BrowserAct Movie Article Builder

Make AI Movie Article Builder helps you automatically turn raw movie data into fully structured, publish-ready HTML articles—without manually researching IMDb pages or writing content from scratch.

When producing movie-related content at scale, key information such as movie details, FAQs, images, and user reviews is often scattered across multiple IMDb pages. Manually collecting, organizing, and rewriting this data into a consistent article format is time-consuming and difficult to scale.
This workflow solves that problem by orchestrating data extraction, AI content generation, and structured output through Make.

The workflow starts from a Google Sheets movie list. Each row represents a movie content task. Make reads and processes each movie individually, triggers an external data extraction workflow, and converts the collected structured data into a complete HTML article using AI.

The final result is automatically written back to Google Sheets, allowing content teams to manage, review, and publish movie articles efficiently from a single spreadsheet.

Input:

• Movie name
• Production year

Output:

• A complete, styled HTML movie article including:
• • Synopsis
  • Movie details table
  • Cast list
  • Image gallery
  • User reviews

This automation is ideal for bloggers, SEO teams, content platforms, and media projects that require scalable, repeatable, and structured movie content production.

Typical use cases include:

• Batch-generating movie blog articles
• Building SEO-driven movie content websites
• Automating content pipelines for media platforms
• Creating structured movie databases from IMDb data

Working Principle (How it works)

1. Trigger (Google Sheets):
   The workflow starts when Make reads movie records from Google Sheets. Each row contains a movie name and production year and is treated as an independent content task.
2. Task iteration (Make):
   Make uses an Iterator to process each movie one by one, ensuring scalable execution and preventing errors from affecting other tasks.
3. Data collection (BrowserAct):
   For each movie, Make triggers a BrowserAct workflow that searches IMDb, navigates to the movie page, and extracts structured data such as movie details, FAQs, images, and user reviews. The extracted data is returned as a structured JSON output.
4. Content generation (AI):
   Make sends the structured movie data to an AI model, which transforms the JSON into a complete HTML article based on predefined layout and styling rules suitable for blog publishing.
5. Result storage (Google Sheets):
   The generated HTML article is written back to the corresponding row in Google Sheets, completing the automated movie content production loop.