R Archives - ryanpraski.com

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.

April 6, 2017

R Heatmap Tutorial for Google Analytics

heatmap_scroll_depth_page_google_analytics_R_last_365days_

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.

July 15, 2016

Apple Health Data How to Export Analyze Visualize Guide

apple_health_kit_steps_by_day_of_week_r_graph

Introduction

Did you know that the Apple Health App is recording your steps, mileage, and flights climbed data? This post will show you how to export, analyze and visualize your Apple Health data using both Excel and R. But first let’s establish that you may be sitting on a mountain of personal fitness data on your iPhone without even knowing it.

Send me your Apple Health export.xml file and I’ll analyze your fitness data for you.

Contents
Introduction
Export Apple Health App Data
Transform Apple Health XML to CSV
Analyze and Visualize Apple Health Data in Excel
Analyze and Visualize Apple Health Data in R

On iPhones 5s and newer and iOS 8 and newer, the health data is automatically collected as long as you have your iPhone with you when you are walking, running or hiking. Senors on the iPhone including the gyroscope, accelerometer, GPS, and barometer are used to measure steps, miles and flights climbed. To access the Apple Health data find and tap the heart health icon in your applications shown below. Your quantified self data is already being captured and you may not even know it.

By default your Health dashboard should launch. If not tap the Dashboard icon on the bottom navigation. The dashboard will look like the screen shot shown below.

If you tap on any of the graphs twice, the first tap will bring you to a screen with a graph of just the single metric i.e. steps, and the second tap will launch a detailed table view of the data by day. This gives a nice quick view of your health data, but it makes it difficult to answer questions such as:

How do my steps this month compare to the same month to last year?
Am I more or less active on the weekdays or weekends?

The boxplot below shows my steps data by day of the week by year. This visualization was created using R and is just one example of what you will learn to create in this post.

This post will show you how to answer these questions and get started exporting, analyzing and visualizing your Apple Health steps, walking and running distance and flights climbed data.