A complete journey to web analytics using R tool

Course Curriculum

Chapter 1: Introduction to the course

Lecture 1: 1.1 Web analytics Introduction

Lecture 2: 1.2 What you should know

Lecture 3: 1.3 Who should go for this course

Lecture 4: 1.4 Intro to Tool that is to be used

Lecture 5: 1.5 How this course will help

Chapter 2: Why Web Analytics

Lecture 1: 2.1 Why Web Analytics

Lecture 2: 2.2 What is pre, post and onsite visitors

Lecture 3: 2.3 Questions to consider

Lecture 4: 2.4 Some insights that we can get from Web Analytics

Lecture 5: 2.5 Why is it useful for businesses

Lecture 6: 2.6 Who uses Web Analytics

Lecture 7: 2.7 Metrics for Web Analytics Report

Lecture 8: 2.8 Why invest in Web Analytics

Lecture 9: 2.9 Setup a web analytics tracking system

Lecture 10: 2.10 Discussion on E-commerce and Non-Ecommerce data

Chapter 3: The Web Analytics Framework

Lecture 1: 3.1 How data collection works

Lecture 2: 3.2 How you can start with your account

Lecture 3: 3.3 Understanding data reporting

Lecture 4: 3.4 Understanding Web analytics framework and KPIs

Lecture 5: 3.5 Choosing a right web analytics tool

Lecture 6: 3.6 Web Analytics and Business Organizations

Lecture 7: 3.7 Stakeholders and Expectations

Lecture 8: 3.8 Reporting to stakeholder's need

Lecture 9: 3.9 Understnding Business Strategy

Chapter 4: Introduction to R Studio

Lecture 1: 4.1 Understanding origin of R and Rstudio

Lecture 2: 4.2 Advantages of using R in Web Analytics

Lecture 3: 4.3 Introduction to R Interface

Lecture 4: 4.4 Introduction to Rstudio Interface

Lecture 5: 4.5 Installation Process of R and Rstudio tool

Chapter 5: R Studio Basics

Lecture 1: 5.1 Understanding Vectors and variables

Lecture 2: 5.2 Understanding Dataframe

Lecture 3: 5.3 Factors,Subsetting and Summarizing methods

Lecture 4: 5.4 R help Feature

Lecture 5: 5.5 Importing data in r studio

Chapter 6: Introduction to Google Analytics in R

Lecture 1: 6.1 Intro to R google analytics

Lecture 2: 6.2 Understanding Dev tools and Github

Lecture 3: 6.3 Authentication to Google API

Lecture 4: 6.5 Extracting Data

Lecture 5: 6.6 Google trends Data Extraction

Lecture 6: 6.7 Interpreting the results for Decision making

Chapter 7: Analyzing website behavior

Lecture 1: 7.1. Understanding & Differentiating new users and

Lecture 2: 7.2. Hierarchy of visits, visitors and page views

Lecture 3: 7.3. Sorting data by Browser capabilities

Lecture 4: 7.4. Analyzing data from mobile browsers

Lecture 5: 7.5. Optimizing Traffic by time of day

Lecture 6: 7.6. Tracking your Marketing

Lecture 7: 7.7. Understanding Internal Site search behavior

Lecture 8: 7.8. Measuring Return on Investment (ROI)

Chapter 8: Visualization in R

Lecture 1: 8.1 What is Visualization

Lecture 2: 8.2 Benifits of visualizing data in R

Lecture 3: 8.3 Useful Graphs to Visualize Information

Lecture 4: 8.4 Understanding Map plotting in R

Lecture 5: 8.5 Plotting Geographic Information of Visitors on map

Chapter 9: Introduction to Time Series

Lecture 1: 9.1 What is Time Series

Lecture 2: 9.2 How do we use Time Series Data

Lecture 3: 9.3 Components of Time Series

Lecture 4: 9.4 Flavors of Time Series

Lecture 5: 9.5 Steps of Time Series Forecasting in R

Lecture 6: 9.6 Forecasting using Exponential Smoothing

Chapter 10: Further Resources and links

Lecture 1: 10.1 Further Resources

Lecture 2: 10.2 Helpful Books and Links