Marketing For Scientists

It's a tough time to be a scientist: universities are shuttering science departments, federal funding agencies are facing flat budgets, and many newspapers have dropped their science sections altogether. But according to Marc Kuchner, this antiscience climate doesn't have to equal a career death knell-it just means scientists have to be savvier about promoting their work and themselves. In Marketing for Scientists, he provides clear, detailed advice about how to land a good job, win funding, and shape the public debate. As an astrophysicist at NASA, Kuchner knows that "marketing" can seem like a superficial distraction, whether your daily work is searching for new planets or seeking a cure for cancer. In fact, he argues, it's a critical component of the modern scientific endeavor, not only advancing personal careers but also society's knowledge. Kuchner approaches marketing as a science in itself. He translates theories about human interaction and sense of self into methods for building relationships-one of the most critical skills in any profession. And he explains how to brand yourself effectively-how to get articles published, give compelling presentations, use social media like Facebook and Twitter, and impress potential employers and funders. Like any good scientist, Kuchner bases his conclusions on years of study and experimentation. In Marketing for Scientists, he distills the strategies needed to keep pace in a Web 2.0 world.

Marketing decisions often misfire when driven more by beliefs than by knowledge. This book will guide you on how to differentiate between the two and to think more clearly and correctly when making those decisions, thereby increasing organizational success. The author has based this book on the fields of epistemology—the study of how knowledge is created—and the philosophy of science— the study of what it means for a science to be called a science. The motivation behind the book is quite simple: Given that science is so successful, why shouldn’t marketers borrow thinking and reasoning skills from science and apply them to marketing? Indeed, why not? The book details the groundwork for learning how to apply scientific reasoning to the field of marketing, such as some basic and important definitions (“What is a belief?” “What is knowledge?”), and identifies barriers to scientific reasoning, giving an example from the Dow Chemical Company and just how Dow uses critical thinking and reasoning skills to make more effective marketing and business decisions. You’ll also learn some real “thinking tools” you will need to apply scientific reasoning to solving your marketing problems. It introduces topics relating to attributes versus constructs, the meaning of causation, the relationship between coherence and justified beliefs, the importance of logic to sound reasoning, and the avoidance of logical fallacies in making sound recommendations. The book concludes by giving you direction to further improve your ability to apply scientific reasoning to solving marketing problems.

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.

Applying for grants, bidding for project funding or helping to sell products are part of the day to day life of a research scientist. Drawing on experience at leading research institutes and companies, the authors of this book turned to best practice in marketing to make 'selling science' interesting and rewarding for scientists. The central thesis of the book is that effective marketing means planning for the impact of research, and this is a skill that every scientist can easily acquire. It sets out a structured approach, supported by tools, checklists and hints from experience so that delivering impact from research becomes 'just the way things are done around here'. Starting with gathering background information (in much the same way as preparing the introduction to a scientific paper), the book describes methods to analyse the data and to implement a communication plan. The book is a valuable resource for research scientists from any discipline, and for team leaders wanting to involve members of their team in developing their organization's strategy.

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.

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.