https://github.com/ngangawairimu/funnel-analysis
User Engagement using Funnel Analysis to visualize the user journey through key interaction stages: "first_visit," "page_view," "add_to_cart," and "purchase."
https://github.com/ngangawairimu/funnel-analysis
conversion-optimization funnel-analysis marketing-analytics user-journey-mapping
Last synced: 3 months ago
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User Engagement using Funnel Analysis to visualize the user journey through key interaction stages: "first_visit," "page_view," "add_to_cart," and "purchase."
- Host: GitHub
- URL: https://github.com/ngangawairimu/funnel-analysis
- Owner: ngangawairimu
- Created: 2024-10-27T14:09:45.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-10-27T14:10:28.000Z (12 months ago)
- Last Synced: 2024-11-30T03:16:43.191Z (10 months ago)
- Topics: conversion-optimization, funnel-analysis, marketing-analytics, user-journey-mapping
- Homepage:
- Size: 5.86 KB
- 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/1sV8ZunQC84kNBC3FLsJg70gwmXV8htx4gweC_gYivE0/edit?usp=sharing
### Overview
This project conducts a funnel analysis on user engagement data from the tc-da-1.turing_data_analytics dataset. The primary objective is to visualize and understand the user journey across different stages of interaction, such as "first_visit," "page_view," "add_to_cart," and "purchase." By identifying drop-off points, we aim to uncover insights that can enhance user retention and conversion rates.
### Methodology
The analysis utilizes SQL queries to extract relevant data, first identifying the top three countries with the highest event counts. A deduplication process ensures that only unique user-event combinations are considered, capturing the earliest occurrence of each event type per user. This enriched dataset is filtered to focus on the user journey through key event types.
The funnel analysis highlights the progression of users through each stage, allowing us to calculate conversion rates at each step. By visualizing this data, we can identify critical drop-off points where users disengage.
#### Insights and Applications
The insights gained from this funnel analysis can inform marketing strategies, improve user experiences, and optimize product offerings tailored to specific markets. Understanding user behavior throughout the funnel enables organizations to implement targeted interventions that boost engagement and conversion rates.