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Talk: Hierarchical effects of advertising (42 min)

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DETAILED SLIDE INDEX

  1. 1. Introduction
  2. 2. Outline
  3. 3. Multi-stage purchase process
  4. 4. Intermediate media effects (1)
  5. 5. Intermediate media effects (2)
  6. 6. Empirical data
  7. 7. Hierarchical effects
  8. 8. Models considered
  9. 9. Modeling approach (1)
  10. 10. Modeling approach (2)
  11. 11. Proposed segment level model (1)
  12. 12. Proposed segment level model (2)
  13. 13. Summary statistics (automobile data)
  14. 14. Simulation study 1
  15. 15. Simulation study 2
  16. 16. Standard aggregate regression model
  17. 17. Partitioning the dependent variable
  18. 18. Aggregate model
  19. 19. Model comparisons
  20. 20. Trace plot for automobile data
  21. 21. Best fitting model - output (1)
  22. 22. Best fitting model - output (2)
  23. 23. Best fitting model - output (3)
  24. 24. Purchase intention and media exposure
  25. 25. For the best fitting model
  26. 26. Effect of media exposure on purchase intention
  27. 27. Empirical results
  28. 28. Thank you!
  29. 29. END

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TALK'S CITATION

Chandukala, S.R. (2010), "Hierarchical effects of advertising", in Allenby, G.M. and Rossi, P.E. (eds), Bayesian Analysis in Marketing: A breakthrough in customer analytics, The Marketing & Management Collection, Henry Stewart Talks Ltd, London (online at http://hstalks.com/?t=MM0992310)

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ABOUT THIS TALK

Speaker(s)

Prof. Sandeep R. Chandukala Show Biography

SPEAKER BIOGRAPHY

Prof. Sandeep R. Chandukala – Assistant Professor of Marketing, Indiana University, USA

Sandeep is an Assistant Professor of Marketing at the Kelley School of Business in Indiana University. He graduated with a PhD in marketing from Fisher College of Business at the Ohio State University in 2008. He also holds Masters degrees in computer engineering from University of Minnesota and in business administration, and management and administration sciences from the University of Texas at Dallas. He has worked as a software developer and advisor at Dell Computer Corporation in Austin, Texas. His primary areas of research include Bayesian applications in marketing, discrete choice models and quantitative models of advertising and consumer memory.

Publication Date

January, 2010

Topics Covered

Multistage processes... more

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  • Multistage processes
  • Understanding intermediate effects of advertising
  • A simple Bayesian approach for capturing intermediate effects with heterogeneous response segments
  • Application based on cross-sectional brand tracking data to demonstrate the proposed modeling strategy and model comparisons

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