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"r" for ROI

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Andrea Dodet
Andrea Dodet

Showing clearly the effect of a Google AdWords campaign is one of the most important task involved in a digital consultancy. Here's a quick method to impress your clients with outstandingly clear content. Just a little "r" scripting required (definitely not rocket science). Enjoy

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¡°r¡± for ROI (for Google adWords campaigns) Andrea Dodet - MSc International Business Copenhagen Business School
HOW CAN WE ASSESS THE IMPACT WITHOUT KNOWING THEIR EFFECT OF GOOGLE ADWORDS CAMPAIGNS ?
"r" for ROI
The Language R is a free software programming language and software environment for statistical computing and graphics.
The Package The model predicts how the response metric would have evolved after the campaign as if the campaign had never been performed. Simple, uh? ` install.packages("devtools") library(devtools) devtools::install_github("google/CausalImpact") library(CausalImpact)
Easy, quick, intuitive # Load data data <- read.csv (¡°data.csv¡±) ! # Specify pre-post intervention periods pre.period <- c(1,70) post.period <- c(71,100) ! # Causal impact analysis library(CausalImpact) impact <- (data, pre.period, post.period) ! # Show results summary(impact) plot(impact) !
The Output
Observed and predicted response to the original scale. Black line is the data affected by the campaign. Blue area is the situation in which nothing happened. In this case the line is well above the blue area = The campaign has produced a positive effect on the variable
The difference between the two: Causal effect produced by the campaign each point in time.
Individual causal effects added up in time (cumulative)
¡­RECAP What you need ? R installed (R Studio for comfortably interface) ? CausalImpact package ! A dataset formed by: ! ? Entries with clicks (variables) in non-affected markets or clicks on other sites etc. ? Entries after the launch of a given adWords campaign.
GRAZIE Andrea Dodet ando13ab@student.cbs.dk

More Related Content

"r" for ROI

  • 1. ¡°r¡± for ROI (for Google adWords campaigns) Andrea Dodet - MSc International Business Copenhagen Business School
  • 2. HOW CAN WE ASSESS THE IMPACT WITHOUT KNOWING THEIR EFFECT OF GOOGLE ADWORDS CAMPAIGNS ?
  • 4. The Language R is a free software programming language and software environment for statistical computing and graphics.
  • 5. The Package The model predicts how the response metric would have evolved after the campaign as if the campaign had never been performed. Simple, uh? ` install.packages("devtools") library(devtools) devtools::install_github("google/CausalImpact") library(CausalImpact)
  • 6. Easy, quick, intuitive # Load data data <- read.csv (¡°data.csv¡±) ! # Specify pre-post intervention periods pre.period <- c(1,70) post.period <- c(71,100) ! # Causal impact analysis library(CausalImpact) impact <- (data, pre.period, post.period) ! # Show results summary(impact) plot(impact) !
  • 8. Observed and predicted response to the original scale. Black line is the data affected by the campaign. Blue area is the situation in which nothing happened. In this case the line is well above the blue area = The campaign has produced a positive effect on the variable
  • 9. The difference between the two: Causal effect produced by the campaign each point in time.
  • 10. Individual causal effects added up in time (cumulative)
  • 11. ¡­RECAP What you need ? R installed (R Studio for comfortably interface) ? CausalImpact package ! A dataset formed by: ! ? Entries with clicks (variables) in non-affected markets or clicks on other sites etc. ? Entries after the launch of a given adWords campaign.
  • 12. GRAZIE Andrea Dodet ando13ab@student.cbs.dk