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DACS for CDB workshop 10-9-2008-copy

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Does Advertising Cause Sales, October 2008 for MIT Center for Digital Business. Erik Brynjolfsson, at the MIT Sloan School and MIT Center for Digital Business.

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DACS for CDB workshop 10-9-2008-copy

  1. 1. Does Advertising Cause Future Sales? Evidence from Retail Advertising Duncan Simester Yu (Jeffrey) Hu Sloan School of Management Krannert School of Management MIT Purdue University Eric T. Anderson Erik Brynjolfsson Kellogg School of Management Sloan School of Management Northwestern University MIT
  2. 2. Research Questions Lord Lever’s Quandary: – Half my advertising budget is wasted. The problem is I don’t know which half!s Research Question: Is advertising effective? – Direct effects on current sales – Indirect Effects • Future sales • Cross channel saless Two Obstacles have blocked a definitive answer – Advertising endogenous – Advertising is dynamic
  3. 3. Our Approachs Large-scale Controlled Field Experiment – Catalogs as advertising • Largest category of advertising: $48 Billion/yr • Product: Availability & Price • Firm: Brand, Warranties, Orderings Exogenously Varied mailing strategy for 9 monthss Random assignment between two conditions – 17 catalogs – 12 catalogs
  4. 4. Experimental Design Initial Sample 20,000 Good Customers Best Customers 10,000 10,000 Random assignment Random assignmentControl Group Test Group Control Group Test Group 5,000 5,000 5,000 5,00012 catalogs 17 catalogs 12 catalogs 17 catalogs
  5. 5. Low High Advertising AdvertisingCatalog 1Mailing Date 1 January 11 January 11Mailing Date 2 February 22 February 8Catalog 2Mailing Date 1 February 1 January 25Mailing Date 2 February 22Catalog 3Mailing Date 1 March 15 March 8Maili ng Date 2 April 26 April 5Catalog 4Mailing Date 1 April 5 March 22Mailing Date 2 May 3Catalog 5Mailing Date 1 May 17 April 19Mailing Date 2 May 17Catalog 6Mailing Date 1 June 7 June 7Mailing Date 2 June 28 June 28Catalog 7Mailing Date 1 July 26 July 26Mailing Date 2 September 6 August 23Mailing Date 3 September 20Catalog 8Mailing Date 1 August 9 August 9Mailing Date 2 September 6
  6. 6. Three Periodss The “Pretest” period – January 1, 1988 through January 24, 2002.s The “Test” period – January 25, 2002 through December 31, 2002s The “Posttest” period – January 1, 2003 through August 13, 2003.
  7. 7. Table 3: Check on Randomization Process Purchases During the Pretest Period Control Treatment p-value Condition ConditionBest Customers 1.43 1.43Recency 0.72 (0.02) (0.01) 40.38 40.75Frequency 0.59 (0.45) (0.51) 61.11 61.22Monetary Value 0.69 (0.19) (0.19)Sample Size 4,921 4,904Other Customers 4.67 4.76Recency 0.30 (0.06) (0.06) 10.56 10.62Frequency 0.85 (0.20) (0.21) 63.85 64.18Monetary Value 0.50 (0.29) (0.33)Sample Size 4,790 4,758
  8. 8. Demand During the Test Period 5 4 Control TestItems / Customers 3 2 1 0 Good Customers Best Customers
  9. 9. Demand During the Test Period 15% 10%% C h a n g e in D e m a n d 5% 0% G o o d C u s to m e rs B e s t C u s to m e rs -5 % -1 0 % Test P ost Test
  10. 10. Demand During the Posttest Period 15% 10%% C h a n g e in D e m a n d 5% 0% G o o d C u s to m e rs B e s t C u s to m e rs -5 % -1 0 % Test P ost Test
  11. 11. Demand During the Posttest Period 15% 10%% C h a n g e in D e m a n d 5% 0% G o o d C u s to m e rs B e s t C u s to m e rs -5 % -1 0 % Test P ost Test
  12. 12. Persistence of the Effect Good Best Customers CustomersStart of Posttest Period 12.2% ** -9.4% **End of Posttest Period
  13. 13. Persistence of the Effect Good Best Customers Customers ** **Start of Posttest Period 12.2% -9.4%End of Posttest Period 7.3% **
  14. 14. Persistence of the Effect Good Best Customers CustomersStart of Posttest Period 12.2% ** -9.4% **End of Posttest Period 7.3% ** 1.6%
  15. 15. Cross-Channel Effects Good Best Customers Customers ** **Catalog Channel 11.6% 6.3%Internet Channel
  16. 16. Cross-Channel Effects Good Best Customers CustomersCatalog Channel 11.6% ** 6.3% **Internet Channel 30.3% **
  17. 17. Cross-Channel Effects Good Best Customers CustomersCatalog Channel 11.6% ** 6.3% **Internet Channel 30.3% ** -9.6% *
  18. 18. Profit Implications Good Best Customers CustomersShort-Run Catalog Profit $0.36 $1.58
  19. 19. Profit Implications Good Best Customers CustomersShort-Run Catalog Profit $0.36 $1.58Add Short -Run Internet $1.08 $1.53
  20. 20. Profit Implications Good Best Customers CustomersShort -Run Catalog Profit $0.36 $1.58Add Short -Run Internet $1.08 $1.53Add Long -Run $2.43 -$0.73
  21. 21. Conclusion: Key Findings1. Current advertising can cause changes in future demand – Increase demand (Brand switching) – Decrease demand (Intertemporal substitution) – We modeled and found both effects2. Heterogeneity: Effect on future sales can differ across customers segments – Purchase history matters • Best Customers: Intertemporal (and Channel) Substitution • Good Customers: Brand Switching
  22. 22. Implicationss Treating time periods and channels as independent leads to wrong marketing decisions – Dynamic models – Sharing data – Integrations Field Experiments can help address endogeneity and dynamic confounds • But models matter: naïve aggregation of even experimental data nets to zero(!) effect
  23. 23. For more informationhttp://digital.mit.edu/erik

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