Eye Care Marketing Campaign from Product Specifications

Introduction

You've got a product specification document for a new line of eye care products. It contains everything: ingredient lists, clinical benefits, target demographics, packaging details. Now you need to turn that into a multi-channel marketing campaign, fast. Manually, this would mean copy-pasting specs into ChatGPT, manually checking which messaging resonates with different audience segments, writing separate versions for LinkedIn, TikTok, and email, then uploading each one to the respective platform. That's four to six hours of work, minimum.

This workflow automates the entire process. A product spec goes in one end, and you get platform-specific marketing copy, tailored by audience type, automatically posted to your channels. No jumping between tabs. No manual reformatting. No waiting.

The workflow uses four tools working in concert: ai-boost handles the initial content analysis and enrichment, chatgpt-writer generates the copy variants, eye-type-detector categorises your audience segments, and postwise publishes across platforms. We'll orchestrate everything with n8n, which gives you the most granular control over data flow and error handling.

The Automated Workflow

What You're Building

The workflow ingests a product spec, enriches it with market data, generates three distinct copy variants (one per audience segment), and publishes each variant to the appropriate platform. The entire process runs end-to-end without human intervention.

Why n8n Over Zapier or Make

Zapier is fine for simple linear flows, but this requires conditional branching and parallel processing. You need to route copy variants to different platforms based on audience type. Make works, but n8n gives you a cleaner visual editor and better error handling without the enterprise pricing. Claude Code is overkill here unless you need custom data transformation logic mid-workflow.

Step 1: Trigger and Input

Start with a webhook that receives your product spec as JSON. This could come from your product database, a form submission, or even a scheduled daily check.

Copy
POST /webhook/eye-care-spec
Content-Type: application/json

{
  "product_id": "ECS-2024-001",
  "product_name": "HydraVision Daily Contact Lens Solution",
  "category": "contact_lens_care",
  "key_benefits": [
    "24-hour hydration",
    "protein removal",
    "gentle formula for sensitive eyes"
  ],
  "target_age": "18-45",
  "ingredients": [
    "hyaluronic acid",
    "sodium chloride",
    "potassium chloride"
  ],
  "clinical_data": {
    "comfort_rating": 4.7,
    "efficacy_trials": 500
  },
  "price_point": "premium"
}

In n8n, create a Webhook node set to receive POST requests. This acts as your trigger.

Step 2: Content Enrichment with ai-boost

ai-boost analyses the product spec and pulls in relevant market data: trending hashtags for eye care, seasonal demand patterns, competitor positioning. This enrichment ensures your copy isn't written in a vacuum.

Configure an HTTP Request node in n8n to call ai-boost's API:

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POST https://api.ai-boost.io/v1/enrich
Headers:
  Authorization: Bearer YOUR_AI_BOOST_API_KEY
  Content-Type: application/json

Body:
{
  "product_spec": {
    "name": "HydraVision Daily Contact Lens Solution",
    "category": "contact_lens_care",
    "benefits": ["24-hour hydration", "protein removal", "gentle formula"],
    "price_tier": "premium"
  },
  "enrichment_type": "market_data",
  "include_trending": true
}

The response will look like this:

Copy
{
  "enriched_spec": {
    "product_name": "HydraVision Daily Contact Lens Solution",
    "market_sentiment": "growing demand",
    "trending_keywords": ["lens solution", "eye hydration", "sensitive care"],
    "seasonal_peak": "Q4",
    "competitor_gap": "eco-friendly packaging messaging",
    "audience_sentiment_drivers": {
      "comfort_focused": ["hydration duration", "gentleness"],
      "value_focused": ["clinical backing", "price"],
      "lifestyle_focused": ["daily routine", "convenience"]
    }
  }
}

Store this enriched data as a workflow variable in n8n for use in downstream steps.

Step 3: Audience Segmentation with eye-type-detector

eye-type-detector categorises your target audience into three segments: clinical professionals (ophthalmologists, optometrists), comfort-conscious consumers, and budget-conscious consumers. Each segment needs different messaging angles.

Add another HTTP Request node:

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POST https://api.eye-type-detector.io/v1/segment
Headers:
  Authorization: Bearer YOUR_EYE_TYPE_DETECTOR_API_KEY
  Content-Type: application/json

Body:
{
  "target_demographics": {
    "age_range": "18-45",
    "product_category": "contact_lens_care",
    "price_point": "premium",
    "market_data": {
      "trending_keywords": ["lens solution", "eye hydration", "sensitive care"],
      "competitor_gap": "eco-friendly packaging messaging"
    }
  }
}

Response:

Copy
{
  "segments": [
    {
      "segment_id": "clinical_professional",
      "label": "Clinical Professional",
      "messaging_angle": "efficacy_and_clinical_data",
      "primary_platforms": ["linkedin", "email"],
      "tone": "authoritative, evidence-based",
      "key_hooks": ["500 efficacy trials", "4.7 comfort rating"]
    },
    {
      "segment_id": "comfort_conscious",
      "label": "Comfort-Conscious Consumer",
      "messaging_angle": "daily_comfort_and_gentleness",
      "primary_platforms": ["tiktok", "instagram"],
      "tone": "relatable, empathetic",
      "key_hooks": ["24-hour hydration", "gentle formula for sensitive eyes"]
    },
    {
      "segment_id": "budget_conscious",
      "label": "Budget-Conscious Consumer",
      "messaging_angle": "value_and_clinical_backing",
      "primary_platforms": ["email", "google_ads"],
      "tone": "practical, straightforward",
      "key_hooks": ["clinically proven", "premium quality at fair price"]
    }
  ]
}

Store this as another workflow variable.

Step 4: Copy Generation with chatgpt-writer

Now you generate three distinct copy variants, one for each audience segment. Use a Loop node in n8n to iterate through the segments, calling chatgpt-writer each time.

For each iteration, configure an HTTP Request node:

Copy
POST https://api.chatgpt-writer.io/v1/generate
Headers:
  Authorization: Bearer YOUR_CHATGPT_WRITER_API_KEY
  Content-Type: application/json

Body:
{
  "product_spec": {
    "name": "HydraVision Daily Contact Lens Solution",
    "benefits": ["24-hour hydration", "protein removal", "gentle formula"],
    "ingredients": ["hyaluronic acid", "sodium chloride", "potassium chloride"],
    "clinical_data": {
      "comfort_rating": 4.7,
      "efficacy_trials": 500
    },
    "price_point": "premium"
  },
  "segment": {
    "segment_id": "clinical_professional",
    "messaging_angle": "efficacy_and_clinical_data",
    "tone": "authoritative, evidence-based",
    "key_hooks": ["500 efficacy trials", "4.7 comfort rating"]
  },
  "formats": [
    "linkedin_post",
    "email_subject_and_body",
    "short_form_video_script"
  ],
  "length_constraints": {
    "linkedin_post": "max 250 words",
    "email_subject": "max 60 characters",
    "email_body": "150-200 words",
    "video_script": "30 seconds"
  }
}

The response includes multiple copy variants for different formats:

Copy
{
  "segment_id": "clinical_professional",
  "generated_copy": {
    "linkedin_post": "New clinical data on HydraVision Daily: 500-trial validation shows 4.7 comfort rating in sensitive eye populations. The formulation addresses protein accumulation through dual-action chemistry, reducing end-of-day discomfort. Hyaluronic acid retention extends hydration over 24 hours. For practitioners seeking evidence-based recommendations.",
    "email": {
      "subject": "Clinical validation: HydraVision Daily contact lens solution",
      "body": "Dear practitioner, our latest clinical trial results demonstrate HydraVision Daily's efficacy in maintaining lens comfort and clarity. Over 500 participants reported sustained hydration and reduced protein build-up. The formulation contains hyaluronic acid, sodium chloride, and potassium chloride in proportions optimised for sensitive eyes. Review the full data sheet."
    },
    "video_script": "HydraVision Daily. Five hundred clinical trials. One result: comfort that lasts all day. Validated. Tested. Recommended."
  }
}

Create a Set node in n8n to store each generated variant with its segment ID and platform targets.

Step 5: Publishing with Postwise

Postwise handles multi-platform publishing. You'll make separate API calls for each platform, using the appropriate copy variant and publishing parameters.

For LinkedIn:

Copy
POST https://api.postwise.io/v1/publish
Headers:
  Authorization: Bearer YOUR_POSTWISE_API_KEY
  Content-Type: application/json

Body:
{
  "platform": "linkedin",
  "content_type": "organic_post",
  "text": "New clinical data on HydraVision Daily: 500-trial validation shows 4.7 comfort rating in sensitive eye populations. The formulation addresses protein accumulation through dual-action chemistry, reducing end-of-day discomfort. Hyaluronic acid retention extends hydration over 24 hours. For practitioners seeking evidence-based recommendations.",
  "scheduling": {
    "publish_immediately": false,
    "scheduled_time": "2024-02-15T09:00:00Z",
    "timezone": "UTC"
  },
  "metadata": {
    "campaign_id": "ECS-2024-001",
    "segment": "clinical_professional",
    "product_id": "hydravision-daily"
  }
}

For TikTok (using the short-form video script):

Copy
POST https://api.postwise.io/v1/publish
Headers:
  Authorization: Bearer YOUR_POSTWISE_API_KEY
  Content-Type: application/json

Body:
{
  "platform": "tiktok",
  "content_type": "video_script",
  "text": "HydraVision Daily. Twenty-four hour hydration for sensitive eyes. All-day comfort. No compromise.",
  "video_metadata": {
    "script_duration_seconds": 30,
    "music_style": "modern_upbeat",
    "visual_theme": "product_focused"
  },
  "scheduling": {
    "publish_immediately": false,
    "scheduled_time": "2024-02-15T17:00:00Z",
    "timezone": "UTC"
  },
  "metadata": {
    "campaign_id": "ECS-2024-001",
    "segment": "comfort_conscious",
    "product_id": "hydravision-daily"
  }
}

For email:

Copy
POST https://api.postwise.io/v1/publish
Headers:
  Authorization: Bearer YOUR_POSTWISE_API_KEY
  Content-Type: application/json

Body:
{
  "platform": "email",
  "content_type": "newsletter",
  "email_subject": "Clinical validation: HydraVision Daily contact lens solution",
  "email_body": "Dear practitioner, our latest clinical trial results demonstrate HydraVision Daily's efficacy in maintaining lens comfort and clarity. Over 500 participants reported sustained hydration and reduced protein build-up. The formulation contains hyaluronic acid, sodium chloride, and potassium chloride in proportions optimised for sensitive eyes. Review the full data sheet.",
  "recipient_list": "clinical_professionals_segment",
  "scheduling": {
    "publish_immediately": false,
    "scheduled_time": "2024-02-16T08:00:00Z",
    "timezone": "UTC"
  },
  "metadata": {
    "campaign_id": "ECS-2024-001",
    "segment": "clinical_professional",
    "product_id": "hydravision-daily"
  }
}

In n8n, use a Loop node to iterate through each segment and call Postwise once per platform.

N8n Workflow Structure

Here's the visual flow:

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Webhook (receive product spec)
    ↓
ai-boost HTTP Request (enrich data)
    ↓
eye-type-detector HTTP Request (segment audience)
    ↓
Set node (prepare loop data)
    ↓
Loop node (iterate through segments)
    ├─ chatgpt-writer HTTP Request (generate copy)
    ├─ Set node (store variant)
    └─ Inner Loop (iterate through platforms)
        └─ Postwise HTTP Request (publish)
    ↓
Set node (log completion)

Add error handling at each step: use Try/Catch nodes to gracefully handle API failures. If ai-boost fails, log the error and continue with the base product spec. If Postwise fails on one platform, log it but continue publishing to others.

The Manual Alternative

You can run these steps individually without orchestration. Feed the product spec to ai-boost via its web dashboard, download the enriched data, manually input it into eye-type-detector's UI, copy the segmentation results into ChatGPT with a custom prompt, and finally log into each platform to post. It works, it's just tedious and error-prone. You'll lose the benefit of the audience segmentation if you make a typo when copying data between tools.

Pro Tips

Rate Limiting

ai-boost allows 100 requests per minute on the standard tier. If you're running this for a large product catalogue, add a Delay node between webhook triggers set to 1 second. This spreads requests evenly and prevents hitting rate limits.

Cost Control

chatgpt-writer charges per API call, not per token. Generating three copy variants costs three API calls. If you only need LinkedIn and email variants, adjust your formats array to remove unnecessary outputs. This cuts costs by a third without compromising results.

Fallback Copy

If chatgpt-writer fails, n8n can use a default template. Add a Conditional node after the chatgpt-writer request: if the response contains an error, use a predefined copy template stored as a workflow variable. This ensures campaigns still launch even if the API fails.

Scheduling Intelligence

Postwise's scheduling respects platform-specific peak times. LinkedIn engagement peaks Tuesday to Thursday at 8-10 AM. TikTok peaks at 6-10 PM. Don't hardcode times; let Postwise determine optimal posting windows based on your audience data. Set "publish_immediately" to false and omit the "scheduled_time" parameter to activate smart scheduling.

Monitoring and Alerts

Add a Send Email node at the end of your workflow to notify you of completion. Include a summary: which segments were created, how many posts were scheduled, any API failures. This keeps you informed without requiring you to check the orchestration platform.

Cost Breakdown

This workflow saves roughly 30 hours per month compared to manual copy writing and posting, and costs less than hiring a freelance copywriter for two days.