Skip to content

Analysis of user behavior and email campaign performance using BigQuery and Looker Studio, focusing on account creation trends, email engagement, and user segmentation.

Notifications You must be signed in to change notification settings

thenazar9/user-behavior-email-campaign-analysis-sql

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

8 Commits
Β 
Β 
Β 
Β 
Β 
Β 

Repository files navigation

User Behavior and Email Campaign Performance Analysis (SQL & Looker Studio)

This project analyzes user behavior and email campaign performance using an e-commerce dataset in BigQuery. The main goal is to create a dataset that helps track account creation dynamics, user activity with emails (sent, opened, clicked), and evaluate user segmentation based on sending intervals, account verification status, and subscription status.

πŸ” Project Goals

  • Analyze user account creation trends and email activity by date and country.
  • Segment users by sending interval, account verification (is_verified), and subscription status (is_unsubscribed).
  • Calculate key metrics including:
    • Number of accounts created (account_cnt)
    • Number of emails sent (sent_msg)
    • Number of emails opened (open_msg)
    • Number of email link clicks (visit_msg)
  • Rank countries by total account creation and total emails sent to identify top markets.
  • Combine account and email metrics in one dataset using SQL UNION.
  • Filter results to include only top 10 countries by accounts or emails sent.

πŸ“Š Tools & Skills Used

  • BigQuery SQL: complex queries with CTEs (Common Table Expressions), window functions for ranking, grouping and aggregations.
  • Looker Studio: interactive dashboards and data visualizations.
  • Data analysis: user behavior, email campaign effectiveness, segmentation, ranking.

πŸ“ Dataset Structure

The final dataset includes the following fields:

  • date β€” account creation date or email sent date
  • country β€” user country
  • send_interval β€” email sending interval set by user
  • is_verified β€” account verification status
  • is_unsubscribed β€” subscription status
  • account_cnt β€” number of accounts created
  • sent_msg β€” number of emails sent
  • open_msg β€” number of emails opened
  • visit_msg β€” number of email link clicks
  • total_country_account_cnt β€” total accounts created per country
  • total_country_sent_cnt β€” total emails sent per country
  • rank_total_country_account_cnt β€” rank of countries by accounts created
  • rank_total_country_sent_cnt β€” rank of countries by emails sent

πŸ“„ Deliverables

  • SQL query with detailed comments explaining logic and structure.
  • Looker Studio dashboard visualizing:
    • Email engagement trends (sent, opened, clicked messages) over time.
    • Total accounts created by country (map visualization).
    • Country rankings by total account creation and total emails sent.
    • Account information by country, including subscription and verification status.

πŸ“ˆ Visualization of Results

Below is the graphical representation of the analyzed data, showing key trends and metrics from the user behavior and email campaign performance analysis.

Visualization Screenshot

About

Analysis of user behavior and email campaign performance using BigQuery and Looker Studio, focusing on account creation trends, email engagement, and user segmentation.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published
pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy