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https://github.com/docuvesta/youtube-api-fragrance-channel-analytics

Engagement metrics analysis of perfume Youtube channel using Youtube API 🎀
https://github.com/docuvesta/youtube-api-fragrance-channel-analytics

analysis beauty-products comments data-analysis data-analysis-python engagement-metrics insights jupyter-notebook likes-count marketing marketing-analytics perfume python views-count youtube youtube-api youtube-api-v3

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Engagement metrics analysis of perfume Youtube channel using Youtube API 🎀

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Engagement Metrics Analysis of a Perfume Youtube Channel Using YouTube API



## Overview
What better way to discover new products than through a recommendation? It's pre-vetted and, if you're lucky, it includes a detailed breakdown of the product's pros and cons. Nowadays, if we're considering buying a new sunscreen, lotion, or perfume, it's likely because we've seen it highlighted by an influencer on social media. For this project, I analyze Monika Cioch's YouTube channel, which is largely dedicated to reviewing, discovering, and recommending perfumes. This analysis aims to understand her viewers' preferences by examining engagement metrics such as views, likes, and comments count to determine which of her videos performs the best.


## Data Context
#### For the analysis, each video was categorized into a specific group


Category Name
Description


recommendation
in-depth description of perfume(s)


review
first impression of a perfume or perfume comparison


informative
in-depth breakdown of a specific perfume or videos on how to choose a perfume


fun
non-perfume related videos for entertainment


fashion
non-perfume related videos about fashion


shorts
Youtube shorts


## Analytics






## Key Insights
- Monika's audience prefers review videos. Although they make up just 11.7% of her content, review videos receive the highest number of views and comments, with likes trailing only slightly behind Youtube shorts. To note, it is also the category with the most outliers based on the violin plot.
- Based on all three engagement metrics, longform content tend to generally outperform shortform content
- The top 4 videos that consistently rank in the top 10 are about the types of perfumes that men would find appealing on women 👀


## Future Work
- Comments analysis
- Classify videos using more specific categories
- Audience demographics analysis
- Include the variable of time: Are the best performing videos the ones that have been up the longest?


## Repository Contents
### Folder: data
##### All data used to complete project


File Name
Data Description


video_info.csv
raw data from Youtube API


video_info_with_categories.csv
added new column named 'category' to classify videos


video_info_cleaned.csv
final cleaned data


### Python File: youtube_api_data_collection.py
- Extracts engagement metrics from a perfume YouTube channel
- Utilizes the YouTube API for data retrieval
- Saves the data in csv format


### Jupyter Notebook: data_transformation_fragrance_youtube.ipynb
- Jupyter notebook with annotations detailing each stage of preprocessing data from Youtube's API
- Data exploration process
- Plotly visualizations


### Folder: assets
##### All assets used to complete project
- pictures
- graphs
- tables