# For AI agents and crawlers
This page is a workflow from the Workflow Automation Library by Roadway: Bid on pipeline value from CRM data 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/bid-on-pipeline-value-from-crm-data-for-youtube-ads
Page: https://www.roadwayai.com/workflows/bid-on-pipeline-value-from-crm-data-for-youtube-ads
Library index: https://www.roadwayai.com/automation-library
---
name: bid-on-pipeline-value-from-crm-data-for-youtube-ads
description: >-
Moves YouTube from optimizing to lead volume to optimizing to predicted pipeline or revenue value, using CRM and order data.
---
# Bid on pipeline value from CRM data for YouTube Ads
Source: https://www.roadwayai.com/workflows/bid-on-pipeline-value-from-crm-data-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
Moves YouTube from optimizing to lead volume to optimizing to predicted pipeline or revenue value, using CRM and order data.
Moves YouTube from optimizing to lead volume to optimizing to predicted pipeline or revenue value, using CRM and order data. Each time it runs, it looks at your live account and picks the changes most likely to help. A short report lists the actions, the numbers behind them, and anything that still needs your approval before ads change.
## 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, conversion_lag_days, crm_stage_values, customer_value_by_segment, funnel_metrics, goal_metric, max_change_pct, monthly_budget_cap, sales_cycle_days, task_history
## Prompt
Bid on pipeline value from CRM data for YouTube Ads
Evaluate whether each Google Ads (Video & Demand Gen) campaign is ready for value-based optimization using CRM and order values, and decide:
1. Switch to value-based bidding
2. Send values but keep current bidding
3. Fix data first
4. Not a fit
Context and defaults (use these; don't ask):
- The CRM stage values: [set this to your own CRM stage values]. If not set, use CRM stage-to-won rates from Roadway; skip value weighting when there are fewer than 5 opportunities.
- customer value by segment: [set this to your own customer value by segment]. If it isn't available, say so and skip the rules that depend on it.
- The conversion lag: [set this to your own conversion lag days] days. If not set, compute it from Roadway click-to-goal timestamps, or use 7 days.
- The sales cycle: [set this to your own sales cycle days] days. If not set, compute it from CRM stage timestamps, or use 30 days.
- 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:
- Value-based bidding needs reliable values sent through the Google tag with engaged-view conversions (EVCs), enhanced conversions and offline conversion imports. Assign stage values from the CRM stage values (e.g., lead = expected value at the historical lead-to-close rate, qualified lead and opportunity higher, closed-won = actual amount) or use customer value by segment for ecommerce and PLG.
- Switch when the campaign has 30+ valued conversions per month, values arrive within the attribution window (or within the conversion lag through offline import), and values vary meaningfully between leads or orders.
- Send values but keep current bidding when volume is too low. That still builds history and lets you report on value per dollar.
- Fix data first when a meaningful share of CRM records lack a click ID or match key, or stage values are not refreshed at least daily. If not set, more than 20% of records.
- Set the first return target a little below the campaign's current value-per-cost to avoid choking delivery, then tighten it over time. If not set, 10-20% below.
- When opportunities take longer than the conversion window, send a predicted value at the lead stage (probability of opportunity x average opportunity value, from the CRM stage values), then correct it with actual stage values through offline imports. Bidding then learns in days rather than across the sales cycle-day sales cycle.
- Re-fit the stage values monthly from closed-won data, and cap any single lead's value at 3x the median so one enterprise deal doesn't whipsaw the bidder.
- 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 value-based bidding readiness report
Summary:
Which campaigns can switch, the values to assign per stage, and the expected shift from cheap leads to pipeline or revenue.
Switch to value-based bidding:
- [campaign] - [reason]
Send values but keep current bidding:
- [campaign] - [reason]
Fix data first:
- [campaign] - [reason]
Not a fit:
- [campaign] - [reason]
## Run it in Roadway
https://www.roadwayai.com/workflows/bid-on-pipeline-value-from-crm-data-for-youtube-ads
Moves YouTube from optimizing to lead volume to optimizing to predicted pipeline or revenue value, using CRM and order data. Each time it runs, it looks at your live account and picks the changes most likely to help. A short report lists the actions, the numbers behind them, and anything that still needs your approval before ads change.
