• Monitor your advertising costs daily by comparing them against a set threshold.
• Detect anomalies in cost by evaluating performance data from the previous day and the last 30 days.
• Receive notifications if costs exceed the predetermined threshold to take timely action.

About this flow:

This flow is designed to help you monitor your advertising costs by analyzing expenses across your campaigns. With a simple setup, you can define a threshold percentage that, when exceeded, triggers a notification. The process incorporates daily cost reports from Google Ads and performs calculations to ensure that you stay on track with your advertising budget. You’ll receive notifications if there are significant variations in costs compared to previous periods, allowing you to react quickly and prevent overspending.

The Issue:

As a marketer, you often face the challenge of staying vigilant about your advertising spend. Cost anomalies can go unnoticed, leading to wasted budgets and poor campaign performance. Without a systematic way to monitor and compare daily costs against historical data, it can be difficult to manage your budget effectively. You need a solution that enables you to detect these anomalies as soon as they arise so you can make informed decisions and adjustments to optimize your campaigns.

The Solution:

This flow helps you effectively manage your advertising costs by pulling in Google Ads campaign reports from both yesterday and the previous 30 days. You specify a threshold for acceptable cost deviations, and the flow checks whether yesterday's costs exceed this benchmark. If they do, a notification is sent, allowing you to investigate or adjust spending as needed. This proactive approach gives you control over your budget and helps ensure that you're not overspending on your campaigns.

The Results:

• Proactive monitoring of costs ensures you're always aware of your spending.
• Immediate alerts allow you to address potential overspend promptly.
• Historical comparison helps inform budget adjustments based on past performance.