Talk to usAdd a negative when a shopper query or product is a clear mismatch for the advertised book, or when sufficiently mature performance has exceeded the testing allowance you can afford. Choose the narrowest exclusion that fits the reason, and check its scope before applying it.
This article combines Amazon’s documented targeting behavior with workflow details supplied by Adigy’s founder. The examples illustrate decisions; they are not customer performance claims.
What a negative keyword does
A negative keyword prevents matching shopper queries from triggering your ad within the scope where the exclusion applies. It does not remove the book from organic search. A negative product target excludes a product target rather than a word or phrase.
Keep three things separate: the keyword you bid on, the shopper’s actual search term, and the negative used to exclude unwanted traffic. One broad keyword can generate several different queries. Excluding one poor-fit query may let you keep testing the others.
Amazon’s Sponsored Products targeting guide describes keyword and product exclusions and campaign or ad-group scope. Check the options available for your campaign type before making changes.
Negative exact, negative phrase, and negative products
Scroll horizontally on a small screen to compare the options.
| Type | Scope | Useful when | Watch for |
|---|---|---|---|
| Negative exact | Excludes the specified query and close variations under Amazon’s matching rules. | A particular query is unsuitable or has exhausted its test. | “Exact” does not mean a literal character-only match. |
| Negative phrase | Excludes queries containing the phrase or close variations. | The phrase expresses an intent you want to exclude throughout that scope. | It can also block longer, valuable queries containing those words. |
| Negative product | Excludes the specified product target. | A particular product audience is unsuitable or unaffordable. | Verify the ASIN and campaign scope; a product exclusion is not a keyword exclusion. |
See Amazon’s current negative-targeting documentation for match behavior and limits. Use actual search-term reports to review the effect after a change.
When should you add a negative?
Start with relevance
Consider the book’s subject, level, audience, likely purchaser, and intended reader. A guitar-learning query is a clear mismatch for a rose-growing manual. A broad topic word is more ambiguous: it may bring people who want something much more general than the book offers.
Do not treat every broad term as automatically bad. A general introduction and a specialist reference can deserve different decisions for the same query.
Then examine the economics and reporting
For relevant traffic, review click cost, spend, attributed outcomes, the royalty contribution, and how much testing you are willing to fund. Recent reporting may be incomplete: Amazon says sales data can take up to 48 hours to populate in its metrics documentation. Later purchases can also change attributed results.
A spending limit is a risk-management choice. Zero sales at that limit does not prove a query will never convert. If the query fits but clicks are too expensive, a lower bid may be worth considering. If only some queries are poor fits, exclude those before reducing opportunity across the whole parent target.
Three worked examples
1. An unrelated query
A rose-growing book receives traffic from “beginner karate lessons.” The topics and buyer intent do not align. An exact exclusion is a focused way to stop that query; it need not wait for an arbitrary number of clicks to establish the mismatch.
2. A query that is too general for this book
The same specialist book receives clicks from “gardening.” Adigy’s founder identifies this as a candidate for semantic exclusion when the broad intent does not fit the book. If you make that decision, an exact exclusion is narrower than a phrase exclusion: a negative phrase containing “gardening” could also block useful longer queries about gardening with roses.
A different, general gardening book should be assessed separately. The decision belongs to the book and audience, not to the account as a whole.
3. A term reaches its spending allowance
Suppose a book earns $6.50 royalty per sale before ads, and a term has spent $6.50 with no attributed sales after allowing for reporting maturity. A conservative testing policy might exclude it; a more permissive policy might allow further spend. This is an illustrative checkpoint, not Adigy’s universal formula or a guarantee of future performance.
Use the correct royalty contribution and avoid subtracting printing costs twice. For bid economics and the uncertainty in small samples, read Amazon Ads getting clicks but no book sales. For the distinction between retail sales and royalties, see our ACoS and profit guide.
How Adigy’s Negative Oracle works
According to the product workflow confirmed by Adigy’s founder, the software uses two decision paths:
- Performance evidence: when sufficient data is available, margin and the author’s aggressiveness or target ACoS settings govern how much testing is allowed. Terms or products that cross the applicable threshold can be excluded automatically with negative exact keywords or negative product targets.
- Semantic relevance: when performance data is insufficient, Negative Oracle can assess fit using the book’s title and description, intended audience, likely buyer and reader, market context, and seasonality. Clear mismatches or overly general intent can be excluded without waiting for a full performance sample.
The process runs continuously rather than depending on the author’s working hours. Semantic decisions are still judgments that authors should be able to review; automation does not make every exclusion correct.
What authors control—and where exclusions propagate
- Review and reversal: inspect Negative Oracle’s suggestions and reverse decisions.
- Never Negative list: protect keywords you want to retain.
- Aggressiveness: adjust how readily negatives are added and how much testing is tolerated alongside your target ACoS goals.
- Manual exclusions: add exact or phrase negative keywords and negative products through bulk lists or the software’s toggle interface.
This matters when the same poor-fit term can appear in several campaigns. Removing it from just one route may leave others active. Conversely, sharing an exclusion across unrelated books could remove useful traffic. Review the book and managed scope when making or reversing a decision.
Common mistakes to avoid
- Negating every term with zero sales before checking reporting maturity or relevance.
- Using phrase exclusions when only one specific query is the problem.
- Assuming exact exclusions cannot affect close variations.
- Applying another book’s negative list without checking audience and intent.
- Reducing all bids when a few poor-fit queries account for the waste.
- Keeping a negative forever after the book, presentation, season, or economics have changed.
Explore Adigy’s campaign-management features and the software buying guide. For an individual customer’s perspective on regular account review, see Vincent Chevalier’s case study; it does not establish a guaranteed result or measure Negative Oracle’s effect in isolation.