Updated August 18, 2026: added the late-converter economics and the conversion-drop measurement from the follow-up analysis run, and refreshed all figures from a rerun that excludes our demo tenant at source.
Every Amazon PPC playbook has a version of the same rule: if a search term takes N clicks without an order, negate it. Ten clicks, fifteen, twenty - the number varies, the logic doesn't. The spend is real, the orders aren't there, kill it. We run our own Amazon brands and we have typed that rule into bid tools ourselves. Then we measured what it actually does.
The short answer: across 90 days of Sponsored Products history on our platform - about 257,000 search terms and $1.2M in ad spend across 25 seller ad profiles - 29.7% of search-term spend sat in terms that never produced an order. The dead-spend problem is real. But of the terms that looked dead at the moment a 5-clicks-no-orders rule would have negated them, 33.8% went on to convert inside the same 90-day window. At higher thresholds the miss rate was worse, not better. And because of how Amazon attribution works, every one of those figures is a floor.
What we measured, exactly
We took daily Sponsored Products search-term rows for the trailing 90 days across the ad profiles on our platform (our demo tenant's synthetic data excluded), and accumulated each term's clicks and orders in date order - reconstructing what an automated rule would have seen on each day, not just the end-of-window totals. A "term" here is one search query in one match type in one profile. For each click threshold N, we asked: of the terms that had zero orders at the moment their cumulative clicks crossed N, how many converted later in the window?
Finding one: the dead spend is real
Zero-order terms consumed 29.7% of all search-term spend in the window - about $355,000 of $1.2M. Across individual accounts with meaningful spend the share ranged from 14% to 89%, with the median around a third. Whatever else this article says, that number is why negation exists as a discipline: letting search terms run unexamined is how a fifth to a third of an ad budget quietly evaporates. If you take nothing else away, audit your zero-order spend share this week.
Finding two: the rule you'd use to fix it misfires a third of the time
| Negation rule | Terms it would negate | ...that converted later | Miss rate (floor) |
|---|---|---|---|
| 5 clicks, 0 orders | 8,771 | 2,966 | 33.8% |
| 10 clicks, 0 orders | 2,511 | 1,089 | 43.4% |
| 15 clicks, 0 orders | 1,123 | 500 | 44.5% |
| 20 clicks, 0 orders | 611 | 276 | 45.2% |
Read the first row carefully, because it is the common rule. A 5-clicks-no-orders negation, applied mechanically across these accounts, would have negated 8,771 terms - and been wrong about 2,966 of them, terms that converted afterward inside the same window. One negation in three would have removed a term that was about to produce orders.
One honest caveat belongs right here, not buried at the bottom: converting later does not automatically mean a term deserved to live. A term can convert once at a ruinous cost per order and still be a correct negation. So we measured that too.
What the late converters actually returned
| Cohort (would-be negations that converted) | Window spend | Window sales | Blended ACoS |
|---|---|---|---|
| Dead at 5 clicks | $200,323 | $537,384 | 37.3% |
| Dead at 10 clicks | $88,391 | $211,255 | 41.8% |
| Dead at 15 clicks | $50,050 | $114,734 | 43.6% |
| Dead at 20 clicks | $32,523 | $68,803 | 47.3% |
Two things make this table sharper than it first looks. First, every dollar of those sales landed after the moment the rule would have negated the term - the cohorts had zero orders at their thresholds by definition, so a mechanical rule forfeits all of it. At the 5-click threshold that is $537,384 in sales the rule never sees, against $54,026 of window spend on the terms that truly never converted. Second, the blended ACoS is not free money: 37% blended at 5 clicks, drifting to 47% by 20, spans products where that is comfortably profitable and products where it is not - and a blend hides the spread. The right reading is neither "never negate" nor "the rule was fine": it is that the click counter throws away a large, mostly-recoverable revenue stream along with the genuine waste, and only margin-aware review can tell them apart. Whether 37% ACoS is good news depends entirely on your breakeven, which is a number you should know precisely.
Why the miss rate rises with the threshold
The counterintuitive row is the last one: waiting until 20 clicks made the miss rate worse (45.2%), not better. The explanation is selection. A term does not reach 20 clicks with zero orders by accident - someone, or something, kept it alive that long, and the terms that survive that filter are disproportionately plausible ones: relevant queries, considered purchases, higher price points with naturally longer decision cycles. The obvious junk gets pruned early. What is left at high click counts is exactly the population where patience pays. A click counter cannot tell the difference between an irrelevant term burning money and a relevant term with a slow conversion cycle; that distinction is the whole game, and it lives in the term's relevance and price point, not its click count.
The check almost nobody's rule includes: the term's own history
Everything above treats a term's life as one continuous window, and that is exactly how most negation rules see the world. But the single most informative question about a "dead" term is one no click counter asks: did this term used to convert?
Picture a term that goes 0-for-20 over the last thirty attribution-complete days - a textbook negation candidate. Now add one fact: in the thirty days before that, the same term produced six orders. Negating it would be treating a product problem as a keyword problem. A term that converted reliably and then went cold is not telling you the traffic is wrong; it is telling you something changed at the destination. The usual suspects: your price moved (or a competitor's did), your review score dipped, you lost the Buy Box, the listing changed, stock ran low and suppressed the offer, or a new competitor now owns that query's results page. Kill the term and you silence the messenger - the spend stops, the diagnosis never happens, and whatever broke stays broken on every other term too.
We measured this split on the same accounts, using a lag-adjusted window (the last 30 attribution-complete days against the 30 days before them). Of 508 terms that looked dead in the recent window - ten or more clicks, zero orders - 198 of them, 39.0%, had converted in the prior period, and 64 had three or more prior orders. Two in five of this month's "negation candidates" were converting last month. The dollars in this particular snapshot are modest, but the diagnostic weight is not: those 64 strong flags are 64 product-level alarms that a click-counting rule would have silently converted into negative keywords.
So a negation review needs two lanes, not one. Terms with no conversion history anywhere: candidates for negation on the evidence-budget logic above. Terms whose history splits - orders then, none now: product-review flags, routed to a different checklist entirely.
What we do about it, and what you can do
This does not mean stop negating. It means a click counter alone is the wrong instrument. What the data supports:
- Negate on relevance immediately. A term that does not match what you sell needs zero clicks of evidence. Most of the 29.7% dies here, and no future conversion is being sacrificed.
- For plausible terms, budget in spend, not clicks. Ten clicks means something entirely different at a $0.40 CPC than at $4. Set the evidence budget relative to the product's price and margin, not a universal click count.
- Respect the attribution tail. Sponsored Products orders report on a 7-day attribution window, and the most recent days are always undercounted. A rule that evaluates yesterday's clicks is judging terms on evidence that has not arrived yet.
- Check the term's own history before negating. A formerly-converting term that went cold is a conversion-drop flag, not a negation candidate - review the product (price, reviews, Buy Box, stock, competitors) before touching the keyword.
- Revisit your negatives. If a third or more of threshold-based negations are wrong, your negative lists contain buried winners. An occasional audit of high-spend negated terms is cheap insurance.
In AMZ Vault, negation candidates are surfaced from attribution-complete history rather than same-day counters, every proposed negative is staged for your approval before it touches Amazon, and if you use the AI connection you can run this exact analysis on your own account by asking for it - your zero-order spend share, your would-have-been-wrong rate. We built it that way because the first version of us used the click-counter rule too.
Limitations, stated plainly
These are our platform's accounts, not a random sample of Amazon. Conversion after the threshold does not automatically mean the term was profitable - it means the rule's premise ("this term does not convert") was false. The 7-day attribution window and the end-of-window cutoff both undercount conversions, which is why every miss rate above is a floor: the true rates are higher. And the selection effect that explains the rising curve also means these numbers describe accounts that were already being managed - unmanaged accounts likely have more genuine junk and lower miss rates at low thresholds.
Method: daily SP search-term rows, trailing 90 days to August 18, 2026, cumulative click/order reconstruction per (profile, query, match type); aggregates only, no per-account data published. Related: how we calculate true Amazon profit · every Amazon MCP server compared · try the platform with no signup