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

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)
!

7. The Output

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