Taking Action on Suggestions: Applying, Ignoring, and Bulk Actions Explained

Taking Action on Suggestions: Applying, Ignoring, and Bulk Actions Explained

Overview

The Suggestions module allows users to take direct action on system-generated recommendations to optimize Amazon Ads performance. Actions can be applied individually or in bulk, depending on the suggestion type. This article explains the available actions, how they work, and what happens after an action is taken.

Explanation

Suggestions themselves cannot be edited or created manually. Users act on suggestions by applying the recommended action (such as updating bids or budgets) or by ignoring them. Once an action is applied or ignored, the suggestion is considered completed and is removed from the active list.

Actions are executed directly against the connected Amazon Ads account or related KwickMetrics modules, depending on the suggestion type.

Usage

Users should take action on suggestions after reviewing performance metrics and reasons provided by the system. Bulk actions can be used to save time when applying the same action to multiple suggestions.

Types of Actions

  1. Apply actions
    Apply actions make changes to the Amazon Ads account or trigger related workflows. The available apply actions depend on the active Suggestions tab.

    Common apply actions include:

    1. Mark as Negative (Wasted Spend – Search Terms)

    2. Pause or Decrease Bid (Wasted Spend – Keywords or Products)

    3. Add to Campaign (New Targets)

    4. Update Bid (Bid)

    5. Increase or Decrease Budget (Budget)

    6. Increase or Decrease Placement Bid (Placements)

    7. Apply Day Parting (Day Parting)

    Notes
    There is no universal action across all tabs. Only actions relevant to the selected tab are available.

  1. Ignore
    Ignoring a suggestion tells the system that the recommendation should not be acted on.

    Behavior of Ignore:

    1. The suggestion is marked as ignored (snoozed)

    2. It is removed from the active Suggestions list

    3. Tab counts are updated immediately

    Ignored suggestions do not reappear unless regenerated by a future sync based on new data.

Bulk Actions

Bulk actions allow users to apply the same action to multiple suggestions at once.

How bulk actions work:

  1. Select one or more rows in the Suggestions table

  2. Open the Action dropdown

  3. Choose an available action

  4. Complete the required fields in the action modal

  5. Apply the action

The system processes all selected rows together and returns a success and failure summary.

Action Modals and Validation

When an action is selected, a modal opens to collect required inputs.

Common validation rules:

  1. Required fields must be completed (for example, new bid, new budget, match type)

  2. Bid and budget limits are enforced by Amazon Ads

  3. Errors returned by the ad platform are shown per row when applicable

AlertIf some rows fail and others succeed, only the successful rows are removed from the Suggestions list. Failed rows remain visible for correction or retry.

Post-Action Behavior

After an action is completed:

  1. Successfully processed suggestions are removed from the list

  2. Tab counts update automatically

  3. No full page refresh is required

  4. Ignored or executed suggestions no longer appear as active items

NotesSuggestions are not editable after execution. Any further changes must be made directly through campaign or rule adjustments.

Important Rules and Behavior

  1. Action button availability
    The Action button is disabled until at least one row is selected.

  2. Partial success handling
    The system supports partial success during bulk actions and clearly shows which rows failed and why.

  3. No undo action
    Applied actions cannot be undone from the Suggestions module.

Summary

Taking action on Suggestions allows users to directly optimize their Amazon Ads account using system-generated insights. Users can apply actions individually or in bulk, ignore recommendations when needed, and rely on clear validation and feedback to understand execution results. Proper use of these actions helps maintain control and consistency in ad optimization workflows.

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