1.
Using R to Feed
Google Analytics Data
into BigQuery
Slides: https://bit.ly/3SNmp2y
@DannySmAnalysis @Semetrical
Danny Smith
Semetrical

2.
1. The Google Analytics API
2. Why use R?
3. Accessing your GA data with R
4. Uploading your GA data to Big Query
5. Additional use cases
What we’ll cover…
#BrightonSEO @Semetrical

3.
The Google
Analytics API
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4.
• Automate reporting processes
• Avoid sampling
• Granular analysis
• Send measurement protocol hits – not in reporting / data
• Change configurations – not in reporting / data
Some of the key uses of the APIs:
#BrightonSEO @Semetrical

5.
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• Free
• Quick analysis
• No sampling
• Avoids having to use SQL
Why use the GA4 API?

6.
Why
Use R?
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7.
10

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11

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12

10.
13

11.
14
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12.
Statistics, data
visualization and user-
friendly interface
The Benefits of R
#BrightonSEO @Semetrical

13.
Accessing your Google
Analytics data with R
#BrightonSEO @Semetrical

14.
17

15.
18
Setting your 4 key conditions following the API
schema. Filter between UA and GA4 accordingly.

16.
19
1. GA ID
2. Date range
3. Metrics
4. Dimensions
5. Dimension filters – optional
6. Segments - optional

17.
Uploading data to
BigQuery with R
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18.
Uploading data to
BigQuery with R
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3 variables required
for uploading data
into BigQuery:
• Project name
• Dataset name
• Table name
Locate your destination & upload to
BigQuery

19.
Summary &
Additional Use Cases
#BrightonSEO @Semetrical

20.
Overlay your Google
Analytics data with
additional data points i.e.
use Google Trends API
www.semetrical.com/using-ga-google-trends-api-with-r/

21.
• Statistical packages
• Create visuals using Shiny
or ggplot (i.e. boxplots)

22.
Automate reporting of
Google Analytics data using
cronR

23.
Pull data from BigQuery with SQL

24.
Download the deck from our blog
& grab your free R code cheat sheet to
start having a play today:
https://bit.ly/3SNmp2y
ds@Semetrical.com
@DannySmAnalysis
Thank you!
#BrightonSEO @Semetrical