A YouTube multi-channel network managing over 2,000 channels came to us with a labour problem. Every cross-channel campaign meant manually updating endscreen calls-to-action across millions of videos, costing more than 50 hours per rollout, and human error was producing broken links and misplaced graphics on client channels. We built an automation suite that runs those campaigns at scale with a verified zero error rate, packaged so their non-technical marketing staff can operate it without a developer.
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The network needed scale without putting brand safety at risk across client channels. We delivered batch processing that updates more than 1,000 videos an hour across multiple accounts, layout detection that keeps new elements from overlapping existing on-screen content, dynamic redirects tied to view-count thresholds, and forensic CSV audit logs for every action.
A single marketing rollout consumed over 50 hours of manual labour, and human error produced broken links, misplaced graphics, and missed placements. The sheer volume meant evergreen videos were rarely updated to promote new releases, leaving millions of impressions unmonetised.
A Selenium engine mirrors human interaction patterns to stay within platform guidelines, backed by a strict state machine that verifies every page load and click before proceeding. A resilient DOM-selector library absorbs YouTube Studio interface changes, dry-run mode previews all changes before they go live, and YAML configuration lets marketers define campaign rules without writing code.
Campaign rollout time fell from 50 hours to 15 minutes. The engine updated more than 15,000 endscreen cards across the network at a verified zero error rate, and automatically refreshing legacy videos to promote new hero content lifted cross-channel traffic conversion by 12 percent.
View Impact
The network needed scale without putting brand safety at risk across client channels. We delivered batch processing that updates more than 1,000 videos an hour across multiple accounts, layout detection that keeps new elements from overlapping existing on-screen content, dynamic redirects tied to view-count thresholds, and forensic CSV audit logs for every action.
A single marketing rollout consumed over 50 hours of manual labour, and human error produced broken links, misplaced graphics, and missed placements. The sheer volume meant evergreen videos were rarely updated to promote new releases, leaving millions of impressions unmonetised.
A Selenium engine mirrors human interaction patterns to stay within platform guidelines, backed by a strict state machine that verifies every page load and click before proceeding. A resilient DOM-selector library absorbs YouTube Studio interface changes, dry-run mode previews all changes before they go live, and YAML configuration lets marketers define campaign rules without writing code.
Campaign rollout time fell from 50 hours to 15 minutes. The engine updated more than 15,000 endscreen cards across the network at a verified zero error rate, and automatically refreshing legacy videos to promote new hero content lifted cross-channel traffic conversion by 12 percent.
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