Travel Vlog Production from Destination Research to Social Media

You've just returned from two weeks in Japan. Your camera roll contains hundreds of photos and videos. Your phone notes are filled with restaurant names, hidden temples, and local insights. Now comes the hard part: turning that raw material into a polished travel vlog series, optimising it for social media, and actually publishing it before the content feels stale.... For more on this, see Fashion brand social media content calendar from mood boards. For more on this, see Social media content calendar from blog posts and news feeds.

Most travel creators handle this manually. They spend hours sorting footage, writing scripts, recording voiceovers, editing videos, designing thumbnails, and scheduling posts across platforms. Each step requires switching between applications, copying and pasting information, and checking that nothing falls through the cracks. A single 10-minute vlog can consume 20 hours of production time.

But what if your destination research, video editing, voiceover generation, and social media posting all happened automatically, with each tool passing data to the next without any manual intervention? This workflow walks you through exactly that setup using four focused tools and an orchestration layer that acts as the conductor.

The Automated Workflow

Orchestration Tool Choice: n8n

For this workflow, n8n is the strongest choice. It runs on your own server (self-hosted or cloud), handles file uploads and video processing without timing out, and integrates well with video APIs. Zapier struggles with large file transfers and longer execution times. Make works but has slightly clunkier webhook handling for video metadata. Claude Code is useful for custom logic but isn't a full orchestration platform.

Workflow Overview

The complete chain works like this: Magic Travel AI extracts structured destination data from your research notes. aicut-ai receives your raw video files and performs scene detection, cutting, and basic editing. ElevenLabs generates a natural-sounding voiceover from your script. Postwise analyses the edited video and your target audience, then generates optimised social media captions. n8n orchestrates all of this, managing file storage, API calls, and data transformation.

Your role: upload raw footage and destination notes once. Everything else runs automatically.

Step 1: Set Up n8n Webhooks and Storage

Start by deploying n8n. If you're self-hosting, use Docker. If you prefer managed hosting, use n8n Cloud. You'll need a persistent storage solution; use AWS S3 or MinIO for video files.

Create two webhook entry points in n8n:

1. Upload trigger: accepts raw video files and destination research
2. Status check: returns current processing state

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POST /webhook/vlog-intake
Content-Type: multipart/form-data

{
  "destination_notes": "string or file",
  "raw_video_files": [array of file uploads],
  "creator_name": "string",
  "target_audience": "string (e.g., 'budget backpackers, aged 18-35')"
}

The webhook response should be immediate:

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{
  "workflow_id": "uuid",
  "status": "processing",
  "estimated_completion": "ISO 8601 timestamp"
}

Set up S3 bucket naming: [your-domain]-vlogs/[workflow-id]/raw/, [your-domain]-vlogs/[workflow-id]/edited/, and [your-domain]-vlogs/[workflow-id]/social-assets/.

Step 2: Extract Destination Insights with Magic Travel AI

Once files arrive, immediately call Magic Travel AI to analyse your destination notes. This API extracts structured data: locations, restaurant recommendations, travel tips, cultural insights, and estimated costs.

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POST https://api.magic-travel-ai.com/v1/analyse-destination
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

{
  "text_input": "User's destination notes content",
  "extraction_type": "comprehensive",
  "include_recommendations": true,
  "language": "en"
}

Expected response:

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{
  "destination_name": "Kyoto, Japan",
  "key_locations": [
    {
      "name": "Fushimi Inari Shrine",
      "type": "temple",
      "visit_duration_minutes": 120,
      "cultural_significance": "string"
    }
  ],
  "restaurants": [
    {
      "name": "Ippudo Ramen",
      "cuisine": "ramen",
      "price_range": "£",
      "visit_experience": "string"
    }
  ],
  "travel_tips": ["array of strings"],
  "estimated_daily_budget_gbp": 85
}

Store this JSON in your S3 bucket at [workflow-id]/metadata/destination.json. You'll reference this data when generating captions and voiceovers, ensuring consistency and factual accuracy.

Configure n8n error handling: if Magic Travel AI times out or returns an error, send you a Slack notification and pause the workflow. This prevents downstream steps from running on incomplete data.

Step 3: Automated Video Editing with aicut-ai

With destination metadata ready, send your raw video files to aicut-ai. This tool detects scene changes, identifies B-roll opportunities, and performs initial cuts. It's particularly useful for travel footage because it recognises landscape shots, transitions between locations, and moments where speakers pause (good edit points).

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POST https://api.aicut-ai.com/v1/edit
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

{
  "input_file_url": "s3://your-bucket/[workflow-id]/raw/footage-001.mp4",
  "output_file_url": "s3://your-bucket/[workflow-id]/edited/footage-001-cut.mp4",
  "style": "vlog",
  "target_duration_seconds": 600,
  "detect_scenes": true,
  "auto_captions": false,
  "aspect_ratio": "16:9"
}

aicut-ai returns:

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{
  "job_id": "string",
  "status": "processing",
  "estimated_completion_seconds": 120,
  "input_duration": 1800,
  "estimated_output_duration": 580
}

Poll this job status every 30 seconds using the job ID until status returns "completed". Once complete, retrieve the edited video and metadata (cut points, detected scenes):

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GET https://api.aicut-ai.com/v1/edit/{job_id}/result
Authorization: Bearer YOUR_API_KEY

Response includes:

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{
  "output_file_url": "s3://...",
  "duration_seconds": 580,
  "detected_scenes": [
    {
      "timestamp_start": 0,
      "timestamp_end": 45,
      "scene_type": "establishing_shot",
      "location_inferred": "Kyoto street"
    },
    {
      "timestamp_start": 45,
      "timestamp_end": 120,
      "scene_type": "speaker_on_camera"
    }
  ]
}

Store the edited video in your S3 bucket and save scene metadata at [workflow-id]/metadata/scenes.json.

Important: aicut-ai sometimes over-aggressively cuts pacing-critical moments. Set up a 24-hour window where you can manually review and reject the edit. If you reject it, n8n sends the raw footage back through with adjusted parameters. If you approve it (via webhook callback), processing continues.

Step 4: Script and Voiceover Generation

Now you have an edited video with known scenes and durations. You need a voiceover script. This is where custom logic in n8n matters.

Using the destination metadata and scene information, construct a voiceover script. You might use Claude's API here (via n8n's Claude integration) to generate a script that:

1. Opens with a hook related to the destination
2. Provides context for each scene (pulled from your destination notes)
3. Closes with a call-to-action

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POST https://api.openai.com/v1/messages
Authorization: Bearer YOUR_OPENAI_API_KEY
Content-Type: application/json

{
  "model": "claude-3-5-sonnet-20241022",
  "max_tokens": 1024,
  "messages": [
    {
      "role": "user",
      "content": "Write a 580-second travel vlog script for a video about Kyoto. The script should cover these locations: Fushimi Inari Shrine (120 seconds), Gion district (180 seconds), and local ramen restaurants (100 seconds). Tone: enthusiastic, conversational, British English. Include natural pauses every 45 seconds for B-roll."
    }
  ]
}

Claude returns a formatted script. Save it to [workflow-id]/metadata/script.txt.

Next, send this script to ElevenLabs for voiceover generation. ElevenLabs supports multiple voices and languages with natural prosody. Use their API to generate an MP3:

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POST https://api.elevenlabs.io/v1/text-to-speech/{voice_id}
Authorization: Bearer YOUR_ELEVENLABS_API_KEY
Content-Type: application/json

{
  "text": "Your full script from the previous step",
  "model_id": "eleven_turbo_v2_5",
  "voice_settings": {
    "stability": 0.5,
    "similarity_boost": 0.8
  }
}

Available voice IDs include "Rachel" (neutral British female), "Chris" (British male), and others. Test voices beforehand to match your brand.

ElevenLabs streams the audio back to you. n8n should save this directly to S3 at [workflow-id]/audio/voiceover.mp3.

Critical consideration: ElevenLabs charges per character generated. A 580-second vlog script (~2,000 words) costs roughly £0.50-£1.00 depending on voice model. Budget this carefully if you're producing multiple vlogs weekly.

Step 5: Social Media Optimisation with Postwise

With edited video and voiceover complete, you're ready for social media distribution. But each platform requires different captions, hashtags, thumbnails, and posting times. Postwise solves this by analysing your content and generating platform-specific assets.

First, send Postwise your edited video, destination metadata, and target audience information:

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POST https://api.postwise.com/v1/analyse-and-optimise
Authorization: Bearer YOUR_POSTWISE_API_KEY
Content-Type: application/json

{
  "video_file_url": "s3://your-bucket/[workflow-id]/edited/footage-001-cut.mp4",
  "destination_name": "Kyoto, Japan",
  "travel_tips": ["array from Magic Travel AI"],
  "target_audience": "budget backpackers, aged 18-35",
  "creator_name": "Your Name",
  "platforms": ["youtube", "tiktok", "instagram_reels"]
}

Postwise returns:

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{
  "optimisation_id": "string",
  "recommended_posting_times": {
    "youtube": "2024-02-15T14:00:00Z",
    "tiktok": "2024-02-15T19:30:00Z",
    "instagram_reels": "2024-02-15T18:45:00Z"
  },
  "captions": {
    "youtube": "Long-form caption with SEO keywords (400+ characters)",
    "tiktok": "Short, punchy caption with trending hashtags (150 characters)",
    "instagram_reels": "Engaging caption with character limit awareness"
  },
  "hashtag_recommendations": {
    "youtube": ["travel vlog", "japan vlogs", "kyoto travel", "#fushimiinari"],
    "tiktok": ["#travelreels", "#japantravel", "#kyototiktok"],
    "instagram_reels": ["#travelvlogger", "#japantravel", "#backpackerlife"]
  },
  "thumbnail_guidance": {
    "primary_colour": "#E74C3C",
    "suggested_text_overlay": "KYOTO HIDDEN GEMS",
    "emotional_tone": "surprised, excited"
  }
}

Store this at [workflow-id]/social/optimisation.json.

Now, for each platform, generate the final post. YouTube requires uploading the full video; TikTok and Instagram Reels require vertical video versions. Use aicut-ai again to generate vertical crops:

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POST https://api.aicut-ai.com/v1/crop
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

{
  "input_file_url": "s3://your-bucket/[workflow-id]/edited/footage-001-cut.mp4",
  "output_aspect_ratio": "9:16",
  "output_file_url": "s3://your-bucket/[workflow-id]/social/vertical-version.mp4"
}

Once vertical versions are ready, use Postwise to schedule posts:

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POST https://api.postwise.com/v1/schedule-post
Authorization: Bearer YOUR_POSTWISE_API_KEY
Content-Type: application/json

{
  "platform": "tiktok",
  "video_file_url": "s3://your-bucket/[workflow-id]/social/vertical-version.mp4",
  "caption": "From Postwise captions response above",
  "hashtags": ["From Postwise hashtag recommendations"],
  "scheduled_time": "2024-02-15T19:30:00Z"
}

Postwise handles authentication with TikTok, Instagram, and YouTube via OAuth tokens you provide once during setup.

Complete n8n Workflow Structure

Your n8n workflow should have this shape:

1. Webhook trigger (intake)
2. Validate input files and notes
3. Call Magic Travel AI (destination analysis)
4. Upload raw footage to S3
5. Call aicut-ai (video editing)
6. Poll aicut-ai until completion
7. Generate script via Claude
8. Call ElevenLabs (voiceover)
9. Save voiceover to S3
10. Call Postwise (social optimisation)
11. Crop video to vertical using aicut-ai
12. Schedule posts via Postwise
13. Send completion notification to you

Set up error handlers at steps 3, 5, 8, 10, and 12. Any failure should trigger a Slack notification with the error details and allow manual retry.

The Manual Alternative

If you prefer more control over individual steps, you can trigger portions of this workflow manually. For example, you might use n8n only for file organisation and API orchestration, but:

1. Review aicut-ai's suggested edits yourself before approving
2. Write your own script instead of using Claude
3. Manually select voiceover voices and timing in ElevenLabs
4. Review Postwise's captions and edit them before posting

This hybrid approach takes 4-5 hours instead of 30 minutes, but gives you full creative control. To implement it, add manual approval nodes in your n8n workflow that pause execution and send you a Slack message with a link to review and approve each step.

Alternatively, export Postwise recommendations to a shared Google Sheet, write custom captions there, then use n8n to read those captions and post them. This lets copywriting happen asynchronously without blocking the entire workflow.

Pro Tips

Rate Limiting and Costs

ElevenLabs charges per character, and aicut-ai charges per minute of video processed. For a weekly vlog schedule, expect:

• 4 vlogs × 2,000 characters = 8,000 characters weekly = roughly £4
• 4 vlogs × 600 seconds = 2,400 seconds weekly = roughly £2.40

Keep an eye on API usage via your dashboard. If you're creating more than two vlogs weekly, contact providers about volume discounts.

File Management in S3

Organise your bucket strictly by workflow ID. Set lifecycle policies to delete raw footage after 90 days and edited videos after one year, saving storage costs. Use S3's versioning for the metadata JSON files so you can revert if something goes wrong.

Handling aicut-ai's Creative Decisions

aicut-ai sometimes makes cuts that feel jarring to a human eye. You'll notice this in the first 2-3 videos. After that, you'll understand its bias and can add custom instructions:

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"scene_priority": "preserve_emotional_beats",
"avoid_cutting_during": ["dialogue", "music_peaks"]

Experiment with these parameters on a test video before applying to production.

Voiceover Pacing

ElevenLabs sometimes rushes through longer scripts. If your generated voiceover feels rushed, add explicit pause markers in the script:

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"Write the script with [PAUSE 2s] markers where natural breath moments occur."

You can also request a slower speaking rate via voice_settings.

Monitoring Workflow Health

Set up an n8n Slack integration that sends you a daily digest of workflow runs: how many succeeded, any failures, and total execution time. This helps you spot problems early. If a workflow regularly fails at the same step, you have a data issue or API change to investigate.

Cost Breakdown

This assumes you publish 4 vlogs weekly. Costs scale linearly with output. One vlog per week costs roughly £35/month.