Data

Tools

Indexes

Applications

Experiments

Awesome

An open API service indexing awesome lists of open source software.

https://github.com/gilliganondata/ga-view-audit

Script that cycles through a list of views (view IDs) and makes a snapshot of custom dimension, custom metrics, and goals that it then pushes to an Excel file.
https://github.com/gilliganondata/ga-view-audit

Last synced: about 1 month ago
JSON representation

Script that cycles through a list of views (view IDs) and makes a snapshot of custom dimension, custom metrics, and goals that it then pushes to an Excel file.

Awesome Lists containing this project

README 

        



code{white-space: pre;}



  pre:not([class]) {

    background-color: white;

  }



if (window.hljs && document.readyState && document.readyState === "complete") {

   window.setTimeout(function() {

      hljs.initHighlighting();

   }, 0);

}



h1 {

  font-size: 34px;

}

h1.title {

  font-size: 38px;

}

h2 {

  font-size: 30px;

}

h3 {

  font-size: 24px;

}

h4 {

  font-size: 18px;

}

h5 {

  font-size: 16px;

}

h6 {

  font-size: 12px;

}

.table th:not([align]) {

  text-align: left;

}



.main-container {

  max-width: 940px;

  margin-left: auto;

  margin-right: auto;

}

code {

  color: inherit;

  background-color: rgba(0, 0, 0, 0.04);

}

img {

  max-width:100%;

  height: auto;

}

.tabbed-pane {

  padding-top: 12px;

}

button.code-folding-btn:focus {

  outline: none;

}






$(document).ready(function () {

  window.buildTabsets("TOC");

});











Google Analytics View Auditor


This is a script intended to help the user get a handle on his/her custom dimensions, custom metrics, and goals across one or many Google Analytics views:


    

  • Which custom dimensions, custom metrics, and goals exist, but are not recording any data, or are recording very little data?
    • 

  • Are there naming inconsistencies in the values populating the custom dimensions?
    • 



While custom metrics and goals are relatively easy to eyeball within the Google Analytics web interface, if you have a lot of custom dimensions, to truly assess them, you need to build one custom report for each custom dimension.


And, for all three of these, looking at more than a handful of views can get pretty time-consuming.


This script cycles through all of the views in a user-provided list of view IDs and returns three things for each view:


    

  • A list of all of the active custom dimensions in the view, including the top 5 values based on hits

    • 

  • A list of all of the active custom metrics in the view and the total for each metric
    • 

  • A list of all of the active goals in the view and the number of conversions for the goal
    • 



The output is an Excel file:


    

  • A worksheet that lists all of the views included in the assessment
    • 

  • A worksheet that lists all of the values checked – custom dimensions, custom metrics, and goals across all views
    • 

  • A worksheet for each included view that lists just the custom dimensions, custom metrics, and goals for that view
    • 





How to Use


This does take a little bit of setup work.




Set Up a Google Project


This script uses googleAnalyticsR, and it hits the Google APIs pretty hard and fast, so you do not want to use the default project. Luckily, it’s pretty easy (and free) to set up a Google Project to work with googleAnalyticsR. Donal Phipps has put together a nice video on how to do that.






Put the Credentials in Your .Renviron File


If you put your client ID and client secret in a .Renviron file as GA_CLIENT_ID AND GA_CLIENT_SECRET, then you are all set (remember to restart your R session if you do add them after you’re already working with this project).


The following lines in the code will then read those values in. But, you can also just hardcode the values if you like to live on the wild side:


ga_client_id <- Sys.getenv("GA_CLIENT_ID")

ga_client_secret <- Sys.getenv("GA_CLIENT_SECRET")






Create a key_views.csv File


This is the list of views that you want to assess. You can get these from the Google Analytics Query Explorer or through any other means. But, ultimately, they need to go into a file called key_views.csv located in the input folder. (There is a file there now that you can use as a template.)


KEY: The headings for the file need to be view_id and label. label actually never appears in the output and is just there for your own reference as you are building the .csv file.


view_id,label

104######,Some Descriptor for Your Reference

119######,Some descriptor for your reference


If you’re building it in Excel, it would look more like this before you exported it as a .csv:



view_id

label



104######

Some Descriptor for Your Reference



119######

Some descriptor for your reference







Check/Adjust the Date Range


The script, by default, will pull data for the last 30 days. But, you can adjust this code as you see fit if you want a different timeframe:


end_date <- Sys.Date() - 1

start_date <- end_date - 29






Set How Many Custom Dimension Values to Return


The script, by default, returns the top 5 custom dimension values by hits. This can be set to any number (if there are fewer than that number for any specific dimension, it will simply return all of the values). Just update this line of the code:


custom_dim_top_x <- 5






Run the Script!


Open and run ga-views-dims-metrics-goals.Rmd'. Depending on how many views and how many custom dimensions, custom metrics, and goals are set up, it may take a while to run. But, ultimately, it will export a file calledcustom_data_summary.xlsxto theoutput` directory.








A Note on the Output File


The data_snapshot column that appears on every sheet except the first one is probably the most important piece of output. It’s three different things depending on the type of data:


    

  • For custom dimensions, it’s the top X (default = 5) values for the custom dimension based on hits, as well as, parenthethically, the actual number of hits
    • 

  • For custom metrics, it’s the total for the metric
    • 

  • For goals, it’s the number of conversions for the goal
    • 



That’s about it!










// add bootstrap table styles to pandoc tables

function bootstrapStylePandocTables() {

  $('tr.header').parent('thead').parent('table').addClass('table table-condensed');

}

$(document).ready(function () {

  bootstrapStylePandocTables();

});



  (function () {

    var script = document.createElement("script");

    script.type = "text/javascript";

    script.src  = "https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML";

    document.getElementsByTagName("head")[0].appendChild(script);

  })();