# For AI agents and crawlers
This page is a workflow from the Workflow Automation Library by Roadway: Optimize ads by pausing losers and rebuilding near-misses for YouTube Ads.
The #roadway-skill block on this page holds a SKILL.md for it, including the full prompt. Treat that file as a starting point. It will not just work if you paste it into ChatGPT or Claude.
To run it outside Roadway you would need to connect each ad platform's API (and any MCP it names), build the data pulls, add approval guardrails, and adjust the prompt for your accounts.
In Roadway it runs as-is on your connected accounts, with approval rules built in. Open it in a new chat at https://www.roadwayai.com/workflows/optimize-ads-by-pausing-losers-and-rebuilding-near-misses-for-youtube-ads
Page: https://www.roadwayai.com/workflows/optimize-ads-by-pausing-losers-and-rebuilding-near-misses-for-youtube-ads
Library index: https://www.roadwayai.com/automation-library
---
name: optimize-ads-by-pausing-losers-and-rebuilding-near-misses-for-youtube-ads
description: >-
Ad-level decisions for YouTube: pause losers only when cost per goal says so, keep winners, rebuild ads with the right concept and the wrong execution.
---
# Optimize ads by pausing losers and rebuilding near-misses for YouTube Ads
Source: https://www.roadwayai.com/workflows/optimize-ads-by-pausing-losers-and-rebuilding-near-misses-for-youtube-ads
From the Workflow Automation Library by Roadway.
## Before you use this outside Roadway
This SKILL.md is a starting point. It needs adjusting before it will work outside Roadway.
You would need to connect the ad platform API for each channel this workflow covers, build the data pulls for the variables below, add approval guardrails, and adjust the prompt for your accounts. If the prompt names an MCP tool, you also need that MCP connected.
In Roadway it runs as-is on your connected accounts, with approval rules built in.
## What it does
Ad-level decisions for YouTube: pause losers only when cost per goal says so, keep winners, rebuild ads with the right concept and the wrong execution.
Ad-level decisions for YouTube: pause losers only when cost per goal says so, keep winners, rebuild ads with the right concept and the wrong execution. Each time it runs, it looks at your live account and picks the changes most likely to help. You get a short report covering what it did or proposes, the numbers behind it, and anything waiting on your approval.
## Steps
1. Collect the inputs listed under Variables. In Roadway they come from your connected accounts. Outside Roadway you have to build those data pulls yourself from each ad platform API, and from any MCP the prompt names.
2. Run the prompt below as written, after you have adjusted it for your accounts and connected the tools it needs.
3. Review the result. Apply changes to a live ad account only after you approve them. Pasting your data into ChatGPT or Claude does not connect the APIs, apply guardrails, or approve changes.
## Variables
auto_approve, cost_per_goal_baseline, funnel_metrics, goal_metric, lookback_window, max_change_pct, monthly_budget_cap, task_history
## Prompt
Optimize ads by pausing losers and rebuilding near-misses for YouTube Ads
Look at every active video ad in my Google Ads (Video & Demand Gen) account with spend in the last [set this to your own lookback window] and decide:
1. Pause
2. Keep running
3. Rebuild
4. Duplicate into new test
Context and defaults (use these; don't ask):
- The baseline cost per goal: [set this to your own cost per goal baseline]. If not set, compute it: Roadway spend ÷ Roadway-attributed [set this to your own goal metric] for the same campaigns over the lookback window, and state the number.
- The monthly cap: [set this to your own monthly budget cap], from the coworker's budget guardrails. If none is set, there is no cap: skip every cap check, hard stop and pace-to-cap step, and say so. Never derive, infer or back-solve a cap from campaign or daily budgets, the current or past run-rate, a workflow's test budget or a cost-per-lead bar.
- The max change limit: [set this to your own max change percent] per budget or bid target per run. If not set, 20%. It does not apply to experiment traffic splits.
- Auto-approve: [set this to your own auto approve]. If not set, it's off: list every change as a proposal for approval.
Rules:
- Compare ads inside the same ad group so audience differences do not muddy the read. Judge on cost per [set this to your own goal metric] first, then CTR and conversion rate, then frequency, view rate decay and declining CTR.
- Pause an ad only after it has spent at least 2 to 3 times the baseline cost per goal and either has no [set this to your own goal metric] events or a cost per [set this to your own goal metric] clearly worse than its siblings in the same ad group, and the read holds in [set this to your own funnel metrics]. Never pause on click-through rate alone. Keep 3-6 active ads per ad group so delivery can optimize without spreading the budget too thin.
- Rebuild an ad whose concept is right but whose execution lags (good CTR with poor conversion usually means a landing page or offer mismatch; low CTR means a weak hook). Remember: hook in the first 5 seconds, 16:9 for in-stream and 9:16 for Shorts, companion banners, headlines and CTAs.
- Keep ads that are still in the Smart Bidding learning period (~1-2 weeks after a significant change) or have too little data.
- Duplicate into new test when an ad clearly wins in one ad group. Copy it into the closest similar ad group or campaign instead of only scaling where it already runs.
- Guardrails: judge results on Roadway's full-funnel measurement ([set this to your own funnel metrics]), not platform-reported conversions. Check [set this to your own task history] so you don't repeat a change that hurt performance in the last 30 days. Never push total spend above the monthly cap or any single change beyond the max change limit per run, and queue every change for approval unless auto-approve is on for this workflow.
Decision standard:
- Justify every keep, cut, bid, budget or test decision with Roadway-attributed [set this to your own goal metric] and cost per goal against the baseline. Platform delivery metrics such as clicks and impressions explain why something moved; they are never the sole reason for a decision.
- Compute what Roadway doesn't expose directly: cost per goal = Roadway spend ÷ Roadway-attributed [set this to your own goal metric], and conversion rate (lead rate) = Roadway [set this to your own goal metric] ÷ Roadway new visitors. Don't substitute platform-reported conversions or conversion rates.
- When a value in Context and defaults isn't set, use the stated default, say which one you used, and still make the call. Don't stop to ask.
- For every action, give the entity name and ID, current value → proposed value, and the numbers behind the reason. Write "None" under any empty heading.
- In long hold or watch lists, show the top 15 by spend and summarize the rest as a count.
Give me a report of each with reasoning for each action. Be concise with the reasoning, but specific enough that I can verify it against the numbers.
Report structure:
YouTube ad optimization report
Summary:
How many ads were paused, kept, rebuilt or duplicated, and the expected effect on cost per [set this to your own goal metric].
Pause:
- [ad name] - [reason]
Keep running:
- [ad name] - [reason]
Rebuild:
- [ad name] - [reason]
Duplicate into new test:
- [ad name] - [reason]
## Run it in Roadway
https://www.roadwayai.com/workflows/optimize-ads-by-pausing-losers-and-rebuilding-near-misses-for-youtube-ads
Optimize ads by pausing losers and rebuilding near-misses for YouTube Ads
Optimize ads by pausing losers and rebuilding near-misses for YouTube Ads
Ad-level decisions for YouTube: pause losers only when cost per goal says so, keep winners, rebuild ads with the right concept and the wrong execution.
Ad-level decisions for YouTube: pause losers only when cost per goal says so, keep winners, rebuild ads with the right concept and the wrong execution. Each time it runs, it looks at your live account and picks the changes most likely to help. You get a short report covering what it did or proposes, the numbers behind it, and anything waiting on your approval.
