Upload

Loading...

This video is unavailable.

Watch Queue

TV Queue

Watch QueueTV Queue

    Loading...

Watch Queue
TV Queue
__count__/__total__

Survival Analysis for Marketing Attribution

Want to watch this again later?

Sign in to add this video to a playlist.
2,152

Like this video?

Sign in to make your opinion count.

Don't like this video?

Sign in to make your opinion count.

Loading...

Loading...

Transcript

The interactive transcript could not be loaded.

Loading...

Loading...

Ratings have been disabled for this video.
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. 1

    Applications in R - Success and Lessons Learned from the Marketplace

  2. 2

    Is Revolution R Enterprise Faster than SAS? Benchmarking Results Revealed

  3. 3

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

  4. 4

    Find the Hidden Signal in Market Data Noise

  5. 5

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

  6. 6

    20Feb14 Lityx Building and Deploying Customer Behavior Models Webinar

  7. 7

    Creating Value That Scales - with Revolution Analytics & Alteryx

  8. 8

    Big Data Analytics with Teradata and Revolution Analytics 12Nov13

  9. 9

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

  10. 10

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

  11. 11

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

  12. 12

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

  13. 13

    The Modern Data Architecture for Predictive Analytics

  14. 14

    R: The most powerful and most widely used statistical software

  15. Survival Analysis for Marketing Attribution

  16. 16

    American Century Revolutionizes their Equities Selection Platform

  17. 17

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

  18. 18

    What's New in Revolution R Enterprise 6.2

  19. 19

    Real-Time Big Data Analytics: From Deployment to Production

  20. 20

    UpStream Software: The Impact of Big Data On Marketing Analytics

  21. 21

    American Century at Revolution Analytics Customer Day, February 2013

  22. 22

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

  23. 23

    BBBT Interview with David Smith

  24. 24

    Revolution Analytics Customer Day Feb 26 2013: Panel Discussion

  25. 25

    Revolution R Enterprise and Hadoop

  26. 26

    Revolution Analytics: Revolution R Enterprise

  27. 27

    RHadoop: R meets Hadoop

  28. 28

    Introduction to R for Data Mining

  29. 29

    Using R with Hadoop Webinar

  30. 30

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

  31. 31

    New Advances in High Performance Analytics with R

  32. 32

    Shiny Launch at JSM 2012

  33. 33

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

  34. 34

    Predictive Analytics with data in Hadoop using Revolution R Enterprise 6.1

  35. 35

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

  36. 36

    Northern Trust Bank Speeds Operational Risk Models with Revolution R Enterprise

  37. 37

    R in the Insurance Industry: Loss Reserving with James Guszcza

  38. 38

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

  39. 39

    Fast, Scalable GLM in R, from Laptop to Cluster

  40. 40

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

  41. 41

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

  42. 42

    Introduction to R for Data Mining

  43. 43

    High-Performance GLM with R: An auto insurance example

  44. 44

    Cloud Computing with Revolution R Enterprise 6 and Azure Burst

  45. 45

    Certificate Program in R for Statistical Analysis, Visualization and Modeling

  46. 46

    Analyzing SAS data files with Revolution R Enterprise 6

  47. 47

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

  48. 48

    R and Hadoop - Big Data Analytics

  49. 49

    How Big Data is Changing Retail Marketing Analytics

  50. 50

    Actuarial Analytics in R

  51. 51

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

  52. 52

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

  53. 53

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

  54. 54

    Revolution R Enterprise for IBM Netezza Demonstration

  55. 55

    A Backstage Tour of ggplot2 with Hadley Wickham

  56. 56

    Introduction to RevoDeployR

  57. 57

    Big Data Analysis Starts with R

  58. 58

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

  59. 59

    Distributed Data Analysis: A Billion Row Logistic Regression

  60. 60

    Revolution R Enterprise 5.0: Distributed Analysis of Big Data

  61. 61

    Revolution Analytics - The Perfect Storm with Norman Nie

  62. 62

    Big Data Logistic Regression in R with Revolution Analytics

  63. 63

    RevoScaleR demo: Old Wives

  64. 64

    Revolution Productivity Environment Demo

  65. 65

    RevoDeployR: Web Services for R

  66. 66

    Revolution R Enterprise IDE Demo

  67. 67

    Big Data Statistics for R: RevoScaleR Demo

  68. 68

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

  69. 69

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

  70. 70

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

  71. 71

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

Loading...
Working...
to add this to Watch Later

Add to