Amazon keyword research and market opportunity analysis for sellers. Retrieve autocomplete suggestions (long-tail keywords), analyze competitor landscape, and assess market opportunity for any keyword on 12 Amazon marketplaces (US/UK/DE/FR/IT/ES/JP/CA/AU/IN/MX/BR). No API key required. Make sure to use this skill whenever the user mentions Amazon product research, finding products to sell on Amazon, Amazon keyword ideas, niche analysis, competition analysis for Amazon, market opportunity on Amazon, comparing Amazon keywords, evaluating whether a product is worth selling, Amazon autocomplete data, seasonal demand for Amazon products, or anything related to researching what to sell on Amazon — even if they don't explicitly say 'keyword research'. Also trigger when the user asks vague questions like 'is this a good product to sell?', 'what's the competition like for X on Amazon?', 'should I sell X or Y?', or 'what are people searching for on Amazon?'.
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Amazon keyword research and market opportunity analysis for sellers. Retrieve autocomplete suggestions (long-tail keywords), analyze competitor landscape, and assess market opportunity for any keyword on 12 Amazon marketplaces (US/UK/DE/FR/IT/ES/JP/CA/AU/IN/MX/BR). No API key required. Make sure to use this skill whenever the user mentions Amazon product research, finding products to sell on Amazon, Amazon keyword ideas, niche analysis, competition analysis for Amazon, market opportunity on Amazon, comparing Amazon keywords, evaluating whether a product is worth selling, Amazon autocomplete data, seasonal demand for Amazon products, or anything related to researching what to sell on Amazon — even if they don't explicitly say 'keyword research'. Also trigger when the user asks vague questions like 'is this a good product to sell?', 'what's the competition like for X on Amazon?', 'should I sell X or Y?', or 'what are people searching for on Amazon?'.
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Amazon Keyword Research 🔍
Free keyword research for Amazon sellers. No API key — works out of the box.
Returns deduplicated, sorted list of real search suggestions — one per line
Why this matters: Amazon autocomplete reflects what real shoppers are actually typing. These aren't guesses — they're demand signals directly from Amazon's search engine. The prefix and alphabet expansion catches long-tail terms that basic autocomplete misses, which are often lower competition and higher intent.
Example:
<skill>/scripts/research.sh "portable blender" us
# Returns 100-200 long-tail keywords
For multi-marketplace research, run the script once per marketplace.
Step 2: Analyze Competition
Use web_search to gather competitor intelligence:
Search "<keyword>" site:amazon.com — note approximate result count for competition density
Summarize: total competitors, price range (min/avg/max), average star rating, top 5 brands by visibility
Why this matters: Raw keyword volume means nothing without competition context. A keyword with 10,000 searches but dominated by 3 entrenched brands with 10,000+ reviews each is a very different opportunity than one with the same volume but fragmented sellers. The price range reveals margin potential — if everything is under $10, margins will be razor-thin after FBA fees.
If Google Trends returns a 429 error, fall back to web_search for seasonal data:
"<keyword>" seasonal trends demand peak months
Identify: trend direction (rising/declining/stable), seasonal peaks (which months), year-over-year change.
Why this matters: Seasonality determines cash flow risk. A product that sells 80% of its volume in Q4 means you need capital for inventory months in advance and may sit on dead stock the rest of the year. Rising trends mean growing demand and more room for new entrants; declining trends mean you're fighting over a shrinking pie. This context turns a keyword from a number into a business decision.
Step 4: Synthesize Report
Combine all data into the output format below.
Why structure matters: Grouping keywords by intent (commercial vs informational vs niche) helps the seller understand not just what people search, but why they search it. The opportunity score condenses multiple signals into a single actionable number, but the breakdown behind it is what actually informs the decision — so always show the reasoning.
When the user asks to compare two or more keywords, run the full workflow (Steps 1-4) for each keyword separately, then present results in a side-by-side comparison table.
Example user input:
Compare "laptop stand" vs "monitor stand" vs "tablet stand" on Amazon US — which one should I sell?
How to execute: Run the script 3 times:
<skill>/scripts/research.sh "laptop stand" us
<skill>/scripts/research.sh "monitor stand" us
<skill>/scripts/research.sh "tablet stand" us
Then complete Steps 2-3 for each keyword, and output a comparison table:
Metric
laptop stand
monitor stand
tablet stand
Long-tail count
—
—
—
Avg price
—
—
—
Top brand dominance
—
—
—
Trend direction
—
—
—
Opportunity score
—
—
—
End with a Recommendation stating which keyword has the best opportunity and why.
Limitations
This skill uses publicly available data (Amazon autocomplete + web search). It does not provide exact monthly search volumes or sales estimates. For precise data, stay tuned for Nexscope — coming soon.
Part of the Nexscope suite — AI-powered Amazon seller tools.
