Decision Filtering & Search

The AI Decisions page may contain a large number of automated optimization records, especially in accounts where multiple campaigns are running and automation rules are applied frequently.

To make it easier to analyze these decisions, the interface provides filtering and search tools that allow advertisers to narrow the list of displayed records.

These tools help users quickly locate specific optimization events, investigate automation behavior, and analyze how decisions are affecting campaign performance.

Purpose of filtering and search

Filtering and search functions are designed to help advertisers isolate relevant decision records within the AI Decisions table.

Without filtering, the table may include decisions from many campaigns, targets, and optimization rules, making it difficult to identify specific changes.

Using filters and search, advertisers can focus on:

This allows advertisers to analyze automation behavior more efficiently.

Decision filtering

Filtering allows users to limit the decisions displayed in the table based on specific criteria.

Filters can be used to display only certain categories of decisions.

For example, advertisers may choose to view only:

Filtering the table by decision type makes it easier to investigate specific optimization behaviors without being distracted by unrelated actions.

Filters can also help advertisers quickly review recent changes applied by a specific optimization mechanism.

Searching decision records

In addition to filtering, the AI Decisions page includes a search function that allows users to locate specific decision records.

The search field can be used to find decisions related to particular entities within the advertising system.

For example, advertisers may search for:

The search function scans the decision table and returns results that match the entered term.

This feature is particularly useful when investigating optimization behavior related to a specific campaign or advertising element.

Combining filtering and search

Filtering and search can be used together to refine decision analysis.

For example, an advertiser may:

This combination allows the user to quickly identify all bid adjustments applied to that campaign.

Using both tools together enables faster navigation through large decision logs and provides better visibility into how the system is optimizing campaigns.

Benefits of filtering decision logs

Using filtering and search tools improves the usability of the AI Decisions page by making decision analysis more structured and efficient.

These tools help advertisers:

By simplifying access to relevant decision records, filtering and search functions allow advertisers to better understand and monitor EVA’s automated optimization system.