# For AI agents and crawlers
This page is a workflow from the Workflow Automation Library by Roadway: Optimize location targeting for LinkedIn 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-location-targeting-for-linkedin-ads
Page: https://www.roadwayai.com/workflows/optimize-location-targeting-for-linkedin-ads
Library index: https://www.roadwayai.com/automation-library
---
name: optimize-location-targeting-for-linkedin-ads
description: >-
Shifts LinkedIn spend toward the regions that convert efficiently and excludes the ones that never do.
---
# Optimize location targeting for LinkedIn Ads
Source: https://www.roadwayai.com/workflows/optimize-location-targeting-for-linkedin-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
Shifts LinkedIn spend toward the regions that convert efficiently and excludes the ones that never do.
Shifts LinkedIn spend toward the regions that convert efficiently and excludes the ones that never do. 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, cost_per_goal_baseline, excluded_geos, funnel_metrics, goal_metric, lookback_window, max_change_pct, monthly_budget_cap, serviceable_regions, target_geos, task_history
## Prompt
Optimize location targeting for LinkedIn Ads
Break down my LinkedIn Campaign Manager performance by country, region and metro over the last [set this to your own lookback window] and decide for each location:
1. Increase investment
2. Decrease investment
3. Exclude
4. Keep
Context and defaults (use these; don't ask):
- The target locations: [set this to your own target geos]. If not set, the currently targeted locations.
- The excluded locations: [set this to your own excluded geos]. If not set, keep current location exclusions.
- 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 serviceable regions: [set this to your own serviceable regions]. If not set, the currently targeted regions.
- 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:
- Only target locations in the target locations and always exclude the excluded locations. Anything delivering outside them is a setup error to fix right away.
- Location options on LinkedIn: location targeting by "Recent or permanent location" vs "Permanent location".
- Increase investment (a separate campaign with its own budget for big markets) where cost per goal is clearly under the baseline for long enough to trust it, with at least 10 goal events. Decrease where cost per goal is over the cost per goal guardrail after 1.5x baseline spend. Exclude locations with 2x baseline spend and no [set this to your own goal metric], unless they are strategic in the target locations.
- Watch for timezone and language mismatches, and for regions where the product, shipping or sales coverage does not exist (the serviceable regions).
- 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:
LinkedIn location optimization report
Summary:
Spend and cost per goal by location, the waste removed, and where to invest more.
Increase investment:
- [location] - [reason]
Decrease investment:
- [location] - [reason]
Exclude:
- [location] - [reason]
Keep:
- [location] - [reason]
## Run it in Roadway
https://www.roadwayai.com/workflows/optimize-location-targeting-for-linkedin-ads
Shifts LinkedIn spend toward the regions that convert efficiently and excludes the ones that never do. 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.
