fileCustomer Analytics

Customer Analytics
  • MP416. Implementation of the Model.mp443.41MB
  • MP415. Probability Models.mp436.64MB
  • MP412. Beyond Period 2.mp433.73MB
  • MP414. Data Set Predictions (ry Sharmila or Chris).mp433.40MB
  • MP413. king Predictions Using a DataSet.mp423.94MB
  • MP430. Analytics Applied (Kohl\s NetFlixAmEx and more).mp422.96MB
  • MP426. The Golden Age of rketing.mp422.29MB
  • MP417. Results and Predictions.mp418.94MB
  • MP429. The Perils of Efficiency.mp417.32MB
  • MP421. Parameters of the Model.mp416.40MB
  • MP427. Applications (ROI).mp415.01MB
  • MP431. Conclusion to Application to Analytics.mp413.48MB
  • MP46. Media Planning.mp413.16MB
  • MP427. The Future of rketing is Business Analytics.mp412.27MB
  • MP49. Asking Predictive Questions.mp411.97MB
  • MP47. Types of Desc<x>riptive Analytics.mp411.97MB
  • MP428. Radically New Data Sets in rketing.mp410.73MB
  • MP425. Introduction to Application to Analytics.mp410.41MB
  • MP44. Desc<x>riptive Data Collection.mp410.03MB
  • MP419. What is Presc<x>riptive Analytics.mp49.55MB
  • MP422. rket Structure.mp49.37MB
  • PDF31-_EricBradlow_ppt_Emerging Data Sets in rketing (The Future of Marketing Science).pdf9.32MB
  • MP423. Competition and Online Advertising Models.mp48.84MB
  • MP420. Using the data to ximize revenue.mp48.74MB
  • MP43. What is Desc<x>riptive Analytics.mp48.59MB
  • PDF7-1_Iyengarppt_Desc<x>riptive Customer Analytics (Issues in rketing Research).pdf7.40MB
  • MP410. Regression Analysis (part 1).mp47.32MB
  • MP424. Conclusion(s) to Presc<x>riptive Customer Analytics.mp47.16MB
  • MP411. Regression Analysis (part 2)_The Dend Curve.mp46.71MB
  • MP45. Passive Data Collection.mp46.62MB
  • MP48. Introduction to Predictive Analytics.mp46.44MB
  • MP42. Overview of the Business Analytics Specialization.mp45.10MB
  • MP41. Course Introduction and Overview.mp44.13MB
  • MP418. Introduction to Presc<x>riptive Customer Analytics.mp42.53MB
  • PDF17-1_20150912-WDP-Fader-CustomerCentricity_Chapter4_CourseraCustomerAnalytics001.pdf917.17KB
  • PDF17-3_PeterFader_Predictive Customer Analytics.pdf536.06KB
  • PDF24-1_RonBern_ppt_Presc<x>riptive Customer Analytics.pdf342.69KB
  • PDF17-2_Iyengar2ppt_Customer Analytics (Regression Analysis).pdf280.27KB
Latest Search: 1.MXTDS-006   2.YOOM-01   3.MSYG-007   4.LIA-112   5.HITMA-45   6.CADV-327   7.NASS-052   8.KWBD-081   9.FSET-209   10.MDED-412   11.BIJ-035   12.EBOD-272   13.TMGK-033   14.MIBD-685   15.RKI-167   16.RKI-221   17.FSET-303   18.ONSD-387   19.ONSD-583   20.DAZD-037   21.WNZ-247   22.DV-1494   23.SOE-480   24.IDBD-310   25.MXGS-011   26.BUR-138   27.MODD-006   28.DAJ-004   29.TMDI-022   30.AA-012   31.JUSD-453   32.MKCK-041   33.PSSD-266   34.KTDS-554   35.DJNR-03   36.MIBD-618   37.KIBD-101   38.ACGJV-017   39.DOKS-157   40.BBS-213   41.ID-21018   42.DEXT-001   43.HTDR-008   44.JUSD-442   45.TGBE-001   46.BUR-416   47.NSPS-066   48.HIB-26   49.MIBD-596   50.SDDL-481   51.SBNS-021   52.RTP-008   53.SDMS-243   54.KAI-009   55.DVDES-603   56.KTIX-010   57.CZP-003   58.KTDVR-171   59.RD-490   60.DAPJ-057   61.SD-015   62.OKAS-022   63.PKC-040   64.NDV-438   65.DGKD-074   66.ROSD-28   67.EMAV-098   68.KA-2251   69.SUN-006   70.FE-595   71.006   72.01   73.007   74.112   75.45   76.327   77.052   78.081   79.209   80.412   81.035   82.272   83.033   84.685   85.167   86.221   87.303   88.387   89.583   90.037   91.247   92.1494   93.480   94.310   95.011   96.138   97.006   98.004   99.022   100.012   101.453   102.041   103.266   104.554   105.03   106.618   107.101   108.017   109.157   110.213   111.21018   112.001   113.008   114.442   115.001   116.416   117.066   118.26   119.596   120.481   121.021   122.008   123.243   124.009   125.603   126.010   127.003   128.171   129.490   130.057   131.015   132.022   133.040   134.438   135.074   136.28   137.098   138.2251   139.006   140.595