{"id":6552,"date":"2024-11-27T02:08:32","date_gmt":"2024-11-27T02:08:32","guid":{"rendered":"https:\/\/zonhack.com\/?p=6552"},"modified":"2026-08-31T12:15:14","modified_gmt":"2026-08-31T12:15:14","slug":"using-negative-keyword-strategies-to-reduce-high-acos","status":"publish","type":"post","link":"https:\/\/zonhack.com\/zh\/using-negative-keyword-strategies-to-reduce-high-acos\/","title":{"rendered":"Negative Keyword Strategies for High ACoS: Diagnose First"},"content":{"rendered":"

Negative keyword strategies to reduce high ACoS<\/strong> work on exactly one of the three things that cause high
\nACoS. The other two they cannot touch.<\/strong> So before building a negative list, spend ten minutes
\nestablishing which problem you actually have, because negating your way through a conversion problem burns
\na quarter.<\/p>\n

The three causes, and what fixes each:<\/strong><\/p>\n\n\n\n\n\n\n\n
Cause<\/th>\nWhat it looks like<\/th>\nWhat fixes it<\/th>\n<\/tr>\n<\/thead>\n
Irrelevant traffic<\/td>\nClicks from searches your product does not serve<\/td>\nNegative keywords<\/strong><\/td>\n<\/tr>\n
Poor conversion<\/td>\nRelevant clicks that do not buy<\/td>\nThe listing, or the price<\/td>\n<\/tr>\n
Bids above break-even<\/td>\nRelevant clicks that convert, at a cost you cannot afford<\/td>\nBid math from your margin<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

The diagnostic is simple.<\/strong> Open your search term report and read the terms that spent the most. If they
\ndescribe your product, negatives are not your answer. If they describe something else, they are. I’d do that before reading further.<\/p>\n

In our experience roughly half the accounts that arrive convinced they need a negative keyword project
\nactually have a conversion problem, and negating traffic in that situation reduces spend and sales
\ntogether while leaving ACoS unchanged.<\/p>\n

First, set a target ACoS from your margin<\/h2>\n

Not from a benchmark, and this is where most ACoS conversations go wrong immediately.<\/p>\n

Your break-even ACoS is your contribution margin as a percentage of price.<\/strong> If a product carries a 30%
\nmargin after all costs, advertising at 30% ACoS breaks even. Above that you are buying sales at a loss, and in our experience nobody has calculated it before we ask.<\/p>\n

An earlier version of this page said most sellers aim for 15 to 25%.<\/strong> That figure is meaningless without
\na margin attached. A 45% ACoS is profitable on a high-margin product and ruinous on a thin one,<\/strong> and I’d
\nthrow out any benchmark that arrives without your own numbers.<\/p>\n

Decide what you are buying.<\/strong> Break-even ACoS is the ceiling for profit-focused advertising. You may
\ndeliberately exceed it during a launch to buy rank, which I’d call a decision rather than a mistake, provided
\nsomebody made it on purpose and wrote it down.<\/p>\n

Then convert it to a bid.<\/strong> Break-even cost per click is margin per unit multiplied by conversion rate.
\nOur guide to Amazon bid types and strategies<\/a>
\ncovers the arithmetic properly.<\/p>\n

The diagnostic, in ten minutes<\/h2>\n

Four steps. It decides everything that follows.<\/p>\n

1. Pull the search term report<\/strong> for the last 60 days, sorted by spend descending. I’d not use a shorter window.<\/p>\n

2. Read the top 20 terms and mark each one.<\/strong> Does it describe your product, or something adjacent, or
\nsomething unrelated? Nothing more sophisticated than that. This single pass tells you more than any
\nmetric,<\/strong> and I’d do it by hand rather than by rule.<\/p>\n

3. Count the spend in each bucket.<\/strong> If most of your spend sits on terms that genuinely describe your
\nproduct, stop reading about negatives. Your problem is conversion or bids, and in my experience that is where it usually is.<\/p>\n

4. Check conversion on the relevant terms.<\/strong> Clicks with no sales on a term that describes your product
\nexactly is a listing signal, not a targeting signal. Our guide to
\nimproving your product detail page<\/a> covers
\ndiagnosing which element loses the sale.<\/p>\n

When I have run this on accounts with a stated ACoS problem,<\/strong> the split has been genuinely mixed, and
\nthe sellers who assumed irrelevant traffic without checking were wrong about as often as they were right.<\/p>\n

When negatives genuinely are the answer<\/h2>\n

Three patterns. If you see these, negate.<\/p>\n

Wrong product entirely.<\/strong> You sell a dog bed and you are paying for “dog bed stairs”. Different product,
\nsame words. The commonest genuine case,<\/strong> and broad match is usually the source.<\/p>\n

Wrong intent qualifier.<\/strong> “Free”, “cheap”, “used”, “wholesale”, “DIY”, “how to make”. The shopper is not
\nbuying a new one from you at your price, and I’d negate the whole family at once.<\/p>\n

Wrong attribute.<\/strong> You sell the 12-inch and you are paying for “18 inch”. Specific, high-volume, and
\nentirely wasted. I’d hunt these first because they are unambiguous.<\/p>\n

A pattern worth naming beyond individual terms.<\/strong> Look at the words that recur across your worst terms
\nrather than the terms themselves. If “for cats” appears in nine losing search terms, negate the phrase
\nonce rather than the nine terms separately. That is n-gram thinking, and it scales in a way term-by-term
\nnegation does not.<\/p>\n

The thresholds I would actually use<\/h2>\n

Because “negate the losers” is not an instruction.<\/p>\n

Ten clicks minimum before any judgment.<\/strong> Under that, zero sales means nothing. A keyword paused on
\nthree clicks is a keyword you never tested,<\/strong> and in our experience impatient negation quietly shrinks
\naccounts.<\/p>\n

Then compare spend against break-even, not against a fixed dollar figure.<\/strong> An earlier version of this
\npage suggested negating after $20 to $50 with no sale. That number has no relationship to your product. If
\nyour break-even cost per click is $0.40, ten clicks with no sale is already twice your acceptable
\nacquisition cost. If it is $3.00, the same ten clicks are within tolerance.<\/p>\n

Judge relevance separately from performance.<\/strong> An irrelevant term should be negated on the first click,
\nbecause no amount of data will make it relevant. A relevant term needs data before you touch it, and in our experience conflating the two is the root error.<\/p>\n

Review monthly, not weekly.<\/strong> Search term data accumulates slowly, and I’d rather act once on four weeks
\nthan four times on noise.<\/p>\n

Where to add them, and at which level<\/h2>\n

Placement matters more than sellers expect.<\/p>\n

Campaign level for anything universally wrong.<\/strong> “Free”, “used”, a competitor’s product type. It applies
\neverywhere and belongs once. I’d keep a standing list to paste into every new campaign.<\/p>\n

Ad group level for anything specific to that product.<\/strong> The wrong size, the wrong color, the wrong
\nvariation.<\/p>\n

Negative exact for a single term you have judged.<\/strong> Precise and safe.<\/p>\n

Negative phrase for a pattern.<\/strong> This is where the n-gram work pays, and I’d use it more than most
\naccounts do.<\/p>\n

Negate harvested terms in the source campaign.<\/strong> When a term graduates from an auto or broad campaign
\ninto its own exact-match group, add it as a negative in the campaign it came from. Otherwise you bid
\nagainst yourself,<\/strong> and if somebody managing your account does not mention this step, they have not run a
\nclean account. Our guide to
\noptimizing negative keywords<\/a> covers the
\nmechanics in full, and
\nfinding negative keywords<\/a> covers the
\ndiscovery workflow.<\/p>\n

Mistakes that make ACoS worse<\/h2>\n

Five, and the first two are common enough to be worth naming loudly.<\/p>\n

Negating relevant terms because they had a bad month.<\/strong> You remove converting traffic and ACoS stays
\nflat while sales fall. The worst outcome available here<\/strong> and it looks like diligence.<\/p>\n

Negating so broadly that you block variations you want.<\/strong> A negative phrase is a blunt instrument. I’d
\nread it aloud and ask what else it catches, because when I have seen this go wrong it took a month to notice.<\/p>\n

Negating instead of fixing bids.<\/strong> If a term is relevant and converts but costs too much, lower the bid.
\nDo not remove the traffic.<\/p>\n

Negating instead of fixing the listing.<\/strong> Same logic. If relevant traffic does not convert, the listing
\nis the problem and advertising was only exposing it.<\/p>\n

Building the list once and never revisiting.<\/strong> Search behavior shifts, and a list built last year is
\nblocking terms that may now be worth having. I’d re-read the negatives annually.<\/p>\n

What to do if negatives are not your problem<\/h2>\n

Because for half of you they are not.<\/p>\n

If relevant traffic does not convert:<\/strong> fix the listing first. Main image, then the specification
\nshoppers came for. Advertising amplifies whatever conversion rate you have.<\/p>\n

If relevant traffic converts but costs too much:<\/strong> lower bids to break-even and accept less volume. Our
\nguide to
\nAmazon PPC campaign structure<\/a> covers the structure
\nthat makes bids readable per product.<\/p>\n

If the product itself is uncompetitive on price:<\/strong> no advertising decision fixes that, and I’d rather say
\nso plainly than sell you a keyword project. In our experience that conversation saves more money than any optimization.<\/p>\n

If ACoS is high because you are launching:<\/strong> that may be correct. Buying rank costs money on purpose.<\/p>\n

If you would rather have the diagnosis done and the account managed against margin, that sits inside our
\nAmazon PPC service<\/a>. We are an Amazon Ads
\npartner and an Amazon SPN Verified Partner.<\/p>\n

FAQ<\/h2>\n

Will negative keywords reduce my ACoS?<\/h3>\n

Only if irrelevant traffic is causing it. High ACoS has three causes: irrelevant clicks, poor conversion on
\nrelevant clicks, and bids set above break-even. Negative keywords fix the first and cannot touch the other
\ntwo, so diagnose before building a list.<\/p>\n

What is a good ACoS on Amazon?<\/h3>\n

Whatever sits below your break-even, which is your contribution margin as a percentage of price. A 45%
\nACoS is profitable on a high-margin product and ruinous on a thin one, so published benchmarks such as 15
\nto 25% are meaningless without your own margin attached.<\/p>\n

How do I know if a search term should be negated?<\/h3>\n

Judge relevance and performance separately. An irrelevant term should be negated on the first click since
\nno data will make it relevant. A relevant term needs at least ten clicks before you judge it, then compare
\nits cost against your break-even cost per click rather than a fixed dollar threshold.<\/p>\n

How many clicks before pausing a keyword?<\/h3>\n

At least ten. Below that, zero sales is statistically meaningless, and pausing on two or three clicks means
\nyou never tested the keyword. Impatient negation shrinks accounts while looking like careful management.<\/p>\n

Should negative keywords go at campaign or ad group level?<\/h3>\n

Campaign level for anything universally wrong, such as “free”, “used”, or an unrelated product type. Ad
\ngroup level for anything specific to that product, such as the wrong size or color. Also negate harvested
\nterms in the campaign they came from, or you bid against yourself.<\/p>\n

What is n-gram analysis for negative keywords?<\/h3>\n

Looking at the words that recur across your worst-performing search terms rather than at the terms
\nindividually. If “for cats” appears in nine losing terms, one negative phrase handles all nine, which
\nscales far better than negating each term separately.<\/p>\n

\n

Last updated: August 31, 2026. Amazon’s advertising console, match types, and reporting change over time;
\nthe Amazon Ads console carries the current options for your account. An earlier version of this page
\nquoted a 15 to 25% target ACoS and a $20 to $50 spend threshold for negating a keyword. Both are
\nmeaningless without your own margin and conversion rate, and both have been replaced with the arithmetic
\nthat actually applies.<\/em><\/p>\n

<\/p>","protected":false},"excerpt":{"rendered":"

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