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Keyword Cannibalization Checker

Find the keywords bidding against themselves across your campaigns, see which copy is actually worth keeping, and export a pause file that fixes it — without guessing which instance to cut.

Cross-campaign & cross-ad-groupBest performer identified Confidence-checked before pausingUpload-ready pause fileRuns in your browser

What This Tool Does

Groups every keyword by its text and match type, then shows you each place it runs, what each one costs, and which one to keep.

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Finds every overlapAcross campaigns and across ad groups inside one campaign
Picks the keeperRanks instances on ACOS, with volume weighted in so one lucky order cannot win
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Shows what it costsWasted spend calculated and explained, not asserted
Checks confidence firstFlags instances with too little data to judge instead of telling you to pause them
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Exports the fixTick the losers and download a bulk file that pauses them, IDs intact

📋 How To Use

One export from Amazon, then about a minute.

Download your bulk fileCampaign Manager → Bulk Operations → Download
Drop it in belowParsed locally — nothing is uploaded
Open a conflict groupSee every campaign running that keyword, side by side
Keep the starred oneTick the instances you want paused
Export and uploadBack into Bulk Operations, and negate the paused ones so they do not return
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Drop Your Bulk File Here

Sponsored Products bulk file — .xlsx, .xlsm or .csv

🔒 Never leaves your browser✅ No row limit📝 No signup

Reading your bulk file

Parsing sheets…

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What Is Actually Happening

You are outbidding yourself, and paying Amazon for the privilege.

When the same keyword sits in two campaigns, both are eligible for the same auction. Amazon picks one of your ads — but your own competing bid still helped set the price you pay.

1

Your CPC goes up

The second bid contributes to the price of the auction you were going to win anyway. You pay more for traffic you already had.

2

Data gets split

Clicks and orders divide between two copies, so neither accumulates enough history for Amazon or for you to judge it properly.

3

Budgets compete

Two campaigns spend on the same search. One of them is spending budget it could have used on keywords you do not already cover.

4

It hides from reports

Each campaign looks reasonable in isolation. The problem only appears when you line the copies up side by side, which no Amazon report does for you.

Where We Differ

Four decisions most cannibalization tools get wrong

Exact and broad are not fighting each other

The same term as exact in one campaign and broad in another is standard funnel structure, not a conflict. Grouping them together produces a long list of false alarms. We group by keyword and match type, so only genuine duplicates are flagged.

A duplicate with no data is not a loser

A copy with six clicks and no orders looks like the obvious one to cut. It is not — at a typical conversion rate that outcome is more likely than not on a perfectly good keyword. Those get flagged too early to judge rather than recommended for pausing.

Overlap inside one campaign still counts

Duplicates do not only span campaigns. The same keyword in two ad groups of one campaign competes just as directly. Tools that only compare campaign names miss these entirely.

The numbers say what they measure

Wasted spend here means one specific thing: money spent by duplicate copies that returned nothing. Duplicates that converted are excluded, because that spend was not wasted. And if your cannibalizing keywords happen to run better than the rest of your account, the tool says so rather than asserting harm that is not there.

Practical Use

When To Run This

1

CPC rose without explanation

Costs climbing while competitors and volume look unchanged is a classic self-competition signature.

2

After promoting search terms

Harvesting a converting term into exact without negating it in the source campaign leaves both running.

3

Inheriting an account

Duplicates accumulate quietly through months of launches. This is the fastest way to map them.

4

Before restructuring

Know which keywords live in several places before you start moving campaigns around.

Questions

Frequently Asked Questions

What counts as cannibalization here?
The same keyword text, with the same match type, running in more than one campaign — or in more than one ad group inside a single campaign. Both cases put two of your own targets into the same auction.
Why are exact and broad versions treated separately?
Because running a term as broad for discovery and exact for control is deliberate structure, not a mistake. Flagging it would bury the real conflicts under noise. If you want the broad copy gone after promoting the term, that is a harvesting decision rather than a cannibalization one.
How is the keeper chosen?
Only instances that actually converted are eligible. Among those, the lowest ACOS wins, with order count breaking ties. If no copy in a group has converted at all, the tool keeps whichever has the most clicks — the one with the most evidence — rather than crowning a row with no data behind it.
What does "too early to judge" mean?
That instance has no orders, but not enough clicks for that to mean anything. The threshold comes from your own account conversion rate: below it, zero orders is a likely outcome even on a healthy keyword. Pausing on that basis is guessing, so the tool says so instead of recommending it.
How is wasted spend calculated?
Spend on non-keeper copies that produced zero sales, added up. Duplicates that did convert are deliberately excluded — that money bought something, so calling it waste would overstate the problem. The tool also shows total spend sitting on duplicate copies separately, so you can see both figures.
What does the exported file do?
It contains only the instances you ticked, with Operation set to Update and State set to paused. Upload it through Bulk Operations and those copies stop running. Campaign and keyword IDs are written as text so a 15-digit ID never becomes 4.14046E+14, which is the usual reason a bulk upload gets rejected.
Should I also add negatives?
Usually yes. Pausing a keyword stops that exact target, but if the campaign also runs broad or auto targeting, the same search can come back through those. Adding the term as a negative exact in the campaigns you removed it from closes that door.
How is this different from n-gram analysis?
N-gram analysis breaks search terms into words to find patterns worth negating or bidding on. This looks at whole keywords you are already bidding on and finds the ones duplicated across your structure. Different problem, different fix.
Is my data uploaded anywhere?
No. The file is read by JavaScript in your browser and discarded when you close the tab. There is no server. Load the page, disconnect from the internet, and the tool still works.
Go Deeper

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Want this done properly, every month?

Duplicates come back as accounts grow. Keeping structure clean is part of the work I do for Amazon brands.