Some notable other APIs useful for digital marketing are described below:
Get your SEO keywords back after (not provided) via Google’s Search Console.
## This installs searchConsoleR if you haven't got it already
if(!require(searchConsoleR)) install.packages("searchConsoleR")
library(searchConsoleR)
## authentication similar to googleAnalyticsR
scr_auth()
seo_data <- search_analytics("your-website.com", dimensions = c("date","query"))This is useful if you have Google Analytics data going into BigQuery from Google Analytics 360, as well as if you’re using BigQuery with any other data. See BigQuery section of googleAnalyticsR.
## This installs bigQueryR if you haven't got it already
if(!require(bigQueryR)) install.packages("bigQueryR")
library(googleAnalyticsR)
## Authentication similar to googleAnalyticsR
bqr_auth()
## This function turns GA dimensions/metrics into BigQuery SQL
bq <- google_analytics_bq("project-id", "dataset-id-ga-viewid",
start = "2016-01-01", end = "2016-02-01",
metrics = "users",
dimensions = c("source","medium"))
head(bq)
source medium users
1 mavas|blahbs.ru display 47837
2 examp.ae referral 6090
3 lm.facebook.com referral 335
4 ghtie_yahoo display 133900
5 fjsfs_inmobi display 19887
6 tripadvisor.co.dk referral 307
For more general BigQuery extracts, it may be better to use the more developed bigrquery() package instead.
Historically, the go-to package for getting Twitter data using R was twitteR. But, the authors of that package have recently released a new package called rtweet, which, along with being much easier to search Google for help with, offers quicker authentication options.
Rfacebook offers Facebook user data, and fbRads gets you connected to the Facebook Marketing API.
If you can’t find an R library, then you can make your own. httr is what most of the packages are built on and comes with a quickstart guide.