Get instant, configurable alerts when your YouTube videos spike or slump across views, CTR, watch time, comments, or subs. This automation watches metrics, detects anomalies, and pings you (Telegram/Discord/Email) so you can react before the algorithm moves on. Built for teams that need real-time visibility without living inside YouTube Studio.
Created by Appilot, built to showcase our approach to Automation!
If you are looking for custom YouTube Video Performance Alert Bot, you've just found your team — Let’s Chat.👆👆
##Introduction This system monitors YouTube video performance signals and triggers alerts when thresholds or trend deviations are met. It automates the repetitive workflow of checking analytics, comparing baselines, and escalating issues or wins to your channels. The benefit: faster decisions, protected retention, and timely growth moves.
- Detects sudden drops in CTR or watch time and notifies stakeholders instantly.
- Learns baselines per channel/video to reduce false positives using rolling windows.
- Works with real Android devices/emulators to fetch live signals and verify UI states.
- Integrates with dashboards, webhooks, and team chat for seamless routing.
- Real Devices and Emulators: Run on real phones or emulators (Bluestacks/Nox) to validate on-device analytics pages, notifications, and UI states for resilient monitoring.
- No-ADB Wireless Automation: Control devices via Appilot over Wi-Fi with encrypted channels; avoids tethered USB/ADB footprints for safer farm operations.
- Mimicking Human Behavior: Randomized tap/scroll cadence, dwell times, and jittered navigation across YouTube Studio to emulate human checks and reduce behavioral flags.
- Multiple Accounts Support: Monitor multiple channels/brands at once with isolated profiles, per-account thresholds, and scoped alert routing.
- Multi-Device Integration: Distribute monitoring jobs across 10–300+ devices with queueing, sharding, and backpressure to meet strict polling SLAs.
- Exponential Growth for Your Account: Catch early momentum (CTR bumps, retention spikes) to double down on distribution, comments, and pinning for compounding reach.
- Premium Support: White-glove onboarding, alert rule tuning, and priority incident response for production teams.
- Granular Alert Rules: Thresholds for CTR, impressions, views, average view duration, like rate, comment velocity, and sub delta with AND/OR logic.
- Anomaly Detection: Rolling z-score and median absolute deviation (MAD) against per-video baselines to flag unusual trends.
- Actionable Context: Each alert includes metric snapshots, diffs vs baseline, quick links to Studio pages, and recommended next steps.
| Feature | Description |
|---|---|
| Webhook & Chat Alerts | Send rich alerts to Telegram, Discord, Slack, or custom webhooks with payloads for downstream workflows. |
| Quiet Hours & SLOs | Define alert windows, cooldowns, and escalation policies; prevent noise during known maintenance periods. |
| Proxy & Fingerprint Control | Device-level proxy routing and stable fingerprints per profile for consistent access patterns. |
| Role-Based Access | Team permissions for creating rules, viewing alerts, and acknowledging incidents. |
| Replay & Audit Logs | Persist raw samples, device traces, screenshots, and rule evaluations for debugging and compliance. |
| Scheduler & Queues | Cron-like schedules, rate limits, and priority queues to meet polling frequency without overload. |
- Input or Trigger — From the Appilot dashboard, select channels/videos and define alert rules (e.g., CTR < 4% for 3 samples, watch time drop > 20% vs baseline, comment velocity spike).
- Core Logic — Appilot orchestrates Android devices/emulators via UI Automator or ADB where needed, navigates YouTube Studio, captures KPIs, and aggregates samples.
- Output or Action — When a rule matches or an anomaly is detected, the system pushes alerts to Telegram/Discord/Email/webhooks with diffs and remediation tips.
- Other functionalities — Automatic retries, device failover, per-metric cooldowns, error screenshots, structured logging, and parallel processing are configurable in the dashboard.
- Language: Kotlin, Java, Python, JavaScript
- Frameworks: Appium, UI Automator, Espresso, Robot Framework, Cucumber
- Tools: Appilot, Android Debug Bridge (ADB), Appium Inspector, Bluestacks, Nox Player, Scrcpy, Firebase Test Lab, MonkeyRunner, Accessibility
- Infrastructure: Dockerized device farms, Cloud-based emulators, Proxy networks, Parallel Device Execution, Task Queues, Real device farm
youtube-performance-alert-bot/
│
├── src/
│ ├── main.py
│ ├── rules/
│ │ ├── thresholds.yaml
│ │ ├── anomalies.py
│ │ └── evaluators.py
│ ├── devices/
│ │ ├── controller.py
│ │ ├── ui_automator_client.kt
│ │ └── appium_session.js
│ ├── collectors/
│ │ ├── studio_scraper.py
│ │ ├── metrics_parser.py
│ │ └── screenshotter.py
│ ├── alerts/
│ │ ├── telegram_notifier.py
│ │ ├── discord_notifier.py
│ │ └── webhook_sender.py
│ └── utils/
│ ├── logger.py
│ ├── proxy_manager.py
│ └── config_loader.py
│
├── config/
│ ├── settings.yaml
│ ├── credentials.env
│ └── routes.json
│
├── dashboards/
│ └── grafana/
│ └── panels.json
│
├── media/
│ └── YouTube Video Performance Alert Bot-banner.png
│
├── logs/
│ └── runner.log
│
├── output/
│ ├── samples.jsonl
│ └── alerts.csv
│
├── docker/
│ ├── Dockerfile
│ └── docker-compose.yml
│
├── requirements.txt
└── README.md
- Creators use it to auto-flag CTR drops within minutes, so they can update thumbnails/titles fast and preserve session starts.
- Agencies use it to monitor client channels at scale, so they can escalate wins/risks and justify timely interventions.
- Growth teams use it to detect comment spikes, so they can jump into conversation and pin replies for more engagement.
- Ops engineers use it to maintain SLA-based monitoring, so they can ensure coverage across time zones without manual checks.
How do I configure this for multiple channels?
Add each account profile in config/settings.yaml with its proxy and device mapping. Create per-channel rules in rules/thresholds.yaml and assign alert routes (Telegram/Discord/webhook) per channel.
Does it support proxy rotation or anti-detection?
Yes. Each device/profile can use dedicated residential/mobile proxies. Fingerprints are stable per profile; rotation is handled by proxy_manager.py with health checks and cooldowns.
Can I schedule polling windows and quiet hours?
Absolutely. Use the scheduler to set cron expressions and quiet hours. Cooldowns prevent duplicate alerts during ongoing incidents.
What metrics can I alert on?
Views, impressions, CTR, average view duration, watch time, like rate, comment velocity, subscriber delta, and custom composite signals.
- Execution Speed: Typical poll cycles complete in 18–45 seconds per video on device farms; batch sharding keeps fleet utilization >80% under load.
- Success Rate: 95% successful metric captures across mixed networks with retry and failover enabled.
- Scalability: Proven to coordinate 300–1,000 Android devices via queues and shard controllers; horizontal scale with additional workers.
- Resource Efficiency: CPU-light polling processes; device sessions reused; screenshot diffs reduce bandwidth/storage by ~60%.
- Error Handling: Exponential backoff, circuit breakers, per-rule cooldowns, structured logs, screenshots on failure, and on-call escalation via webhooks.
