What makes a keyword low competition
A low-competition keyword on Amazon is one where the top-ranking listings have relatively few reviews (under 200–500 in most categories), are not dominated by established brands with massive sales velocity, and where the product differentiation of current listings is weak enough that a well-optimized new entry can compete. Low competition is not the same as low volume — some low-competition terms still get several thousand searches per month. The opportunity is that the ranking bar is lower than the volume suggests.
When you search a term on Amazon and the top results all have 500+ reviews and BSR ranks in the top 500 of their main category, that's a signal the keyword is competitive. When the top results are a mix of 15-review listings, generic private label products with weak images, and off-topic items that don't precisely match the query, you're looking at a keyword where a better-executed listing can rank without a massive established advantage.
Modifier mining
Start with your primary keyword and append modifiers to create more specific variations. Modifiers include materials ("wooden," "bamboo," "silicone"), sizes ("mini," "large," "compact"), audiences ("for teens," "for seniors," "for left-handed"), and use-case qualifiers ("for apartment," "for small kitchen," "for beginner"). Take "knife sharpener" and add modifiers: "electric knife sharpener for serrated blades," "manual knife sharpener for hunting knives," "compact knife sharpener for travel." Each of these is likely less competitive than the root term.
Systematic modifier mining can generate 30–50 candidate keywords from a single root term. Most won't have enough search volume to matter, but the 20% that do are often genuinely winnable for a well-optimized listing. The key discipline is actually checking competition for each candidate before targeting it — modifier mining generates candidates, not answers.
Long-tail expansion
Amazon autocomplete is your best free source of long-tail keyword ideas. Type your primary keyword, then add each letter of the alphabet one at a time and record every autocomplete suggestion. "Yoga mat a" → "yoga mat anchor straps," "yoga mat adhesive grip spray." "Yoga mat b" → "yoga mat bag carrier," "yoga mat black thick." Work through the alphabet and you'll surface dozens of specific phrases that real buyers are searching — many of which have minimal competition because most sellers haven't identified them.
After collecting autocomplete suggestions, evaluate each by searching the phrase directly on Amazon and reviewing the top 10 results. Look at review counts, listing quality, and how precisely the top results match the query. A phrase where three of the top five results are loosely related products with thin review counts is a genuine opportunity for a specific, well-optimized listing.
Competitor review mining
Customer reviews contain the exact language buyers use to describe products, and that language often includes keyword variations that sellers haven't thought to target. Read through 30–50 reviews of your top competitors and note any product descriptors, use cases, or problem statements that appear repeatedly. If twelve reviewers mention using a product for something specific ("great for my van kitchen," "perfect for a tiny house"), those use-case phrases are potential long-tail keywords with confirmed buyer interest.
Negative reviews are equally useful — they describe what problems buyers encountered or what they wish the product did differently. If those problems are ones your product doesn't have, the language in negative reviews tells you exactly what search terms will attract buyers who are frustrated with competitors and looking for a better option.
Niche down within category
Amazon's category browse structure is a roadmap to lower-competition niches. Start in your main category and follow the subcategory tree down until you reach the most specific subcategory that still describes your product. The keyword phrases that match the deeper subcategory nodes are typically less competitive because they describe a narrower product, meaning fewer listings are targeting them directly.
A seller in "Kitchen & Dining → Knives → Chef's Knives" is competing at a broader level than a seller targeting "Kitchen & Dining → Knives → Paring Knives → Japanese Paring Knives." The deeper you go in the category tree, the fewer competing listings and the more specific the search intent. Finding the deepest subcategory that accurately describes your product gives you a natural keyword cluster that's both specific and less saturated.
How to evaluate what you find
After generating keyword candidates, evaluate each against three criteria: (1) Is there real search volume? Search the term on Amazon autocomplete — if it doesn't autocomplete or suggest related terms, it may be too obscure to matter. (2) Can you rank for it? Look at the top 10 results and assess review counts and listing quality. Under 300 reviews on most top listings is generally manageable for a new entry with a well-optimized listing. (3) Does it convert? A low-competition term that doesn't match strong purchase intent isn't worth your effort.
If you have access to Brand Analytics or a keyword research tool, add search frequency rank data to your evaluation. Terms in the top 100,000 search frequency rank have meaningful traffic. Terms below 500,000 may not have enough volume to move the needle even if you rank first. Focus your targeting on the terms that pass all three tests — real volume, winnable competition, and clear purchase intent.