Understanding Suggestions Categories and Metrics

Understanding Suggestions Categories and Metrics

Overview

The Suggestions module is organized into multiple tabs, each focused on a specific type of advertising optimization opportunity. Each tab uses historical Amazon Ads performance data and predefined rules to surface actionable insights. This article explains the purpose of each Suggestions tab, the type of data shown, and how metrics are used to support decision-making.

Explanation

Each Suggestions tab represents a different optimization area, such as reducing inefficient spend, expanding profitable targeting, or adjusting bids, budgets, placements, or schedules. Suggestions are generated automatically by the system and are grouped by intent to help users review and act on similar recommendations together.

Metrics shown across tabs are performance indicators derived from Amazon Ads data and campaign settings. These metrics are used to evaluate performance against targets such as ACOS, ROAS, or conversion rate.

Usage

Users should review Suggestions tab-by-tab based on their optimization goals, such as controlling wasted spend, improving efficiency, or scaling profitable campaigns. Understanding the intent of each tab helps prioritize actions and apply the right optimizations.

Suggestions Tabs Overview

  1. Wasted Spend
    Identifies search terms, keywords, or product targets that are spending advertising budget with weak or no sales performance.

    What is shown

    1. Search terms, keywords, or product targets that meet wasted-spend rules

    2. Performance metrics such as ad spend, ad sales, ACOS, ROAS, CVR, clicks, and orders

    3. A system-generated reason explaining why the item is flagged

    How it is used
    Sellers use this tab to reduce inefficiencies by adding negatives, pausing targets, or lowering bids.

  1. New Targets
    Identifies search terms or products that are generating sales and may be suitable to add as new keywords or product targets.

    What is shown

    1. New target opportunities derived from existing traffic

    2. Performance metrics such as ad spend, ad sales, ACOS, ROAS, CVR, and clicks

    3. The existing keyword or product that originally drove the traffic

    How it is used
    Sellers use this tab to expand reach by adding proven-performing targets into campaigns.

  1. Bid
    Highlights keywords or product targets where bid adjustments may improve performance relative to campaign targets.

    What is shown

    1. Keywords or product targets with bid-related recommendations

    2. Current bid, campaign target ACOS or ROAS, and performance metrics

    3. Amazon suggested bid, when available

    How it is used
    Sellers use this tab to fine-tune bids for underperforming or inefficient targets.

  1. Budget
    Identifies campaigns where the daily budget may need to be increased or decreased based on performance and utilization.

    What is shown

    1. Campaign-level performance metrics such as ad spend, ad sales, ACOS, and ROAS

    2. Current campaign budget and budget utilization

    3. A reason indicating why a budget change is suggested

    How it is used
    Sellers use this tab to prevent overspending on inefficient campaigns or unlock scale for well-performing ones.

  1. Placements
    Suggests bid adjustments at the placement level based on how ads perform in different placements.

    What is shown

    1. Placement types such as Top of Search, Product Pages, or Rest of Search

    2. Performance metrics including ad spend, ad sales, ACOS, ROAS, and CVR

    3. Current placement bid modifier and suggested direction of change

    How it is used
    Sellers use this tab to optimize visibility and efficiency by adjusting placement-level bids.

  1. Day Parting
    Identifies campaigns that may benefit from scheduled ad delivery based on time-based performance patterns.

    What is shown

    1. Campaigns with performance indicators suggesting low or high conversion periods

    2. Metrics such as ACOS, ROAS, CVR, CPC, clicks, and budget utilization

    3. A system-generated reason supporting the suggestion

    Notes
    If there is insufficient data to evaluate time-based performance, this tab may show an “Insufficient data” empty state.

    How it is used
    Sellers use this tab to apply day-parting schedules through the Day Parting module.

  1. Low Inventory
    Identifies products that are actively advertised but have no or low available inventory.

    What is shown

    1. Product-level inventory status

    2. Advertising performance metrics such as ad spend, ad sales, ACOS, ROAS, and CVR

    3. A reason explaining why the product is flagged

    How it is used
    Sellers use this tab to avoid wasting ad spend on products that cannot fulfill demand.

Common Metrics Explained

  1. Ad Spend
    Total advertising spend for the item within the configured lookback period.

  2. Ad Sales
    Sales attributed to ads during the lookback period.

  3. ACOS
    Advertising Cost of Sale, calculated as ad spend divided by ad-attributed sales.

  4. ROAS
    Return on Ad Spend, calculated as ad-attributed sales divided by ad spend.

  5. CVR
    Conversion rate, calculated as orders divided by clicks.

  6. Clicks
    Number of ad clicks recorded during the lookback period.

  7. Wasted Spend
    A system-calculated metric representing inefficient ad spend based on performance thresholds.

Important Rules and Behavior

  1. Metrics are historical
    All metrics are calculated using historical data from the configured lookback period. They do not predict future performance.

  2. Lookback periods vary by tab
    Each Suggestions tab may use a different lookback period, configurable in Configuration Center → Ads.

  3. Suggestions are contextual
    Metrics are evaluated in the context of campaign-level targets such as target ACOS or ROAS.

Summary

Each Suggestions tab focuses on a specific optimization objective, supported by performance metrics derived from Amazon Ads data. By understanding the intent of each tab and how metrics are used, sellers can review recommendations more effectively and apply actions that align with their advertising goals and performance targets.