A keyword-selection rule that inverts the instinct to chase high monthly search volume: since Amazon A9 Algorithm ranks listings on sales performance rather than raw search traffic, a keyword that converts well is more valuable than one that merely gets searched a lot, even at lower volume.
Under this strategy, candidate keywords are compared on three axes instead of search volume:
A keyword can look attractive on search volume alone and still be a poor target if the top 3 listings already dominate it or the units-to-rank cost is prohibitive; this strategy filters for keywords that are both winnable and cheap to win. Sellerize Keyword Hunter Pro is the tool built around surfacing exactly this kind of keyword.
A keyword with far lower search volume can still be the better keyword choice if its conversion rate is dramatically higher. The Amazon A9 Algorithm indexes and ranks listings by sales generated through a keyword, not by that keyword's raw search volume — so a low-volume, high-converting term can out-rank a high-volume, low-converting one over time.
The same buyer-intent-over-search-volume logic that drives organic indexing also drives PPC economics: a keyword with lower search volume but high conversion rate can produce a lower effective ACoS than a high-volume, low-conversion keyword, because ad spend on it converts to sales more reliably. This is why the strategy is framed as winning both listing indexing and PPC profitability at once, not just one or the other.
The underlying claim is that Amazon's ranking algorithm rewards sales volume, not search/query volume — so indexing a listing against high-search, low-converting keywords doesn't move rank, while indexing against high-converting keywords does, even at lower search volume. The same logic extends to PPC search-term reports: keywords that generated impressions or clicks but zero sales are excluded from ranking consideration entirely, since 'we don't care about keywords that didn't generate any sales because they're not going to help us rank.'
A screening pass applied to a raw Sellerize Keyword Hunter Pro export: drop any keyword with conversion rate below ~20%, and keep only keywords where sellers outside the top 3 capture at least ~40% of sales (see Market Availability Metric). Applying both filters together shrinks a list of hundreds of keywords down to a workable, higher-quality set before relevance cleanup (Relevance-Sort Keyword Cleanup) and competitor stealing (Keyword List Seed-and-Steal Assembly (Dedupe & Manual Verification)).
Cited example: for the same product, a high-search-volume keyword converted at only ~6%, while a lower-volume "buyer intent" keyword converted at ~52%. Used to argue that chasing search volume is systematically worse than chasing conversion rate — a smaller, more specific audience that's already decided to buy converts far more efficiently than a larger, more generic one.
Autotargeting's search term report is one concrete source for this selection process: mine it for search terms showing high conversion, low ACoS, and profitable sales, then promote those specific terms into an exact-match campaign — often a dedicated Single Keyword Exact Match Campaign if the term is the account's single most important keyword. See Automatic Campaign Four-Way Split (Close Match, Loose Match, Substitutes, Complements) for how Amazon selects autotargeting matches in the first place.