The real mc coy 8

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  1. 1. When the fog clears
  2. 2. a simple truth about data emerges
  3. 3. There are two types of data & inferred dataobserved data
  4. 4. One type of inferred data is panel data
  5. 5. Panel data use has proliferated in recent years 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 198019851990199520002005201020152020 Panel Data Studies* *Social Sciences Citation Index 1986, 2004, and 2005 keywords panel data or longitudinal data Nielsen Homescan Panel
  6. 6. Panel data may be the best option Panel data is suited to large longitudinal studies United States National Longitudinal Surveys of Labor Market Experience (NLS) University of Michigans Panel Study (MPS) Europe Netherlands Socio-Economic Panel (SEP) German Social Economics Panel (GSOEP) Luxembourg Social Panel (PSELL) British Household Panel Survey (BHS)
  7. 7. Warning: Panel data have limitations Panel membership may not be representative Breaks down at lower levels of aggregation Low sample size issues are common Modeling accentuates bias Panel members may report wrong data Not timely Costly
  8. 8. As noted by independent reviews Nielsen Homescan Data The dierent data give dierent results. Out of the 20 slope parameters, 5 have dierent signs, 9 do not agree on their statistical signicance, and 13 are statistically dierent. USDA On the Accuracy of Nielsen Homescan Data
  9. 9. CASE STUDY Measuring Retail Performance
  10. 10. What is the best source for measuring a retailers performance?
  11. 11. No surprise, its sales!
  12. 12. But, retailers are reluctant to give up sales data
  13. 13. Dont despair, theres another way to measure performance
  14. 14. Performance measurement alternatives are within reach Foot trac and distance travelled are observable events that can be measured and analyzed
  15. 15. Deliver timely and relevant marketing oers by oering location-based ad triggers Improve decisions by an improved understanding of customers using time and location analytics Rethink competitive strategy based on competitor sets derived from actual visitations Enhance nancial reporting by benchmarking competitor performance Benets of visitation data
  16. 16. Performance management redened Place Visit Rates PVR Total site visits Visits by distance travelled Visits by time of day Days since last visit Visits to top competitors Prole of best customers Market share by territory Competitive benchmarking Rank of top pre-visit locations Performance Management 2.0
  17. 17. Trip Driver Customer Deciles
  18. 18. Trip Driver Model The trip driver model predicts future visitations based on historical visitations, average distance traveled, demographic acributes, and other explanatory variables Methodologies considered include: generalized linear models (GLM), random-forest, and other classication models The model is validated on a hold-out sample as well as a test-sample using rigorous standards to ensure model robustness and conformity to modeling assumptions
  19. 19. The models score is grouped into deciles to highlight dierences in customer behavior TripDriverModelA.ributes 1 2 3 4 5 6 7 8 9 10 Visits per Month 60% of Visits40% of Visits Distance Traveled (Miles)< 33 - 5> 15 Age25-3535-4545-55 Household Income $85K to $120K$65K to $120K Grocery Visits per Month< 1.8> 1.8 Visits to Top 3 Competitors per Month< 2x2 4x> 4x 60% of visits come from 30% of customers Distance macers TRIP DRIVER CUSTOMER DECILES Best customers skew younger Best customers skew auent Best customers are not active grocery shoppers Best customers are loyal
  20. 20. Media Eectiveness
  21. 21. Customer Deciles is overlaid onto PVR lift to identify marketing opportunities 12345678910 Exposed to Ad in Period 1 & Converted in Period 2 Exposed to Ad in Period 1 & Did Not Convert in Period 2 Not Exposed to Ad in Period 1 & Converted in Period 2 Not Exposed to Ad in Period 1 & Did Not Convert in Period 2 PVR Lift Exposed PVR Control PVR TRIP DRIVER CUSTOMER DECILES
  22. 22. For example CUSTOMER)DECILES)))- 1" 2" 3" 4" 5" 6" 7" 8" 9" 10" Exposed(to(Ad(in(Period(1(&( Converted(in(Period(24 Exposed(to(Ad(in(Period(1(&( Did(Not(Convert(in(Period(24 Not(Exposed(to(Ad(in(Period(1( &(Converted(in(Period(24 Not(Exposed(to(Ad(in(Period(1( &(Did(Not(Convert(in(Period(24 PVR(Lift4 Exposed(PVR4 Control(PVR4