Product
Explore TubeAnalytics product capabilities
Navigate the core feature set, integration options, API access, and release updates from a single product umbrella.
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Features
Revenue analytics, retention curves, competitor tracking, and AI-powered thumbnail testing for monetized creators.
Integrations
Connect Google Looker Studio, Slack, Zapier, Notion, and Airtable for seamless data sync across your tool stack.
API
Programmatic access to revenue data, audience metrics, and competitor benchmarks via REST API with webhooks.
Changelog
Release notes, new features, and product update history.
What TubeAnalytics does
TubeAnalytics is a YouTube analytics platform built for creators, agencies, and media teams that need more than the data YouTube Studio provides. It aggregates revenue metrics, audience demographics, retention curves, and competitive benchmarks into a single workspace — removing the manual work of reconciling spreadsheets across multiple channels or team members.
The platform connects to YouTube's Analytics API through a secure OAuth flow, giving users access to RPM, CPM, watch time, traffic sources, and audience demographics without requiring data exports or copy-paste workflows. All data refreshes automatically so dashboards always reflect current channel performance.
- Revenue analytics: RPM, CPM, estimated revenue, and ad type breakdowns
- Competitor tracking: benchmark against up to 20 channels depending on plan tier
- AI-powered insights: plain-English recommendations based on channel data patterns
- Team collaboration: shared workspaces with role-based access for agencies
- White-label reporting: export or share branded analytics reports with clients
Integrations
TubeAnalytics integrates with popular creator tools to streamline your analytics workflow. Connect data across platforms without manual exports.
Popular integrations include:
- Google Looker Studio — native connector for custom dashboard building
- Slack — automated revenue alerts and performance summaries
- Zapier — trigger workflows on revenue milestones
- Notion — embed analytics in team wikis and docs
- Airtable — sync data for custom reporting pipelines
API Access
The TubeAnalytics API gives developers programmatic access to revenue metrics, audience data, and competitor benchmarks. Build custom dashboards or integrate with internal tools.
Core API capabilities:
- Revenue data export — RPM, CPM, estimated earnings by geography
- Competitor benchmarks — track up to 20 channels via API
- Real-time webhooks — alert on traffic spikes or revenue changes
- Audience demographics — age, gender, geography breakdowns
- Retention curves — second-by-second viewer drop-off data
Latest Update
Version 2.23.0 released March 31, 2026. Blog SEO & Pagination Improvements. This update includes:
- SEO-optimized pagination with 10 articles per page
- 5 new GEO-optimized blog articles
- Enhanced AI citability with inline quotes
Who TubeAnalytics is built for
Independent creators on the Starter tier get access to revenue analytics, channel health scoring, and content performance metrics for a single channel. This tier focuses on the core metrics that matter most for individual monetization — RPM trends, audience retention drop-off points, and traffic source breakdowns that inform upload strategy.
Agencies and multi-channel operations use the Professional and Enterprise tiers for bulk channel tracking, white-label reporting, and API access. These tiers are designed around client delivery workflows where reporting needs to move quickly and consistently across accounts of different sizes and niches.
Platform architecture and data access
TubeAnalytics connects to YouTube through the official YouTube Analytics and YouTube Data APIs. OAuth tokens are stored with AES-256-GCM encryption, and the platform auto-refreshes credentials in the background so users never encounter expired token errors during an analytics session.
The platform is built on Next.js App Router, PostgreSQL, and Upstash Redis for caching, hosted on Vercel's infrastructure. This architecture supports fast dashboard loads for most queries, even when pulling historical data across multiple channels in parallel.
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