https://github.com/ngangawairimu/funnel-analysis-project-
This project analyzes user engagement data to visualize the funnel stages from page_view to purchase. Using SQL and data visualization, it identifies drop-off points, calculates conversion rates, and provides insights to enhance user retention, optimize experiences, and boost conversions.
https://github.com/ngangawairimu/funnel-analysis-project-
funnel-analysis marketing-analytics optimazation optimization
Last synced: 5 months ago
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This project analyzes user engagement data to visualize the funnel stages from page_view to purchase. Using SQL and data visualization, it identifies drop-off points, calculates conversion rates, and provides insights to enhance user retention, optimize experiences, and boost conversions.
- Host: GitHub
- URL: https://github.com/ngangawairimu/funnel-analysis-project-
- Owner: ngangawairimu
- Created: 2024-12-18T14:20:30.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-12-18T15:04:18.000Z (10 months ago)
- Last Synced: 2025-02-17T11:46:21.686Z (8 months ago)
- Topics: funnel-analysis, marketing-analytics, optimazation, optimization
- Homepage:
- Size: 1.35 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
Excel link: https://docs.google.com/spreadsheets/d/1v72IZxuNW3Cy09v3S3ILUNGIKjeK1uJBSnK8RYwWrb8/edit?usp=sharing
### Overview
This project performs a funnel analysis of user engagement data. The primary goal is to visualize and understand the user journey across various interaction stages, including:
- page_view
- view_item
- add_to_cart
- begin_checkout
- add_shipping_info
- add_payment_info
- purchase
By identifying drop-off points between these stages, the analysis aims to provide actionable insights to improve user retention, enhance the user experience, and boost conversion rates.
### Methodology
- Focus on Key Stages:
The funnel is analyzed to track user progression through the critical stages listed above.
Event counts and conversion rates are calculated at each step.
## Country Segmentation:
The top three countries with the highest event counts are identified for deeper analysis.
Data is enriched with country-specific insights using a mapping process.
## Visualization:
Funnel progression and drop-off rates are visualized to highlight key trends and potential bottlenecks.
Insights and Applications
## Key Observations:
- Critical drop-off points, such as from add_to_cart to begin_checkout, are identified.
Regional differences in user behavior are analyzed to inform localized strategies.
## Business Applications:
- Marketing: Insights can inform targeted campaigns to re-engage users at high drop-off points.
- Product Optimization: UX improvements can be implemented to streamline the user journey.
- Strategy Development: Data-driven decisions can optimize resource allocation and improve overall conversion rates.