How to: Configure Auto-Pause Settings

The Auto-Pause Setting rules play a crucial role in preventing unnecessary expenditure on underperforming experiments. Metadata offers default values as initial thresholds, allowing users to customize them.

However, users may struggle with value selection and judgment.

Metadata steps in by helping define threshold values based on an account's historical data. Users can choose between default, custom, and historical thresholds for experiments that are not meeting expectations.

Get started on the Campaigns > Auto-Pause Rules page.

Default Settings vs Group Settings

Auto-Pause Settings can be applied globally (across all experiments in Metadata) or at the budget group level.

Changes to the Default Auto-Pausing Settings section will affect all campaigns in Metadata.

However, if you wish to set up auto-pausing settings for specific budget groups, you can do so by scrolling to the bottom of this page and clicking + Add auto-pausing per Group.

Doing so will add a new section of settings for you to configure and save.

When an experiment is paused the optimizations state will be updated as "LOW PERFORMANCE" navigating to Logs will show the exact reason.

The history of the experiment will be based on:

1. Calculate total clicks, leads, spent, mqls, ctr, for experiments for the last 30 active days.

2. Active days = days when spent > 0 for experiments.

3. If number of active days is less than 30, include all the history

Recommendations for your auto-pausing settings

Case 1 - Default for Lead Generation Experiments (Lead-Based Rules):

• Auto-Pause thresholds are calculated based on historical data.
• Dynamic Recommendations are available for accounts with relevant historical performance.
• Each rule, such as maximum allowed clicks to generate a lead or spend without generating a lead, has its own calculation using the latest 40 experiments meeting specific criteria.

Case 2 - Default for Lead Generation Experiments (MQL-Based Rules):

• Similar to Case 1, but focusing on Maximum Quality Leads (MQL).
• Rules include maximum allowed clicks, spend, and cost per MQL for various channels.

Case 3 - Default for Brand Awareness Experiments:

• Rules involve maximum allowed CPC for different channels and minimum allowed click-through rate (CTR).
• Thresholds are calculated based on statistical characteristics of the latest 40 experiments.

Case 4 - Apply Recommendation:

• Users can apply recommendations as the main threshold for better optimization.
• Dynamic recommendations are recalculated weekly.
• Users are warned when there's insufficient experiment history, specifying the number of experiments needed to run statistical analyses.