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Marketing: Then and Now

Issues and Data. Then (my AMA)One short-term market of interdependent consumers facing aggregated communicationsNow (your AMA)Multiple markets of linked and interacting consumers and firms over long horizons facing customized communicationsLonger-termInteractivity / Network EffectsCustomer-Cus

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Marketing: Then and Now

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    1. Marketing: Then and Now Carl F. Mela Duke University

    2. Issues and Data Then (my AMA) One short-term market of interdependent consumers facing aggregated communications Now (your AMA) Multiple markets of linked and interacting consumers and firms over long horizons facing customized communications Longer-term Interactivity / Network Effects Customer-Customer / Network effects Customer-Firm Spatial Demand CRM/Lifetime Value

    3. Estimation Then EM/Mixture models Simulated maximum likelihood Dynamic programming and control Stochastic models Meta-analyses

    4. Estimation Now EM/Mixture models Simulated maximum likelihood Dynamic programming and control Stochastic models Meta-analyses MCMC/Bayesian Time series (VAR, DLM, etc.) Spectral methods Learning models Spatial statistics Empirical I/O models Non-parametrics Method of moments

    5. 1. Long-term Erosion of Brands

    6. Erosion of Brands Customers are more price sensitive. 75% of CPG retailers and manufacturers rank pressure to reduce price as single largest threat in the next 3 years - IRI/EIU Survey Sales elasticities have increased 1 point in past 25 years (Bijmolt et al. 2005)

    7. Erosion of Brands

    8. DLM

    9. 2. Customer – Customer Interactivity

    10. Network Effects Often related in economics and sociology to adoption, pricing, etc. In marketing many new contexts to study centrality and social influence across individuals as well as populations Peer-peer networks Internet chat Internet auctions

    11. New Data

    12. New Tools Structural orientation with multiple agents Auctions Goal is to infer latent costs of seller and bidder (e.g., opportunity costs of bidding and acquisition costs) and bidder value distribution Bidders bid if expected return is positive Sellers list number of items to max profits Imply bidder and lister likelihoods for MCMC Can infer effect of fee change when none exists

    13. Modeling Network Effects

    14. Modeling Network Effects

    15. 3. Customer Firm Interactivity

    16. Media Proliferation Phil s2Phil s2

    17. Interactive, Addressable and Customizable Media Internet MSN Ad -- $1MM for 24 hours ($25 K 4 Years Back) Interactive TV 10MM US HH Media are now merging So may the research streams Interactivity

    18. E-Customization Approach

    19. Modeling Heterogeneity Finite Mixtures Continuous Mixtures

    20. Optimization Results

    21. 4. Spatial Effects

    22. New Issues/Methods Spatial Demand Demand and equilibrium prices used to inform apartment location decision

    23. Set Up Moment Conditions Demand side (location demand errors independent of instruments) Supply side (price markup errors independent of instruments) MCMC Estimation (Romeo 2006) Replace typical MOM e’Z = 0 with e’Z ~ N(0,S) Allows for Bayesian inference Spatial correlation in demand and supply errors Estimation

    24. Policy Simulation No spatial covariation understates profit variation and leads to parameter bias. Spatial model yields 65% increase in profits (to $35,010).

    25. 5. Customer Relationship Management (CRM)

    26. CRM Lifecycle Acquisition/Birth Lifetime Value > Cost of Acquisition Growth Cross selling and upselling Retention/Death/Churn Predict churn Loyalty programs

    27. CRM Information Sets Many observations and variables Multiple data sources to merge Many customers and variables, but incomplete sets Scalability (e.g., SML v. MCMC) Rare events Churn, cross-selling, acquisitions Inward focused data

    28. Internal Data

    29. Holdout Sample Performance

    30. Rare Events, Many Variables

    31. Summary New Issues Brands in decline, proliferation of media, interactivity, spatial demand, CRM New Data Log files, call records, CRM systems Massive files New Approaches Non-parametrics, spatial statistics, EIO Most Interesting Time in Marketing Since “Then”

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