Set Automate

7/8/2025
37 nodes
Complex
schedulecomplexsplitoutlangchainspotifyfiltergooglesheetssticky noteschedule triggernoopautomationadvancedapiintegrationlogicconditionalcron
Categories:
Schedule TriggeredComplex WorkflowData Processing & AnalysisCreative Content & Video Automation
Integrations:
SplitOutLangChainSpotifyFilterGoogleSheetsSticky NoteSchedule TriggerNoOp

Target Audience

This workflow is ideal for Spotify users who want to systematically archive their listening history and organize their tracks into custom playlists. Specifically:
- Music Enthusiasts: Those who frequently discover and enjoy new music and want to keep a record of their favorites.
- Playlist Creators: Individuals looking to create curated playlists based on personal preferences or specific themes.
- Data-Driven Users: People who appreciate insights into their music preferences and wish to analyze their listening habits over time.
- Social Media Influencers: Creators who want to share their music tastes and playlists with their audience in a structured manner.

Problem Solved

This workflow automates the monthly process of tracking, storing, and categorizing Spotify tracks into relevant playlists. It addresses the challenge of:
- Manual Archiving: Eliminating the need for users to manually log their liked tracks and playlists, saving valuable time.
- Playlist Organization: Helping users maintain well-organized music collections by automatically classifying tracks into appropriate playlists based on their characteristics.
- Historical Record Keeping: Ensuring users have a historical record of their listening habits, which can be useful for reflection or sharing with others.

Workflow Steps

  • Trigger Options: The workflow can be initiated either manually or on a set schedule (monthly).
    2. Retrieve Playlists: It fetches the current playlists owned by the user to gather relevant data.
    3. Get Tracks: The workflow retrieves all tracks liked by the user from their Spotify library.
    4. Audio Features Fetching: It uses the Spotify API to get detailed audio features for each track, such as danceability, energy, and tempo.
    5. Data Merging: The workflow merges track information with their audio features for a comprehensive dataset.
    6. Duplicate Checking: It filters out tracks that have already been logged in Google Sheets to avoid redundancy.
    7. Data Logging: New tracks are archived into a Google Sheet for future reference.
    8. AI Classification: An AI model analyzes the tracks and classifies them into suitable playlists based on their characteristics.
    9. Playlist Updates: Finally, the classified tracks are added to the corresponding playlists on Spotify.

    • Customization Guide

    Users can customize and adapt this workflow by:
    - Adjusting Playlist Conditions: Modify the AI model’s classification criteria to align with personal music preferences.
    - Enhancing Track Analysis: Incorporate additional audio features or external data sources for more refined track categorization.
    - Personalizing Data Logging: Customize which track attributes to log in Google Sheets based on archival preferences.
    - Configuring Scheduling: Set a preferred schedule for periodic track archiving, such as monthly or weekly. This flexibility allows users to tailor the workflow to their specific needs.