Marketing Analytics: A Practical Guide to Improving Consumer Insights Using Data Techniques, 3rd Edition
- Length: 256 pages
- Edition: 3
- Language: English
- Publisher: Kogan Page
- Publication Date: 2022-12-27
- ISBN-10: 1398608211
- ISBN-13: 9781398608214
- Sales Rank: #11990976 (See Top 100 Books)
Who is most likely to buy and what is the best way to target them? How can I use both consumer analytics and modelling to improve the impact of marketing campaigns? Marketing Analytics takes you step-by-step through these areas and more.
Marketing Analytics enables you to leverage predictive techniques to measure and improve marketing performance. By exploring real-world marketing challenges, it provides clear, jargon-free explanations on how to apply different analytical models for each purpose. From targeted list creation and data segmentation, to testing campaign effectiveness, pricing structures and forecasting demand, it offers a complete resource for how statistics, consumer analytics and modelling can be put to optimal use.
This revised and updated third edition of Marketing Analyticscontains new material on forecasting, customer touchpoints modelling, and a new focus on customer loyalty. With accessible language throughout, methodologies are simplified to ensure the more complex aspects of data and analytics are fully accessible for any level of application. Supported by a glossary of key terms and supporting resources consisting of datasets, presentation slides for each chapter and a test bank of self-test question, this book supplies a concrete foundation for optimizing marketing analytics for day-to-day business advantage.
Cover Endorsements Titlepage Contents List of Figures List of Tables Introduction Who is the intended audience for this book? What is marketing science? Why is marketing science important? What kind of people in what jobs use marketing science? Why do I think I have something to say about marketing science? What is the approach/philosophy of this book? The practical focus of this book Part One How can marketing analytics help you? 1 Overview of statistics Measures of central tendency Measures of dispersion The normal distribution Confidence intervals Relations among two variables: covariance and correlation Probability and the sampling distribution Conclusion Checklist: You’ll be the smartest person in the room if you… 2 Consumer behaviour and marketing strategy Introduction Consumer behaviour as the basis for marketing strategy Overview of consumer behaviour Overview of marketing strategy Conclusion Checklist: You’ll be the smartest person in the room if you... 3 What is an insight? Introduction Insights tend not to be used by executives Is this an insight? So, what is an insight? Ultimately, an insight is about action-ability Checklist: You’ll be the smartest person in the room if you... Part Two Dependent variable techniques 4 Modelling demand and elasticity Introduction Dependent equation type vs interrelationship type statistics Deterministic vs probabilistic equations Business case Results applied to business case Modelling elasticity Technical notes Highlight: Segmentation and elasticity modelling can maximize revenue in a retail/medical clinic chain: field test results Abstract The problem and some background Description of the dataset First: segmentation Then: elasticity modelling Last: test vs control Discussion Conclusion: why is elasticity modelling so rarely done? Checklist: You’ll be the smartest person in the room if you… 5 Polynomial distributed lags What is PDL? An example Business case Conclusion Checklist: You’ll be the smartest person in the room if you… 6 Using Poisson regression When to use Poisson regression Technical note Business case Conclusion Checklist: You’ll be the smartest person in the room if you… 7 Logistic regression and market basket analysis Introduction Conceptual notes Business case Results applied to the model Lift charts How deep to mail Using the model – collinearity overview Variable diagnostics Highlight: Using logistic regression for market basket analysis Abstract What is a market basket? How is it usually done? Logistic regression How to estimate/predict the market basket An example Conclusion Checklist: You’ll be the smartest person in the room if you… 8 Survival modelling and lifetime value Introduction Conceptual overview of survival analysis Business case More about survival analysis Model output and interpretation Note: The only way to do churn modelling Conclusion Highlight: Lifetime value: how predictive analysis is superior to descriptive analysis Abstract Descriptive analysis Predictive analysis An example Checklist: You’ll be the smartest person in the room if you… 9 Panel regression and same store sales Introduction What is panel regression? Panel regression: details Business case Insights about marcom (direct mail, email and SMS) Insights about time period (quarters) Insights about cross-sections (counties) Brief note on modelling same store sales Conclusion Checklist: You’ll be the smartest person in the room if you… 10 Introduction to forecasting Overview Forecasting demand Autocorrelation Dummy variables and seasonality Business case Conclusion Checklist: You’ll be the smartest person in the room if you… Part Three Interrelationship techniques 11 Simultaneous equations Introduction What are simultaneous equations? Why go to the trouble of using simultaneous equations? Desirable properties of estimators Business case Conclusion Checklist: You’ll be the smartest person in the room if you… 12 Principal components and factor analysis Interrelationship techniques What is factor analysis? What is PCA? Similarities between PCA and factor analysis Differences between PCA and factor analysis Conclusion Checklist: You’ll be the smartest person in the room if you… 13 Segmentation overview Introduction Introduction to segmentation What is segmentation? What is a segment? Why segment? Strategic uses of segmentation The four Ps of strategic marketing Criteria for actionable segmentation A priori or not? Conceptual process Highlight: Using segmentation to improve both strategy and predictive modelling Introduction Segmentation is a strategic, not an analytic, process Why would segmentation improve predictive modelling accuracy? Segmenting variables for model improvement Example: churn modelling Interpretation and insights What if there was no segmentation? Conclusion Checklist: You’ll be the smartest person in the room if you… 14 Tools of segmentation Overview Metrics of successful segmentation General analytic techniques Segmentation techniques summary Business case Analytics Profile and output Comments/details on individual segments K-means compared to LCA Highlight: Why go beyond RFM? Abstract What is RFM? What is behavioural segmentation? What does behavioural segmentation provide that RFM does not? Conclusion Checklist: You’ll be the smartest person in the room if you… Part Four Focus on media and loyalty 15 Modelling marcom value Introduction Value of marcom model Business case Checklist: You’ll be the smartest person in the room if you… 16 Media mix modelling Overview of MMM Adstock models Single equation and PDLs Simultaneous equations Business case Conclusion Checklist: You’ll be the smartest person in the room if you… 17 Overview of loyalty Introduction to loyalty Is there a range or spectrum of loyalty? What are the three Rs of loyalty? Why design a programme with earn–burn measures? Business case A note on programme valuation Conclusion Checklist: You’ll be the smartest person in the room if you… 18 Loyalty with SEM Structural equation modelling (SEM) Business case Conclusion Checklist: You’ll be the smartest person in the room if you… 19 The customer loyalty journey Introduction Background Segmentation Elasticity modelling Simultaneous equations The experiences questionnaire Conclusion Checklist: You’ll be the smartest person in the room if you… Part Five More important topics for everyday marketing 20 Statistical testing Everyone wants to test Sample size equation: use the lift measure A/B testing and full factorial differences Business case Checklist: You’ll be the smartest person in the room if you… 21 Introduction to Big Data Introduction What is Big Data? Is Big Data important? What does it mean for analytics? For strategy? So what? Surviving the Big Data panic Big Data analytics Big Data – exotic algorithms Conclusion Checklist: You’ll be the smartest person in the room if you… Conclusion: The finale What things have I learnt that I’d like to pass on to you? Anecdote #1 References Further reading Index Copyright
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