Marketing Analytics

Marketing Analytics arms business analysts and marketers with the marketing science understanding and techniques they need to solve real-world marketing problems, from pulling a targeted list and segmenting data to testing campaign effectiveness and forecasting demand. Assuming no prior knowledge, this book outlines everything practitioners need to 'do' marketing science and demonstrate value to their organization. It introduces concepts relating to statistics, marketing strategy and consumer behaviour and then works through a series of marketing problems in a straightforward, jargon-free way. It demonstrates solutions for various data modelling scenarios and includes full workings and critical analyses to reinforce the key concepts. By starting with the marketing problem and then sharing a series of data modelling options on how to solve it, Marketing Analytics both makes marketing science accessible for beginners and aids the more seasoned practitioner in getting to grips with the trickier technical aspects of data analytics to refine their marketing skills and toolkit and compete more effectively in the marketplace. Online supporting resources for this book include a bank of test questions as well as data sets relating to a number of chapters. About the series: The Marketing Science series makes difficult topics accessible to marketing students and practitioners by grounding them in business reality. Each book is written by an expert in the field and includes case studies and illustrations enabling marketers to gain confidence in applying the tools and techniques and in commissioning external research. "For those MBAs who barely passed their quantitative marketing and statistics classes without truly understanding the content, "Marketing Analytics" provides everything managers and executives need to know presented as a conversation with examples to boot! You'll definitely sound smarter in the boardroom after reading this book!"--James Mourey, PhD and Assistant Professor of Marketing "DePaul University "Section - Part One: Overview; Chapter - 1: Introduction; Chapter - 2: A Brief Review of Statistics; Chapter - 3: A Brief Review of Consumer Behavior and Marketing Strategy; Section - Part Two: Dependent Variable Techniques; Chapter - 4: Modeling - Dependent Variable Techniques with One Equation; Chapter - 5: What are Things That Drive Demand?; Chapter - 6: Modeling Elasticity; Section - a: Highlight: Segmentation and Elasticity Modeling Can Maximize Revenue in a Veterinarian Clinic Chain: Field Test Results; Chapter - 7: Who is Most Likely to Buy and How do I Target?; Chapter - 8: Lift Charts and Direct Marketing; Section - a: Hightlight: Predictive Lifetime Value is Superior to Descriptive Lifetime Value; Chapter - 9: Modeling - Dependent Variable Techniques with < One Equation; Chapter - 10: How Does Price (or Other Stimuli) Affect Brands (or Products)?; Section - Part Three: Inter-Relationship Techniques; Chapter - 11: Modeling - Inter-Relationship Techniques; Chapter - 12: What Does My Market Look Like?; Chapter - 13: Segmentation Tools and Techniques; Section - a: Highlight: Why go Beyond RFM?; Section - Part Four: Other; Chapter - 14: Marketing Research; Chapter - 15: Questionnaire Design; Chapter - 16: Missing Value Imputation; Chapter - 17: Brief Mention of Conjoint; Chapter - 18: Structural Equation Modeling; Chapter - 19: Testing; Chapter - 20: How Do I Know What Works?; Chapter - 21: An Alternative to Traditional Testing; Section - Part Five: Capstone; Chapter - 22: Capstone: Applying to Digital Analysis; Chapter - 23: Modeling Engagement; Chapter - 24: Modeling Social Media's Impact on Two Different Channels; Section - Part Six: Conclusion; Chapter - 25: Conclusion;