (probably simplest) model, so that readers can understand the idea and assumption of the model easily. This book would be useful for both sides of marketing and machine learning. That is, marketers would be able to study the way of formulating a problem of marketing into a machine learning problem/function in which parameters are estimated from given data. On the other hand, machine learners would be able to study applications of marketing and also essential and intuitive ideas behind marketing through numerous applications in this book.
Category: Business & Economics

The Intuition Behind The Application Of Machine Learning In Marketing Analytics

Author : Mario a Vinasco
ISBN : 1082108219
Genre :
File Size : 85.1 MB
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Artificial Intelligence (AI) has gained tremendous fame and attention during the past 5 years; there are plenty of books, conferences and online resources, and it has become overwhelming and difficult to separate the hype from practical insights.On one side, the math behind AI can be hard to follow; on the other, the hysteria claims that AI can flip presidential elections and feed other conspiracy theories.This book presents the key insights that make AI/ML useful for marketing and demystifies the core technology and illustrates case studies where my team applied the technology.This book is for marketers and executives that want to gain insights about the use and applicability of AI in marketing and I present a simple yet non-trivial explanation of the core principles of AI.I started using machine learning (ML) models at scale in 2012 and have continued doing so. We have used ML models to help the analysis of experiments, identify cross sell opportunities, design attrition prevention initiatives and many other interesting applications.As you have noted, I am not making a distinction between AI and ML, I even include many other iterative algorithms under the umbrella of AI. The book is not a description of state-of-the-art AI, it is an end user's guide to understand its potential.I will refer to my experience during my work in the marketing analytics groups of Facebook and Uber Technologies from the years 2013 to 2019 (present).
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Artificial Intelligence For Marketing

Author : Jim Sterne
ISBN : 9781119406334
Genre : Business & Economics
File Size : 44.79 MB
Format : PDF, ePub
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A straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals. This book will not teach you to be a data scientist—but it does explain how Artificial Intelligence and Machine Learning will revolutionize your company's marketing strategy, and teach you how to use it most effectively. Data and analytics have become table stakes in modern marketing, but the field is ever-evolving with data scientists continually developing new algorithms—where does that leave you? How can marketers use the latest data science developments to their advantage? This book walks you through the "need-to-know" aspects of Artificial Intelligence, including natural language processing, speech recognition, and the power of Machine Learning to show you how to make the most of this technology in a practical, tactical way. Simple illustrations clarify complex concepts, and case studies show how real-world companies are taking the next leap forward. Straightforward, pragmatic, and with no math required, this book will help you: Speak intelligently about Artificial Intelligence and its advantages in marketing Understand how marketers without a Data Science degree can make use of machine learning technology Collaborate with data scientists as a subject matter expert to help develop focused-use applications Help your company gain a competitive advantage by leveraging leading-edge technology in marketing Marketing and data science are two fast-moving, turbulent spheres that often intersect; that intersection is where marketing professionals pick up the tools and methods to move their company forward. Artificial Intelligence and Machine Learning provide a data-driven basis for more robust and intensely-targeted marketing strategies—and companies that effectively utilize these latest tools will reap the benefit in the marketplace. Artificial Intelligence for Marketing provides a nontechnical crash course to help you stay ahead of the curve.
Category: Business & Economics

Machine Learning And Artificial Intelligence In Marketing And Sales

Author : Niladri Syam
ISBN : 9781800438804
Genre : Business & Economics
File Size : 56.9 MB
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Machine Learning and Artificial Intelligence in Marketing and Sales explores the ideas, and the statistical and mathematical concepts, behind Artificial Intelligence (AI) and machine learning models, as applied to marketing and sales, without getting lost in the details of mathematical derivations and computer programming.
Category: Business & Economics

Hands On Data Science For Marketing

Author : Yoon Hyup Hwang
ISBN : 9781789348828
Genre : Computers
File Size : 58.31 MB
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Optimize your marketing strategies through analytics and machine learning Key Features Understand how data science drives successful marketing campaigns Use machine learning for better customer engagement, retention, and product recommendations Extract insights from your data to optimize marketing strategies and increase profitability Book 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 learn Learn how to compute and visualize marketing KPIs in Python and R Master what drives successful marketing campaigns with data science Use machine learning to predict customer engagement and lifetime value Make product recommendations that customers are most likely to buy Learn how to use A/B testing for better marketing decision making Implement machine learning to understand different customer segments Who 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.
Category: Computers

Handbook Of The Economics Of Marketing

Author :
ISBN : 9780444637598
Genre : Business & Economics
File Size : 26.17 MB
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Handbook of the Economics of Marketing, Volume One: Marketing and Economics mixes empirical work in industrial organization with quantitative marketing tools, presenting tactics that help researchers tackle problems with a balance of intuition and skepticism. It offers critical perspectives on theoretical work within economics, delivering a comprehensive, critical, up-to-date, and accessible review of the field that has always been missing. This literature summary of research at the intersection of economics and marketing is written by, and for, economists, and the book's authors share a belief in analytical and integrated approaches to marketing, emphasizing data-driven, result-oriented, pragmatic strategies. Helps academic and non-academic economists understand recent, rapid changes in the economics of marketing Designed for economists already convinced of the benefits of applying economics tools to marketing Written for those who wish to become quickly acquainted with the integration of marketing and economics
Category: Business & Economics

Ai For Marketing And Product Innovation

Author : A. K. Pradeep
ISBN : 9781119484066
Genre : Business & Economics
File Size : 72.35 MB
Format : PDF, Kindle
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Get on board the next massive marketing revolution AI for Marketing and Product Innovation offers creatives and marketing professionals a non-tech guide to artificial intelligence (AI) and machine learning (ML)—twin technologies that stand poised to revolutionize the way we sell. The future is here, and we are in the thick of it; AI and ML are already in our lives every day, whether we know it or not. The technology continues to evolve and grow, but the capabilities that make these tools world-changing for marketers are already here—whether we use them or not. This book helps you lean into the curve and take advantage of AI’s unparalleled and rapidly expanding power. More than a simple primer on the technology, this book goes beyond the “what” to show you the “how”: How do we use AI and ML in ways that speak to the human spirit? How to we translate cold technological innovation into creative tools that forge deep human connections? Written by a team of experts at the intersection of neuroscience, technology, and marketing, this book shows you the ins and outs of these groundbreaking technological tools. Understand AI and ML technology in layman’s terms Harness the twin technologies unparalleled power to transform marketing Learn which skills and resources you need to use AI and ML effectively Employ AI and ML in ways that resonate meaningfully with customers Learn practical examples of how to reinvest product innovation, brand building, targeted marketing and media measurement to connect with people and enhance ROI Discover the true impact of AI and ML from real-world examples, and learn the thinking, best practices, and metrics you need to capture this lightning and take the next massive leap in the evolution of customer connection. AI for Marketing and Product Innovation shows you everything you need to know to get on board.
Category: Business & Economics

Artificial Intelligence In Digital Marketing

Author : , empreender
ISBN : 9781526028617
Genre : Business & Economics
File Size : 78.34 MB
Format : PDF
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Being smart in business means knowing what’s just around the corner. It means thinking ahead and preparing for inevitable changes that will impact the way business is conducted.This is what allows a business to be resilient and to thrive in a changing environment.Digital marketing is no different.It’s affecting the way that SEO works, the tools and software we use, and the way that ads are displayed.As digital marketers, that means thinking about things that could impact on the face of marketing.Artificial Intelligence (AI) and machine learning have the potential to completely change the face of internet marketing, rendering many older strategies obsolete even.
Category: Business & Economics

Handbook Of Marketing Analytics

Author : Natalie Mizik
ISBN : 9781784716752
Genre :
File Size : 36.5 MB
Format : PDF
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Marketing Science contributes significantly to the development and validation of analytical tools with a wide range of applications in business, public policy and litigation support. The Handbook of Marketing Analytics showcases the analytical methods used in marketing and their high-impact real-life applications. Fourteen chapters provide an overview of specific marketing analytic methods in some technical detail and 22 case studies present thorough examples of the use of each method in marketing management, public policy, and litigation support. All contributing authors are recognized authorities in their area of specialty.
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Machine Learning Based Approaches For Learning Marketing Strategies

Author : Yu San Lin
ISBN : OCLC:1083971983
Genre :
File Size : 60.83 MB
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Studying the markets for better business strategies has been a pressing and practical issue. However, there is not enough attention paid into such research field when it comes to precise computational models. In this thesis, I looked into various marketing problems via approaches including data analysis, probabilistic generative models, and neural network models. The specific research problems I looked into includes (1) analyzing the rewards on crowdfunding platforms and how they correlate with crowdfunding project success, (2) learning the offering and bundling preferences of menu bundles in crowdfunding projects, (3) modeling the market competition and capturing the businesses' competitiveness, and (4) learning the word embedding that carries both the underlying semantic meaning and economic worths. We approach each of these research problems as follows.In the first paper, Analysis of Rewards on Reward-Based Crowdfunding Platforms, we analyze a Kickstarter dataset, which consists of approximately 3K projects and 30K rewards. The analysis employs various statistical methods, including Pearson correlation tests, Kolmogorov-Smirnow test and Kaplan-Meier estimation, to study the relationships between various reward characteristics and project success. We find that projects with more rewards, with limited and late-added rewards are more likely to succeed. We also categorize and automatically annotate rewards into fifteen reward item types. We further analyze how different types of reward items are adopted across various categories of projects as well as how they potentially affect project success. We discover that projects with include the previous rewards are most likely to succeed. Also, different categories of projects may employ different best strategies of adopting reward item types to achieve pledging goals. Finally, we verify the efficacy of reward-related information through predicting project success. The result shows that features extracted from rewards help better predict the successes of crowdfunding projects.In the second paper, Modeling Menu Bundle Designs of Crowdfunding Projects, we raise a novel research question: understanding project creators' decisions of reward designs to level their chance to succeed. We approach this by modeling the design behavior of project creators, and identifying the behaviors that lead to project success. We propose a probabilistic generative model, Menu-Offering-Bundle (MOB) model, to capture the offering and bundling decisions of project creators based on collected data of 14K crowdfunding projects and their 149K reward bundles across a half-year period. Our proposed model is shown to capture the offering and bundling topics, outperform the baselines in predicting reward designs. We also find that the learned offering and bundling topics carry distinguishable meanings and provide insights of key factors on project success.In our third paper, Modeling Dynamic Competition on Crowdfunding Markets, we study the competition on crowdfunding markets through data analysis, and propose a probabilistic generative model, Dynamic Market Competition (DMC) model, to capture the competitiveness of projects in crowdfunding. Through an empirical evaluation using the pledging history of past crowdfunding projects, our approach has shown to capture the competitiveness of projects very well, and significantly outperforms several baseline approaches in predicting the daily collected funds of crowdfunding projects, reducing errors by 31.73% to 45.14%. In addition, our analyses on the correlations between project competitiveness, project design factors, and project success indicate that highly competitive projects, while being winners under various setting of project design factors, are particularly impressive with high pledging goals and high price rewards, comparing to medium and low competitive projects. Finally, the competitiveness of projects learned by DMC is shown to be very useful in applications of predicting final success and days taken to hit pledging goal, reaching 85% accuracy and error of less than 7 days, respectively, with limited information at early pledging stage. In our fourth paper, Learning the Economic Worth of Words with Joint-Task Neural Network Model, we fill in this gap by proposing neural network models that learn a representation of words, which capture the underlying economic worths of words. The models also incorporate factors, e.g., the product's brand, and the restaurant's city, that may affect the aggregated economic values of an item through its textual description. We design an attention mechanism to further capture the different contribution of words at different positions in the sentences/phrases toward the aggregated economic value. Our models are shown to well predict not only the economic values when given the textual descriptions, but also the missing word when given other context words and the aggregated economic value. We design recommendation task to show that our models may serve as a great tool for word-choice recommendation system when a specific perceived economic value is targeted. In particular, in restaurant menu creation, our models recommend words to describe menu dishes that fit the desired perceived values.
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The Ai Marketing Canvas

Author : Raj Venkatesan
ISBN : 150361316X
Genre : Business & Economics
File Size : 30.61 MB
Format : PDF, ePub, Mobi
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This book offers a direct, actionable plan CMOs can use to map out initiatives that are properly sequenced and designed for success --regardless of where their marketing organization is in the process. The book is also a call to action for marketing leaders to confront and decide how they will address this critical pivot point in marketing. The authors pose to marketers the critical questions of (1) "How should modern Marketers be thinking about Artificial Intelligence and Machine Learning?" and (2) "How should Marketers be developing a strategy & plan to implement AI into their marketing toolkit?" Opening chapters provide marketing leaders with an overview of what exactly is AI, how is it different than traditional computer science approaches; then proposes a best practice 5 stage framework for how to implement what the authors term the "AI Marketing Canvas." This is based on research and interviews the authors did with leading Marketers, and offers many tangible examples of what brands are doing at each stage of the AI Marketing Canvas. By way of guidance, Venkatesan and Lecinski provide examples of brands currently, successfully, weaving AI into their marketing strategies, including Google, LYFT, Ancestry.com, and Coca-Cola. The book ends with a discussion of important implications for marketing leaders, for your team, people and culture. Strategically sound, application-focused, and customer-centric, this book fills a lacuna in actionable marketing strategy guidance at a time when it is most needed.
Category: Business & Economics

Ai For Marketers An Introduction And Primer

Author : Christopher Penn
ISBN : 1795675667
Genre :
File Size : 36.68 MB
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In this all-new, completely rewritten edition, you'll see the future of marketing as AI changes it forever. What's inside?- You'll explore what AI is and isn't- What questions marketers should be asking of vendors- The different types of machine learning- What great data is- 5 practical applications of AI for marketing- What it will take for you to succeed on your journey to AI-powered marketingPlus, discover who should and shouldn't pursue a career in AI and machine learning - and get a shortlist of valuable resources for getting started.
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