n8n TikTok Hashtag & Sound Finder: Bright Data + GPT + Sheets + Slack

Find TikTok hashtags & sounds that outperform—then deliver a ranked playbook to Slack

This n8n workflow automatically scrapes TikTok search results with Bright Data, identifies the hashtags and sounds that beat each topic’s median engagement, uses OpenAI (GPT-5.6) to infer the best content format from top captions, logs results to Google Sheets, and posts a ranked digest to Slack every week.

What this workflow does

• Weekly scheduled runs load your topic list and performance thresholds (posts per topic, minimum plays, lift, and cooldown) from a central configuration.
• For each topic, it triggers a Bright Data TikTok discovery scrape, then polls the Bright Data progress endpoint until the snapshot is ready (or times out).
• It downloads the scraped posts, calculates engagement rate, and aggregates results by hashtag and by sound.
• Only groups that beat the topic’s median engagement by your configured lift—and meet the minimum post/plays requirements—are kept.
• It reads previously logged tags/sounds from Google Sheets and filters out entries reported within the configured cooldown window.
• OpenAI GPT-5.6 extracts a content format, angle, and topics from captions of each selected item, then ranks the final list and generates a short strategy brief.
• Finally, it appends one row per selected hashtag/sound to Google Sheets and posts a formatted ranked digest to your Slack channel with metrics and best-post links.

Use cases

• SaaS marketing teams seeking data-driven TikTok strategy for specific niches or keywords.
• Automation engineers building a repeatable content research pipeline (Bright Data + n8n + GPT + Sheets + Slack).
• Creators/operators who want weekly reminders of which hashtags and sounds are currently overperforming.

Technical details

• Bright Data: configure HTTP Header Auth using Authorization: Bearer YOUR_KEY.
• OpenAI (Chat): connect credentials for GPT-5.6.
• n8n nodes/logic: if, set, code, no op, wait, slack.