Reviewing and accepting suggestions in the Ads Optimiser

The Ads Optimiser suggestion queue is where you review AI-powered recommendations for your Amazon PPC campaigns and decide which ones to apply. Each suggestion tells you what to change, why, and what the estimated impact will be — then lets you accept, reject, or snooze it with a single click.

This guide walks you through reading the suggestion table, using filters and sorting to focus on what matters, and processing suggestions one by one.

Note: You need an active Amazon Ads Optimiser subscription and at least one connected Amazon Advertising account to see suggestions. Suggestions appear after the system has analysed enough campaign data — if your queue is empty, check back after your campaigns have accumulated more performance data.

Open the Ads Optimiser suggestion queue

Log in to your dashboard at www.1smart.link.
Navigate to Dashboard → Ads in the left sidebar.
Click the Ads Optimiser tab.

You will see a table of pending suggestions. Each row is one recommendation the system has generated based on your campaign performance data.

Understand the suggestion types

Every suggestion falls into one of five categories. The type label appears prominently on each row.

Type	What it does	Actionable?
NEGATE	Adds the search term as a negative keyword (exact or phrase match) in the relevant campaign or ad group	Yes
REDUCE	Decreases the bid on a keyword by a calculated percentage, typically to bring spend closer to break-even ACoS	Yes
INCREASE	Increases the bid on a high-converting keyword to capture more impression volume	Yes
PROMOTE	Harvests a search term into a new campaign or ad group (populated from Harvest rules you create in Rules & Automation)	Yes
REVIEW	Informational only — flags a Sponsored Display item for your manual review	No (SD only)

Understanding the type helps you prioritise. For example, a NEGATE suggestion for a search term with high spend and zero orders is usually safe to accept quickly, while an INCREASE suggestion deserves a closer look at your budget headroom.

Read the table columns

Each row in the suggestion table contains several columns that give you the context you need to make a decision.

Search Term

This is the actual query a customer typed on Amazon that triggered your ad. It is the core piece of information — especially for NEGATE suggestions, where you are deciding whether this search term is relevant to your product.

Keyword

The keyword in your campaign that matched the search term. If the keyword is identical to the search term, this column shows a dash (—) to reduce visual clutter.

Campaign

The campaign name, truncated if it is long. Click the campaign name to copy the full name to your clipboard — useful when you need to cross-reference it in Amazon Seller Central or another tool.

Ad Group

The ad group name within the campaign. For Sponsored Display (SD) campaigns, which do not use ad groups, this column shows a dash (—).

Diagnosis

A short, plain-language explanation of why the system generated this suggestion. Examples include "High spend, zero orders" or "Strong CVR, bid too low". This is your quickest way to understand the reasoning without digging into the numbers.

What-if

An estimated impact if you accept the suggestion. This might read something like "Save ₹420/month" for a NEGATE or REDUCE, or "Gain 12 more clicks/week" for an INCREASE. Treat these as directional estimates, not guarantees — they are based on recent performance trends.

Source badge

A small badge indicating which part of the system generated the suggestion:

Badge	Source
ENGINE	The core PPC optimisation engine
BID	A bid rule you configured in Rules & Automation
NEG	A negative keyword rule you configured
KH	A keyword harvest rule

This helps you understand whether a suggestion came from the system's general analysis or from a specific rule you created.

Ad Type badge

A colour-coded badge showing the Amazon ad type:

Badge	Ad type	Colour
SP	Sponsored Products	Green
SB	Sponsored Brands	Blue
SD	Sponsored Display	Purple

Reason

A concise one-line explanation that supplements the Diagnosis column. While Diagnosis tells you the pattern the system detected, Reason gives slightly more context about the recommended action.

Use filters to focus the queue

When you have dozens or hundreds of suggestions, filters help you work through them efficiently.

Search box

The search box at the top of the table filters across four fields simultaneously: Search Term, Keyword, Campaign, and Ad Group. Type any fragment — for instance, a product name or a campaign prefix — and the table narrows to matching rows instantly.

Priority filter

Filter suggestions by priority level to focus on the highest-impact recommendations first.

Diagnosis filter

Narrow the queue to a specific diagnosis type. This is useful when you want to batch-process similar suggestions — for example, reviewing all "High spend, zero orders" items in one pass.

Ad Type filter

A dropdown that lets you choose All, SP, SB, or SD. Use this to focus on one ad type at a time, especially if different team members manage different campaign types.

Source filter

Filter by the source badge (ENGINE, BID, NEG, or KH) to see only suggestions from a particular part of the system.

Sort by performance metrics

Six columns are sortable — click any column header to sort the table:

Spend — total spend attributed to this search term / keyword combination
Sales — total sales attributed
ACoS — advertising cost of sale
CVR — conversion rate
Clicks — total clicks
Orders — total orders

Sorting by Spend (highest first) is a reliable way to surface the suggestions that will have the biggest budget impact. Sorting by ACoS can help you quickly spot runaway keywords.

Accept a suggestion

Accepting a suggestion sends the change directly to Amazon through the Advertising API. This is a real change — it will affect your live campaigns.

Review the suggestion row. Read the Diagnosis, What-if estimate, and performance metrics.
For REDUCE or INCREASE suggestions only: check the editable bid input field. The system pre-fills a suggested bid, but you can type a custom value to override it. For example, if the system suggests reducing a bid from ₹15 to ₹9, but you prefer ₹11, simply clear the field and type 11.
Click the Accept icon (the tick/checkmark) on the suggestion row.
The system sends the change to Amazon: - For NEGATE: the search term is posted as a negative keyword (exact or phrase match) to the appropriate campaign and ad group. - For REDUCE or INCREASE: the keyword bid is updated to the value shown in the bid field. - For PROMOTE: the search term is harvested into the target campaign or ad group as defined by your Harvest rule.
A toast notification confirms the change was applied successfully.
The suggestion status updates to "accepted" and the row moves out of the pending queue.
The change is logged in the change log with before and after values, so you always have an audit trail.

Warning: Accepted changes are applied to your live Amazon campaigns immediately. Double-check the bid value and the campaign name before clicking Accept — especially for NEGATE suggestions, where adding an incorrect negative keyword could block relevant traffic.

Reject a suggestion

If a suggestion does not make sense for your business — for example, the system recommends negating a search term that you know converts seasonally — you can dismiss it permanently.

Click the Reject icon (the cross/X) on the suggestion row.
The suggestion is removed from the queue permanently. No change is sent to Amazon.

Rejected suggestions do not reappear. Use this when you are confident the recommendation is wrong for your situation.

Snooze a suggestion

If you are not ready to decide — perhaps you want to wait for more data, or you need to discuss it with a colleague — snooze the suggestion instead.

Click the Snooze icon on the suggestion row.
The suggestion is hidden from the queue until new performance data comes in.
When the system detects updated data for that search term or keyword, the suggestion may reappear with refreshed metrics and a revised recommendation.

Snoozing is ideal for borderline cases. It keeps your queue clean without forcing a premature decision.

Understand empty states

If your suggestion queue is empty, the system shows a context-aware message:

New Keywords (Harvest) tab empty: "No keyword harvest suggestions yet — Go to Rules & Automation → create a Harvest rule." This means you have not set up any Harvest rules yet, so the system has no basis for generating PROMOTE suggestions.
Other tabs empty: "No pending suggestions. All clear!" This means you have either processed all suggestions or the system has not generated new ones based on recent data.

Recommended workflow

While there is no single correct way to process suggestions, this workflow works well for most sellers:

Start with NEGATE suggestions sorted by Spend (highest first). These are usually the quickest wins — cutting wasted spend on irrelevant search terms.
Move to REDUCE suggestions. Review the suggested bids, adjust if needed, and accept.
Review INCREASE suggestions carefully. These ask you to spend more, so verify the conversion rate and margin justify the higher bid.
Check PROMOTE suggestions last. These harvest search terms into new campaigns, which is a strategic decision that benefits from a calm review.
Snooze anything you are unsure about. Do not reject unless you are confident — snoozed items will come back with fresh data.

Troubleshooting

Suggestion shows an error after accepting

The Amazon Advertising API occasionally rejects a change — for example, if the campaign was paused or archived between the time the suggestion was generated and when you accepted it. Check the campaign status in Amazon Seller Central and retry if the campaign is active again.

Editable bid field is greyed out

The bid field only appears for REDUCE and INCREASE suggestions. NEGATE and PROMOTE suggestions do not involve a bid change, so there is no editable field. REVIEW suggestions are informational only and have no editable fields.

Queue is empty but I expected suggestions

Suggestions are generated based on accumulated campaign data. If your campaigns are new or have very low traffic, the system may not have enough data to produce confident recommendations. Allow more time for data to accumulate, and ensure your campaigns are active and receiving impressions.

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