Watch the webinar here: https://digitalmarketinginstitute.in/webinar-02-web-analytics-data-analysis-using-python/ In this webinar, Mr Abhishek Kumar (Ex. Sr. Consultant, Adobe) is sharing his expertise around web analytics. Abhishek brings along over 10 years of experience in consulting. Abhishek discussed key-concepts in web analytics, how organizations add web analytics to the website and how Python and Jupyter notebook is used for data analysis. Web analytics and data analytics What should I do? Theoretical concepts and Difference b/w Web and Data analytics  Tools and techniques  Live Demo of Jupyter Notebook Question & Answer

1. Webinar - Marketing Analytics

2. Marketing Analytics- Session-2
Abhishek Kumar | Boston University

3. Web Analytics - Data Collection
What is needed to succeed ?
- HTML & CSS
- Understanding of HTML tags
- Understanding of DOM
- Understanding class/div
- Basic Javascript
- Commonly used Javascript functions
- Basic Jquery
- Commonly used jQuery functions
- Tag Management system in web analytics

4. Data Collection on Web Vs. Mobile Vs. OTT
- Strategy in data collection on web
- Difference in data from mobile vs. web vs. OTT
- Tools to collect data from Mobile(Few Examples)
- Adobe analytics
- Google Analytics
- Appsflyer
- Mixpanel

5. Web Analytics - Data Analysis
What is needed to succeed ?
- Google Analytics Dashboard
- Adobe Analytics Workspace
Using External Tool
- MS-Excel
- Tableau
- Power BI
- DOMO
- Microstrategy

6. Data Analytics
- A discipline includes everything related to data- data collection, cleaning,
organizing, storing, governing and analyzing the data(data analysis).
- How web analytics and data analytics are related and different?
- Steps involved in Data Analysis(part of data analytics)

7. Data Analysis
Steps in Data Analysis-
1. Understanding the goal and getting the data
2. Data import
3. Data Cleaning
4. Data Exploration
5. …………………
6. ………………..

8. Tools of Data Analysis(not limited to)
- RStudio
- Jupyter Notebook
- Google Cloud Platform
- Google Bigquery
- Amazon Web Services
- Power BI
- Tableau
- Adobe Analytics Workspaces
- SAS
- DOMO
- IBM Cognos ……...

9. Jupyter Notebook
- Install
- Demo of the UI
- Perform
- Data import
- Data review
- Cleaning some data

10. Important methods in Jupyter Notebook
- head(), tail(), shape()
- describe(),drop(), info(), sum(), fillna(0),groupby()

11. Important links
● Know more about DOM Elements
● Frequently used jQuery Events
● Google Analytics for Mobile App tracking

12. About Speaker
Ex-adobe consultant on adobe marketing cloud products. More than 10+ year of
experience in web analytics and data analytics. I am currently pursuing Masters in
Applied Business Analytics from Boston University.
My LinkedIn: https://www.linkedin.com/in/abhibmsce/
My Blog: https://learnomics.wordpress.com
My Twitter: https://twitter.com/abhishekacer
My Email Id- abhikum@bu.edu

13. Webinar - Marketing Analytics