ViewerYT Analytics

Analyzes YouTube video metrics to quantify engagement, retention, and audience demographics for creators and marketers.

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About This Tool

ViewerYT Analytics computes audience-focused metrics for YouTube videos using provided data. It consolidates basic video metrics (views, likes, comments, total watch time) and derives engagement, retention, and demographics insights for creators, channel managers, and marketers. The tool is designed to support post-publish evaluation and pre-publish planning.
Conceptually, you provide a video_id and a time window; the system can pull live data via YouTube API or use manually supplied figures. It then calculates engagement_score as (likes + comments + shares) / views × 100, avg_watch_time_sec as total_watch_time / views, and retention_curve as the average percentage of the video watched across progression segments. When available, demographics are summarized from the audience data.
Unique value lies in optional benchmarking against channel averages, historical comparisons, and exportable results for client reporting. Core features include multi-field inputs, computed metrics, optional benchmarking, and robust handling of missing data. Use cases include post-release performance assessment, content strategy refinement, and performance benchmarking across videos.
This tool supports analysts and creators aiming to improve engagement efficiency and to tailor content to audience segments.

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How to Use

Provide inputs: video_id, timeframe_days, and optional data_source;
Select metrics to compute (engagement, retention, demographics) and whether to benchmark;
Run calculation to generate metrics;
Review outputs in the results card and export as CSV/JSON if needed;
Use comparisons to inform content planning and optimization.

Frequently Asked Questions

Find Quick Answers

What data sources does it use?

The tool can use YouTube API data when available or rely on manually provided metrics. API access enables live data within rate limits; manual mode uses user-supplied views, likes, comments, and watch time.

What does engagement_score represent?

Engagement_score = (likes + comments + shares) / views × 100, representing the percentage of engagement per view. It is capped to a 0–100 scale; zero views yields a null or undefined score to avoid division by zero.

Can I export results?

Yes. Results can be exported in CSV or JSON formats for client reports or archival comparisons, enabling benchmarking over time or across channels.

Is data real-time?

Data freshness depends on the chosen data_source. API-based data can reflect recent activity within API limits; manual data reflects the figures you provide at run time.

What are the outputs?

Outputs include engagement_score, avg_watch_time_sec, views, retention_curve, demographics, and optional notes. Each metric is formatted for downstream analytics and reporting.

Need to run multiple calculations?

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