BrowserAct YouTube Publishing Strategy Generator

This end-to-end automation extracts YouTube channel video data, analyzes historical performance, and identifies the optimal publishing time to maximize viral potential. Using BrowserAct, the workflow dynamically scrapes all videos from a selected channel and stores Title, URL, Views, Likes, and Published Date into Google Sheets. The data is then aggregated and sent to Gemini AI with a structured analytical prompt that examines performance by day of week, hour of day, and minute. The AI model detects high-performing time windows, negative “dead zones,” and statistically significant publishing patterns. The final insights are automatically written back to a dedicated results sheet, aligned to the correct row, enabling fast review and action. This template is ideal for creators, content teams, agencies, and analysts who want a repeatable, data-driven method to optimize their YouTube publishing strategy. No manual data pulling, no repetitive analysis—everything runs end-to-end with one click.

make
BrowserAct YouTube Publishing Strategy Generator

This end-to-end automation extracts YouTube channel video data, analyzes historical performance, and identifies the optimal publishing time to maximize viral potential.

Using BrowserAct, the workflow dynamically scrapes all videos from a selected channel and stores Title, URL, Views, Likes, and Published Date into Google Sheets. The data is then aggregated and sent to Gemini AI with a structured analytical prompt that examines performance by day of week, hour of day, and minute.

The AI model detects high-performing time windows, negative “dead zones,” and statistically significant publishing patterns. The final insights are automatically written back to a dedicated results sheet, aligned to the correct row, enabling fast review and action.

This template is ideal for creators, content teams, agencies, and analysts who want a repeatable, data-driven method to optimize their YouTube publishing strategy. No manual data pulling, no repetitive analysis—everything runs end-to-end with one click.

$3.99
Last updated August 29, 2026
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How to import this workflow into Make

  1. 1Purchase or download the workflow to get the Make blueprint JSON file.
  2. 2In Make, create a new scenario, click the three-dots menu, and choose "Import Blueprint".
  3. 3Reconnect each module to your own app connections when prompted.
  4. 4Run the scenario once to verify it, then set your schedule and turn it on.

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