Web and Social Media Analytics with R: 2-in-1

Perform efficient analytics in R to optimize your web apps and enhance your business

4.50 (30 reviews)
Udemy
platform
English
language
Web Development
category
Web and Social Media Analytics with R: 2-in-1
221
students
6 hours
content
Jul 2018
last update
$39.99
regular price

What you will learn

Work with Key Performance Indicators (KPIs)

Create an effective measurement model for analytics

Learn with hands-on projects to gain insights into your website's performance

Plot cumulative transaction plots to understand the effectiveness of your marketing campaigns

Harness the power of social media analytics to improve your website or business

Use the R-markdown language to generate easy-to-understand PDF reports and dashboards.

Why take this course?

R is a popular choice of tool for analysts, offering a large variety of libraries pertaining to each and every task in data analysis. With practical projects based on various real-world domains and use-cases where web analytics can be used, this course will be your companion for implementing the various web analytics techniques using the free, open source libraries provided by R.

In this comprehensive 2-in-1 course, you will be introduced to important topics in web analytics with interesting hands-on projects to assess the performance of your website. This action-packed, must-have tutorial covers everything that you'd want to learn in web analytics for your website, and covers key concepts using R, Google Analytics, and the Flex dashboard.

This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Web Analytics with Hands-on Projects in R, starts off with covering the basics of web analytics, and why it is used in businesses worldwide. You will then be introduced to R and its libraries and will understand why R is a great choice for performing real-time analysis of your data, analyzing your websites traffic and customers behavior in real-time and how to use this information to optimize the performance of your website. You will also learn how to use the analytical capabilities of R to fully explore your Google analytics data and generate meaningful visualizations of your data using libraries like ggplot2 and generate reports based on various metrics and combinations. Towards the end of this course, you will have a solid understanding of implementing the various web analytics techniques in R, and maximize your websites performance.

The second course, Visitor Insights and Social Media Analytics in R, starts off with an overview to the key concepts such as segmentation followed by a project in which you’ll learn how to plot past 6 months visitors data on a website. You will then learn to plot revenue over the last 12 months on the same website along with cumulative transactions. Towards the end of this course, you will be able to carry out the segmentation and categorization of your website's traffic and recognize loyal visitors and the impact of social media on your visitors.

By the end of this Learning Path, you'll learn to use R to analyze the performance of your website and increase your website's traffic and revenue.

Meet Your Expert(s):

We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:

  • William Shin received his PhD from Columbia University in 2017 in biological sciences with specialization in computational biology. He has been an avid user of R since 2009 and has been using statistics to gain insights into large datasets since 2007. He has been a consistent contributor in digital analytics, a frequent speaker at conferences, and a wide range of regional events around the world.

Content

Web analytics with hands on projects in R

The Course Overview
Why Use Web Analytics?
Why Use Google Analytics?
Why R Is Perfect for Web Analytics?
Installing R and RStudio
Installing and Setting Up Google Analytics Account
GoogleAnalyticsR Package
ggplot2 Package
Useful Links for googleAnalyticsR and ggplot2
Why Use Dashboards?
Who Are the Visitors to Our Site?
Who Is Coming Back to Our Site?
How Loyal Are Our Visitors?
Building Our Business Dashboard
Exit Rate and Bounce Rates
Which Pages Have the Highest Exit and Bounce Rates?
Building Business Dashboard
How Can High Bounce Rates Be Improved?
Why Look at Multiple Time-Frame Analysis?
Why Is Context Important?
Website Performance for the Past Two Years
Building Business Dashboard
Understanding the Limit of Metrics
Multiple Time-Frame Analysis
Pitfalls of Too Much Analysis

Visitor Insights and Social Media Analytics in R

The Course Overview
Understanding Segmentation
Visitors Versus Visitors by Type
Plotting Visitors to Websites over the Last Six Months
Building Our Business Dashboard
Revenue Versus Revenue by Source
Plotting Revenue over the Last Twelve Months by Product Class
Building Our Business Dashboard
How Can Segmentation Continue to Help You?
How to Design an Effective Marketing Campaign
Measuring Customers Acquired via Campaigns
Building Cumulative Transactions Plots
Building Our Business Dashboard
Measuring Visitor Loyalty by Email Open Rates and Unsubscriptions
Measuring the Effect of Segmented Email Campaigns
Plotting Email Open Rates and Unsubscriptions
Building Our Business Dashboard
Understanding Social Media Analytics Versus Web Analytics
Plotting Sessions via Social Media by Traffic Source
Building Our Business dashboard
How Social Media Can Help Performance

Screenshots

Web and Social Media Analytics with R: 2-in-1 - Screenshot_01Web and Social Media Analytics with R: 2-in-1 - Screenshot_02Web and Social Media Analytics with R: 2-in-1 - Screenshot_03Web and Social Media Analytics with R: 2-in-1 - Screenshot_04

Reviews

Serhii
July 14, 2022
no files and explained not all such as installing libraries or who do we do this and this but information still great)
Shane
January 22, 2020
The material covered is useful and interesting but the resource files are difficult to match up with the lectures, partly because the lectures are making reference to 6 'sections' that don't exist on Coursera. I'm looking at lecture 16 now and a particular CSV file is being loaded that's not in the resource files provided. It's not the first time.

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1784994
udemy ID
7/6/2018
course created date
4/23/2021
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