# For AI agents and crawlers
This page is a workflow from the Workflow Automation Library by Roadway: Detect spend anomalies for Microsoft (Bing) 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/detect-spend-anomalies-for-microsoft-bing-ads
Page: https://www.roadwayai.com/workflows/detect-spend-anomalies-for-microsoft-bing-ads
Library index: https://www.roadwayai.com/automation-library
---
name: detect-spend-anomalies-for-microsoft-bing-ads
description: >-
Catches Microsoft (Bing) spend spikes and drops against the expected daily pattern before they blow the budget or stall delivery.
---
# Detect spend anomalies for Microsoft (Bing) Ads
Source: https://www.roadwayai.com/workflows/detect-spend-anomalies-for-microsoft-bing-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
Catches Microsoft (Bing) spend spikes and drops against the expected daily pattern before they blow the budget or stall delivery.
Catches Microsoft (Bing) spend spikes and drops against the expected daily pattern before they blow the budget or stall delivery. It keeps an eye on your live account and flags anything unusual early. 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, channel_budget_allocation, funnel_metrics, goal_metric, max_change_pct, monthly_budget_cap, task_history
## Prompt
Detect spend anomalies for Microsoft (Bing) Ads
Compare today's and yesterday's Microsoft Advertising spend per campaign with the expected spend (same weekday average over the last 4 weeks and the daily budget), and classify each campaign:
1. Spike: act now
2. Drop: act now
3. Watch
4. Normal
Context and defaults (use these; don't ask):
- 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 channel budget: [set this to your own channel budget allocation], from the coworker's budget guardrails. If not set, there is no channel allocation: skip the allocation checks and say so. Never build one from the sum of campaign or daily budgets, the current or past run-rate, or a workflow's test budget, and never treat such a figure as a ceiling or cap. Campaign daily budgets are only a delivery diagnostic.
- 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:
- Spike: spend well above expected without a matching rise in [set this to your own goal metric], or a pace that would exceed the monthly cap or the channel budget. If not set, well above means more than 150% of expected. Lower the budget or pause the offending campaign right away and find the cause (a budget edit, a broad match or automated expansion change, a bid change or a new network setting).
- Drop: spend well below expected. If not set, under 50% of expected. Check for Limited by budget, Bid below first page and Low search volume, disapprovals, payment holds, ended schedules or a tracking-driven bid collapse.
- Watch: spend is running well above or below expected, but not far enough to be a spike or a drop. If not set, 120-150% or 50-80% of expected. Normal: spend is close to expected. If not set, within ±20%.
- Remember that monthly and daily campaign budgets, shared budgets and the account-level spend limit tied to the payment method.
- Delivery-constrained (budget-limited) means it spent nearly all of its daily budget on most recent days and lost impression share to budget. If not set, 95%+ of the daily budget on 4+ of the last 7 days, and 10%+ impression share lost to budget.
- Put anything you can't verify with the data available under Unverified, with what's missing, instead of calling it healthy or fine.
- 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:
Microsoft (Bing) spend anomaly report
Summary:
The anomalies found, the likely cause of each, and the action proposed.
Spike:
- [campaign] - [reason]
Drop:
- [campaign] - [reason]
Watch:
- [campaign] - [reason]
Normal:
- [campaign] - [reason]
Unverified:
- [campaign] - [what couldn't be checked and why]
## Run it in Roadway
https://www.roadwayai.com/workflows/detect-spend-anomalies-for-microsoft-bing-ads
Catches Microsoft (Bing) spend spikes and drops against the expected daily pattern before they blow the budget or stall delivery. It keeps an eye on your live account and flags anything unusual early. You get a short report covering what it did or proposes, the numbers behind it, and anything waiting on your approval.
