Google Analytics Archives - ryanpraski.com

February 18, 2019

Google Analytics Real-Time Data Studio Dashboard

This tutorial shows you how to create a real-time Google Analytics Data Studio dashboard. The real-time Google Analytics data is fed to Google Data Studio via a Google Sheet. The Google Sheet uses Google App Script to query the Google Analytics real-time API. The Google Data Studio dashboard is automatically updated using a Chrome browser extension.

How it Works Flow Chart

Google Analytics Real-Time API > Google App Script > Google Sheet > Google Data Studio Sheets Connector > Google Data Studio Dashboard > Refresh Automatically using Data Studio Auto Refresh Chrome Extension

January 15, 2018

Drift Chat Interaction Google Analytics Tracking Using GTM

This guide shows you how to track Drift chat widget interactions and email captures in Google Analytics using Google Tag Manager (GTM). The tutorial will show you how to capture the following Drift interactions in Google Analytics events:

1) Drift chat widget is opened and closed
2) Drift chat widget sidebar is opened and closed
3) A user’s email address is captured in a conversation in the Drift chat widget
4) A conversation started and a message sent along with the Drift conversation id

After you’ve captured the Drift interactions in GTM you’ll learn how to pass this data to Google Analytics and view the aggregate reports. You’ll then go a step further and analyze an individual user journey in Google Analytics and see the Drift chat interactions in chronological order together with the user’s other site behaviors.

July 11, 2017

Pardot iFrame Form Tracking with Google Analytics

pardot_iframe_form_tracking_google_analytics

This guide shows you how to track Pardot form submissions completed in an iFrame in Google Analytics. The method described allows you to properly attribute the acquisition traffic source and medium to the conversion- the Pardot lead form submission in Google Analytics. You can also see what page on your site the Pardot iFrame lead form was submitted on using this tutorial.

April 6, 2017

R Heatmap Tutorial for Google Analytics

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This is a tutorial on how to create heatmap data visualizations using R. The data source used to construct the heatmaps in this example is Google Analytics R.

You will learn how to create two heatmaps in this tutorial:
Hourly session data by day heatmap
Page scroll depth heatmap

February 24, 2017

Google Analytics R Tutorial

This is a tutorial on how to use R to directly connect to and extract data from Google Analytics using the Google Analytics Reporting API v4. This is meant to be a simple example and assumes no prior knowledge or experience with R, APIs or programming.

I’ve included a video that walks you through each step of the process. You will be up and running in a few minutes. By the end of this tutorial you will be able to:

•Extract page view data for your top pages from Google Analytics Reporting API to R.
•Create a line graph showing session trended by day using R.

December 15, 2016

Scroll Depth Tracking Analysis with Google Analytics R

scroll_depth_google_analytics_percent_page_viewed_R

71% of pageviews to my post on automated Google Analytics cost import scroll 50% of the page and 41% of pageview reach the comments section. This is a tutorial on how to make the scroll depth tracking report above using the googleAnalyticsR package.

Scroll depth reporting gives you insight into how users are engaging with your content. How far down the page do visitors scroll? With the out of the box Google Analytics implementation there is no way to know.

September 22, 2016

Google Analytics Cost Data Import from Google Sheets – Automated

This tutorial shows how to import Google Analytics cost data automatically from Google Sheets with the click of a button. Here is the sample sheet. Go to the File – Make a Copy to edit the sheet in your Google Drive.

June 23, 2016

Integrate Google Adwords & Google Analytics with Salesforce Guide

salesforce_google_analytics_integration__ga_visitor_id_in_sf_lead_detail

How do you integrate Google Adwords and Salesforce?
How do you integrate Google Analytics and Salesforce?

The simple answer to any data integration question: you need a unique identifier that is shared across both systems. This post will give you detailed step by step instructions on how to set and capture the unique identifier to integrate Salesforce with Google Adwords and Google Analytics.

February 24, 2016

Google Search Console API R: Guide to get Started

This tutorial shows you how to setup a daily automated pull of Google Search Console data (formerly known as Google Webmaster Tools) using R. The example shows you how to save your Organic search data daily to get around Google’s current 90 day limit on historical data. Armed with this historical organic search data you can measure your content marketing and SEO efforts over months and years not just the previous 90 days. Take back your ‘not provided’ organic keyword data.

No previous knowledge of programming, APIs or R is necessary to complete this tutorial. Like my previous tutorial on getting started with the Google Analytics reporting API with Python (please check it out), I want to help you get started with a detailed example that you can use right now.

January 4, 2016

Python Google Analytics API Over 1 mil Rows Unsampled Data + Pull Data From Multiple Profiles

How to pull large data sets with over 1 million rows from Google Analytics and avoid sampling?
How to pull the same data across multiple Google Analytics profiles?

This post provides a solution for exporting more than 10,000 rows (the example pulls over 1 millions rows) and a solution for the sampling limitations of Google Analytics. The solution uses the Google Analytics reporting API and Python. It checks for the presence of sampling before running a query and gives you the ability to break your query down into smaller 10,000 row pieces. The pieces are multiple smaller queries with shorter date ranges. All the data from the small queries are stitched together and output into a single CSV file for the full date range. With this solution you can also pull data from multiple profiles using this single Python application. If you work across multiple Google Analytics profiles with high traffic volumes and often run into sampling, then this solution should save you lots of time. If you’d like to see how to use the Google Analytics Sheets Add-on to pull more than 10k rows of data and avoid sampling check out my previous post.