Survival Analysis for Marketing Attribution





The interactive transcript could not be loaded.



Rating is available when the video has been rented.
This feature is not available right now. Please try again later.
Published on Jul 19, 2013

A central question in advertising is how to measure the effectiveness of different ad campaigns. In online advertising, including social media, it is possible to create thousands of different variations on an ad, and serve millions of impressions to targeted audiences each day. Rather too often, digital advertisers use the last click attribution model to evaluate the success of campaigns. In other words, when a user clicks on an ad impression, only the very last event is deemed assignficant. This is convenient but doesn't help in making good marketing decisions.

Survival analysis is widely used in the modeling of living organisms and time to failure of components, but Chandler-Pepelnjak (2010) proposed to use survival analysis for marketing attribution analysis.

All Comments

Comments are disabled for this video.
  1. 8

    Building Your Own Algorithms with RevoRemaR - Training Overview

  2. 9

    Advanced R Programming - Training Overview

  3. 10

    Batter Up! Advanced Sports Analytics with R and Storm

  4. 11

    The Fundamentals of the R Language

  5. 12

    Introduction to Revolution R Enterprise Course on DataCamp

  6. 13

    Introducing Revolution R Open: Enhanced, Open Source R distribution from Revolution Analytics

  7. 14

    Data Science with R Webinar

  8. 15

    Applications in R - Success and Lessons Learned from the Marketplace

  9. 16

    Is Revolution R Enterprise Faster than SAS? Benchmarking Results Revealed

  10. 17

    Decision Trees built in Hadoop plus more Big Data Analytics with Revolution R Enterprise

  11. 18

    Find the Hidden Signal in Market Data Noise

  12. 19

    Deploying R:Advanced Analytics On-Demandin Applications, in Dashboardsand on the Web

  13. 20

    20Feb14 Lityx Building and Deploying Customer Behavior Models Webinar

  14. 21

    Creating Value That Scales - with Revolution Analytics & Alteryx

  15. 22

    Big Data Analytics with Teradata and Revolution Analytics 12Nov13

  16. 23

    Introducing Revolution R Enterprise 7 - The Big Data Big Analytics Platform

  17. 24

    Using Time to Event Models for Prediction and Inference, presented by DataSong

  18. 25

    R+Hadoop: Ask Bigger (and New) Questions, Get Better, Faster Answers

  19. 26

    Trailer: Rob Hyndman's Online Course on Forecasting Using R

  20. 27

    The Modern Data Architecture for Predictive Analytics

  21. 28

    R: The most powerful and most widely used statistical software

  22. Survival Analysis for Marketing Attribution

  23. 30

    American Century Revolutionizes their Equities Selection Platform

  24. 31

    Knowing How People are Playing Your Game Gives You the Winning Hand

  25. 32

    What's New in Revolution R Enterprise 6.2

  26. 33

    Real-Time Big Data Analytics: From Deployment to Production

  27. 34

    UpStream Software: The Impact of Big Data On Marketing Analytics

  28. 35

    American Century at Revolution Analytics Customer Day, February 2013

  29. 36

    Revolution R Enterprise - 100% R and More [March 13, 2013]

  30. 37

    BBBT Interview with David Smith

  31. 38

    Revolution Analytics Customer Day Feb 26 2013: Panel Discussion

  32. 39

    Revolution R Enterprise and Hadoop

  33. 40

    Revolution Analytics: Revolution R Enterprise

  34. 41

    RHadoop: R meets Hadoop

  35. 42

    Introduction to R for Data Mining

  36. 43

    Using R with Hadoop Webinar

  37. 44

    Real-Time Predictive Analytics with Big Data: From Deployment to Production

  38. 45

    New Advances in High Performance Analytics with R

  39. 46

    Shiny Launch at JSM 2012

  40. 47

    Order Fulfillment Forecasting at John Deere: How R Facilitates Creativity and Flexibility

  41. 48

    Predictive Analytics with data in Hadoop using Revolution R Enterprise 6.1

  42. 49

    The Rise of Data Science in the Age of Big Data Analytics

  43. 50

    Northern Trust Bank Speeds Operational Risk Models with Revolution R Enterprise

  44. 51

    R in the Insurance Industry: Loss Reserving with James Guszcza

  45. 52

    Achieving High-Performing, Simulation-Based Operational Risk Measurement with RevoScaleR

  46. 53

    Fast, Scalable GLM in R, from Laptop to Cluster

  47. 54

    100% R and More: Plus What's New in Revolution R Enterprise 6.0

  48. 55

    Finding Meaning in Points, Areas and Surfaces: Spatial Analysis in R

  49. 56

    Introduction to R for Data Mining

  50. 57

    High-Performance GLM with R: An auto insurance example

  51. 58

    Cloud Computing with Revolution R Enterprise 6 and Azure Burst

  52. 59

    Certificate Program in R for Statistical Analysis, Visualization and Modeling

  53. 60

    Analyzing SAS data files with Revolution R Enterprise 6

  54. 61

    Integrate Your Advanced Analytics into BI Apps and MS Office and Multiply Their Value

  55. 62

    R and Hadoop - Big Data Analytics

  56. 63

    How Big Data is Changing Retail Marketing Analytics

  57. 64

    Actuarial Analytics in R

  58. 65

    Models Collecting Dust How to Transform Your Results from Interesting to Impactful

  59. 66

    Using R for Analyzing Loans, Portfolios and Risk: From Academic Theory to Financial Practice

  60. 67

    Turbo-Charge Your Analytics with IBM Netezza and Revolution R Enterprise Webinar

  61. 68

    Revolution R Enterprise for IBM Netezza Demonstration

  62. 69

    A Backstage Tour of ggplot2 with Hadley Wickham

  63. 70

    Introduction to RevoDeployR

  64. 71

    Big Data Analysis Starts with R

  65. 72

    Revolution Analytics Revolution R Enterprise: Production-grade Large Data Set Analytics Software

  66. 73

    Distributed Data Analysis: A Billion Row Logistic Regression

  67. 74

    Revolution R Enterprise 5.0: Distributed Analysis of Big Data

  68. 75

    Revolution Analytics - The Perfect Storm with Norman Nie

  69. 76

    Big Data Logistic Regression in R with Revolution Analytics

  70. 77

    RevoScaleR demo: Old Wives

  71. 78

    Revolution Productivity Environment Demo

  72. 79

    RevoDeployR: Web Services for R

  73. 80

    Revolution R Enterprise IDE Demo

  74. 81

    Big Data Statistics for R: RevoScaleR Demo

  75. 82

    What is R? (Part 3 of 4) Data Analysis and Statistical Graphics for the Enterprise

  76. 83

    What is R? (Part 2 of 4) Data Analysis and Statistical Graphics for the Enterprise

  77. 84

    What is R? (Part 4 of 4) Data Analysis and Statistical Graphics for the Enterprise

  78. 85

    What is R? (Part 1 of 4) Data Analysis and Statistical Graphics for the Enterprise

to add this to Watch Later

Add to