Seamless Webflow Blog Migration: Automating Large-Scale Content Transfers

When a website evolves, content migration quickly becomes a challenge—especially when data structures change, making a simple copy-paste impossible. Recently, we supported a client in migrating their entire Webflow blog to a new Webflow site while adapting each element to a redefined data model.

The goal was clear: How do you transfer hundreds of articles, along with their categories and subcategories, without losing data or requiring weeks of manual work? The solution was to leverage the Webflow API and automation with Python to ensure a smooth and structured transition.

Redefining the Data Structure

The original blog, with over 1,000 articles, categorized its content using separate reference fields for categories and subcategories. The new site, however, consolidated this information into a single multi-reference field, requiring a complete rethinking of how relationships between elements were managed.

Additionally, some articles were created with generic names or numbers as titles, necessitating a harmonization process to ensure consistency in the new database.

A manual migration would have taken weeks, increasing the risk of errors and inconsistencies. Automating the process was the only viable solution.

A Webflow API and Python-Powered Solution

The main objective was to develop a script that could autonomously handle the entire migration using the Webflow v2 API while integrating intelligent processing steps.

This approach was divided into three key phases:

1. Extracting content from the old site via the Webflow API.
2. Transforming data to adapt structures and correct inconsistencies.
3. Injecting articles into the new site with precise category and subcategory mapping.

Automating the Migration with Python and Webflow API

Step 1: Extracting Data from the Old Site

The first step was retrieving all existing articles along with their metadata. A simple API request enabled us to extract structured content efficiently.

Here’s a sample of the extraction script using a GET request to Webflow’s API:

import requests  

def get_items(collection_id, headers):  
    url = f"https://api.webflow.com/v2/collections/{collection_id}/items"  
    response = requests.get(url, headers=headers)  
    if response.status_code == 200:  
        return response.json().get("items", [])  
    else:  
        print(f"Error retrieving articles: {response.status_code}")  
        return []  

Step 2: Transforming Data

Once the articles were retrieved, the next step was to refine the data by replacing incorrect or missing titles and consolidating subcategories into a multi-reference field.

Each article was analyzed to ensure compatibility with the new structure:

def transform_data(item):  
    name = item["fieldData"]["titel"] if item["fieldData"]["name"].isdigit() else item["fieldData"]["name"]  
    subcategories = [  
        item["fieldData"].get("subcat-1"),  
        item["fieldData"].get("subcat-2"),  
        item["fieldData"].get("subcat-3"),  
        item["fieldData"].get("subcat-4")  
    ]  
    return {"name": name, "slug": item["fieldData"]["slug"], "subcategories": list(filter(None, subcategories))}  

Step 3: Injecting Data into the New Site

With the refined data, each article was then injected into the new Webflow site, ensuring proper category and subcategory mapping using a POST request:

def post_item(collection_id, headers, data):  
    url = f"https://api.webflow.com/v2/collections/{collection_id}/items"  
    response = requests.post(url, headers=headers, json={"fields": data})  
    if response.status_code == 200:  
        print(f"Article added: {data['name']}")  
    else:  
        print(f"Error uploading data: {response.status_code} - {response.text}")  

Results and Benefits

Within just a few hours, the entire blog was successfully migrated, including the complex relationships between categories and subcategories.

Key Benefits

• Significant time savings: A migration that would have taken weeks manually was completed in just one day.
• No data loss: Automation ensured that all content and relationships were preserved.
• Scalability: The script can be reused for future migrations, reducing operational overhead.

Looking Ahead

‍This case study highlights how a migration, often perceived as a technical burden, can be streamlined with the right tools. By combining Webflow’s API with Python scripting, it’s possible to structure content migrations efficiently, eliminating repetitive tasks and allowing teams to focus on strategic aspects instead.The question is no longer if migrations should be automated, but how to leverage the right approach for a seamless and reliable transition.