Front Matter; Copyright; Contents; List of contributors; Overview of the chapters; Introduction; METHODS CHAPTERS; PART I EXPERIMENTAL DESIGNS; 1 Laboratory experimentation in marketing; 2 Field experiments; 3 Conjoint Analysis; PART II CLASSICAL ECONOMETRICS; 4 Time-series models of short-run and long-run marketing impact; 5 Panel data methods in marketing research; 6 Causal inference in marketing applications; PART III DISCRETE CHOICE MODELING; 7 Modeling choice processes in marketing; 8 Bayesian econometrics; 9 Structural models in marketing; PART IV LATENT STRUCTURE ANALYSIS 10 Multivariate statistical analyses: cluster analysis, factor analysis, and multidimensional scalingPART V MACHINE LEARNING AND BIG DATA; 11 Machine learning and marketing; 12 Big data analytics; PART VI GENERALIZATIONS AND OPTIMIZATIONS; 13 Meta analysis in marketing; 14 Marketing optimization methods; CASE STUDIES AND APPLICATIONS; PART VII CASE STUDIES AND APPLICATIONS IN MARKETING MANAGEMENT; 15 Industry applications of conjoint analysis; 16 How time series econometrics helped Inofec quantify online and offline funnel progression and reallocate marketing budgets for higher profits 17 Panel data models for evaluating the effectiveness of direct-to-physician pharmaceutical marketing activities18 A nested logit model for product and transaction-type choice planning automakers' pricing and promotions; 19 Visualizing asymmetric competitive market structure in large markets; 20 User profiling in display advertising; 21 Dynamic optimization for marketing budget allocation at Bayer; PART VIII CASE STUDIES AND APPLICATIONS IN PUBLIC POLICY; 22 Consumer (mis)behavior and public policy intervention; 23 Nudging healthy choices with the 4Ps framework for behavior change 24 Field experimentation: promoting environmentally friendly consumer behavior25 Regulation and online advertising markets; 26 Measuring the long-term effects of public policy: the case of narcotics use and property crime; 27 Applying structural models in a public policy context; PART IX CASE STUDIES AND APPLICATIONS IN LITIGATION SUPPORT; 28 Avoiding bias: ensuring validity and admissibility of survey evidence in litigations; 29 Experiments in litigation; 30 Conjoint analysis in litigation; 31 Conjoint analysis: applications in antitrust litigation 32 Feature valuation using equilibrium conjoint analysis33 Regression analysis to evaluate harm in a breach of contract case: the Citri-Lite Company, Inc., Plaintiff v. Cott Beverages, Inc., Defendant; 34 Consumer surveys in trademark infringement litigation: FIJI vs. VITI case study; 35 Survey evidence to evaluate a marketing claim: Skye Astiana, Plaintiff v. Ben & Jerry's Homemade, Inc., Defendant; 36 Machine learning in litigation; Index.

The Handbook of Marketing Analytics showcases analytical marketing methods and their high-impact real-life applications in marketing management, public policy, and litigation support. Fourteen chapters present an overview of specific marketing analytic methods in technical detail, while 22 case studies present thorough examples of the use of each method. The contributors featured are recognized authorities in their fields. Multidisciplinary in scope, this Handbook covers experimental methods, non-experimental methods, and their digital-era extensions. It explores topics such as classical and Bayesian econometrics, causality, machine learning, optimization, and recent advancements in conjoint analysis. This standout collection of analytical methods and application will be useful and educational for all readers, whether they are academics or practitioners in marketing, public policy, or litigation.