Analyze marketing data

[CXL]

34 Playbooks

Get your ad data into Google Analytics

Analyze your advertising performance.

Find and analyze datasets on Kaggle

Find new opportunities through data.

Find and fix data discrepancies in GA

Keep data and results credible and accurate.

Build a mathematical model

Evaluate the options, potential risks, and impacts, to use for complex decision-making.

Enrich customer data using Kaggle

Understanding user behavior and optimize your customer profile.

Ensure your Google Analytics data is useful

Make better business decisions by increasing clarity and confidence in your data.

Fuse your data in spreadsheets

Get more in-depth insights about problems by combining data.

Use SQL for marketing analytics

6 Playbooks Last edited by @hesh_fekry 2023-11-14T15:25:43Z (UTC)

Create views in MySQL

Combine commonly used select queries from multiple tables into a single view and save time.

Import and export data using CSV file in MySQL workbench

Minimize tedious custom scripting tasks.

Set up MySQL Workbench on your computer

Store and retrieve data using objects like tables and views.

Create MySQL tables in a database

Store your data in a MySQL database.

Sort data in MySQL

Retrieve or display the data in a more structured fashion from one table or by joining multiple tables.

Set up MySQL database on Amazon AWS Cloud

Create a free database to learn and grow your skills on MySQL.

Use Python for marketing analytics

11 Playbooks Last edited by @hesh_fekry 2023-11-14T15:25:22Z (UTC)

Use numbers and variables data types in Python

Assign values to variables to use in mathematical functions and to build clean, reusable code.

Create plots using plotly library in Python

Create interactive and publication-quality graphs for data analysis and visualizations.

Work with Excel data in Python

Use Pandas to manipulate data and create data visualizations.

Use lists in Python

Store multiple items using a single variable and build cleaner code for other developers to understand.

Use comparison and logical operators in Python

Perform arithmetic operations either in the code itself or within functions and other objects.

Use sets and Tuples in Python

Store unique values that can be used for developing efficient code.

Install and use libraries in Python

Build modules and functions for data science, manipulation, and visualization.

Use strings data type in Python

Store text in string variables to build reusable code or functions in Python.

Use dictionaries in Python

Store key-value pairs that you can call without knowing the index location.

Use functions in Python

Perform specific tasks and build them to be used repeatedly within the same code or call them externally from other Python code.

Set up Python and libraries on your computer

Set up your computer ready for building automated tasks, extracting data and constructing visualizations.

Analyze raw data with GA and BigQuery

Get more accurate, detailed insight into your website visitors’ behaviors and motivations.

Improve survey analysis

Get value from your customer feedback.

Analyze user survey results

Understand your customer behavior and optimize for those behaviors.

Fix Data discrepancies between Google Ads and Analytics

Get more accurate data when viewing reports on either platform.

Fix Data discrepancies between GA and other tools

Get more accurate and consistent testing data across analytics, A/B testing, personalization & analytics tools.

Fix Data Discrepancies between GA and a CRM/CMS tools

Fix discrepancies to identify missing conversions and keep data consistent.

Model user behavior

Increase revenue and lower acquisition costs.

Tie user behavior to business value

Prioritize feature development for your product.

Last edited by @hesh_fekry 2023-11-14T15:10:22Z