December 19, 2016
Want to review a new digital camera, get gift ideas, or buy tickets to the next Morrissey concert? If you're in Indonesia, KASKUS is your place. 28 million unique users buy, sell, talk and share information on the site each month, making it the country's largest user-generated content publisher.
With so many users, KASKUS recently faced a growing challenge: how to serve ads that are relevant to users' age, gender and interests?
"As KASKUS is the leading digital community and social commerce platform, our vision is to drive data-driven monetization by making our first-party audience data actionable, we want to give advertisers ways to perform better in our sites and increase the effectiveness of our impression-based ads." Ronny W. Sugiadha, Chief Marketing Officer for KASKUS
Sugiadha and his team wanted to create an audience segment that had a high demand among advertisers: users who had shown interest in mobile devices and were more likely to purchase them.
KASKUS turned to Sparkline, a Google Analytics 360 Services and Sales Partner, who worked with them to approach the challenge to serve the most relevant ads. The process went from an advanced Google Analytics 360 implementation, to segmentation analysis and audience sharing with Doubleclick for Publishers (DFP).
Below is a screenshot of the actual segment shared between Google Analytics 360 and DFP. To learn more about the process, read the full case study.
How well did the new audience work compared to its old open-auction inventory in the Doubleclick Ad Exchange (AdX)?
"Using the Google Analytics 360 Audience Segment sharing feature in DFP and AdX, we doubled our CTR and saw a 3.3X CPM uplift on this audience-targeted AdX inventory," reports Ronny Sugiadha. "We are looking forward to even more positive impact moving forward."
To learn more about how KASKUS achieved those results read the full case study.
Posted by Catherine Candano and Daniel Waisberg, Google Analytics team
Google
googleAnalyticsR: A new R package for the Analytics Reporting API V4
December 16, 2016
Hello, I'm Mark Edmondson and I have the honour of being a Google Developer Expert for Google Analytics, a role that looks to help developers get the most out of Google Analytics. My specialities include Google APIs and data programming, which has prompted the creation of googleAnalyticsR, a new R package to interact with the recently released Google Analytics Reporting API V4.
R is increasingly popular with web analysts due to its powerful data processing, statistics and visualisation capabilities. A large part of R's strength in data analysis comes from its ever increasing range of open source packages. googleAnalyticsR allows you to download your Google Analytics data straight into an R session, which you could then use with other R packages to create insight and action from your data.
As well as v3 API capabilities, googleAnalyticsR also includes features unique to v4:
* On the fly calculated metrics
* Pivot reports
* Histogram data
* Multiple and more advanced segments
* Multi-date requests
* Cohorts
* Batched reports
The library will also take advantage of any new aspects of the V4 API as it develops.
Getting started
To start using googleAnalyticsR, make sure you have the latest versions of R and (optionally) the R IDE, RStudio
Start up RStudio, and install the package via:
install.packages("googleAnalyticsR")
This will install the package on your computer plus any dependencies.
After successful installation, you can load the library via library(googleAnalyticsR), and read the documentation within R via ?googleAnalyticsR, or on the package website.
An example API call - calculated metrics
Once installed, you can get your Google Analytics data similarly to the example below, which fetches an on-the-fly calculated metric:
library(googleAnalyticsR)
# authenticate with your Google Analytics login
ga_auth()
# call google analytics v4
ga4
