n8n Workflow: Juicer Brand Mention Alerts to Telegram Support & Marketing

Get Juicer brand-mention alerts in Telegram—automatically routes negative buzz to Support and everything else to Marketing

This n8n workflow listens to your Juicer feed for new post.created events and instantly sends brand mention alerts to Telegram. Mentions with negative sentiment go to your Telegram support chat, while non-negative mentions are routed to your marketing chat. It also prioritizes what matters most when Juicer delivers large batches.

What this workflow does

• Triggers on new Juicer posts: starts when Juicer sends a post.created event for each new feed post.
• Enriches alert routing settings: attaches your Telegram support and marketing chat IDs, plus a configurable `max_alerts_per_delivery` limit.
• Prioritizes and trims large batches: sorts and reduces incoming posts by prioritizing negative sentiment first, then the newest posts.
• Checks AI sentiment: uses the post’s ai_sentiment field to decide whether it’s negative.
• Routes negative mentions to Support: sends the post text and URL to your Telegram support chat.
• Routes non-negative mentions to Marketing: sends the post text and URL to your Telegram marketing chat.

Use cases

• Customer support escalation: catch negative brand mentions in real time and route them straight to the right support channel.
• Marketing monitoring: collect positive/non-negative mentions to inform campaigns, social engagement, and brand reputation tracking.
• High-volume feed control: use max_alerts_per_delivery to prevent Telegram spam during large Juicer delivery batches.

Technical details

• Juicer integration: n8n-nodes-juicer (Juicer community node) with your Juicer API key.
• Core workflow logic: set, code, no op, and switch for routing and batching control.
• Telegram delivery: n8n’s telegram node sends alerts to the configured support/marketing chats.

Built for n8n automation engineers and SaaS operators who want reliable, sentiment-aware Juicer brand mention alerts without manual monitoring.