amz-keyword-research

name	amz-keyword-research
description	Build a complete Amazon keyword set for a product and sort it into a usable map. generates seed keywords, expands by intent, classifies by funnel stage and relevance, and assigns each keyword a placement (title, bullets, backend, PPC). Use when a user asks for keyword research, keyword ideas, what keywords to target, long-tail keywords, search terms to rank for, or how to map keywords to a listing. Trigger phrases: "keyword research", "keyword ideas", "what keywords", "long tail keywords", "keywords for my listing", "keyword map". Works with zero tools. the user describes the product and audience.
metadata	{"author":"Jay GPT Pro","library":"amazon-pro-skills","version":"1.0"}

Keyword Research

A keyword list is not keyword research. A pile of 300 keywords with no structure is as useless as no keywords at all. Real research ends with a map: which keyword goes where, and which keyword to fight for first. This skill builds that map.

When to use this

• A new product needs its keyword foundation before the listing is written.
• An existing listing was built on guesses and never had real keyword work.
• A seller has a keyword list but no idea which to prioritize.
• Planning a PPC campaign and needing the keyword groups it will run on.

The framework. The Keyword Map

Every keyword has two properties that decide what to do with it: intent stage and relevance. Plot both and the placement becomes obvious.

Intent stage

• Head terms. Broad, high volume, high competition ("water bottle"). Hard to rank, worth pursuing only as the product matures.
• Mid-tail. Two to three words, real intent, winnable ("insulated water bottle"). The core ranking target.
• Long-tail. Specific, lower volume, high conversion ("32 oz insulated water bottle for hiking"). Cheap to win, converts well, the launch focus.

Relevance

• Core. The product is exactly this. must rank.
• Adjacent. Related use case or audience. worth targeting.
• Loose. Tangential. backend or skip. never the title.

AI search keywords

Rufus, Alexa+, and the COSMO layer surface listings on a wider range of queries than literal A9 search. Three keyword types specifically earn AI-surface citations and should be included in the map even when their direct search volume looks low.

• Question-form keywords. "what is the best [X]", "how to choose [X]", "how to use [X] for [Y]". These match the way buyers prompt Rufus and how Alexa+ parses spoken queries. Place answers in bullets and in the Customer Questions tab.
• Comparison keywords. "[brand or product] vs [alternative]", "[X] alternative to [Y]", "difference between [X] and [Y]". COSMO uses these to position the listing against the comparison set. Place in A+ comparison-chart copy and in a bullet that names the comparison without naming a competitor brand.
• Audience-specific keywords. "[product] for [audience]", e.g. "running shoes for runners over 50", "stroller for tall parents", "yoga mat for hot yoga". COSMO reads these as explicit audience intent and re-ranks listings that clearly serve the named audience. Place in the title's qualifier slot, in a bullet, and in backend keywords.

These are not separate from the map below. they slot into Bullet/A+, Backend, and PPC placements as normal, with the launch priority weighted toward the audience- specific ones because they convert best and face the least competition.

The placement rule

Keyword type	Placement
Highest-volume core mid-tail	Title
Core and adjacent mid-tail and long-tail	Bullets and A+
Loose, synonyms, misspellings, not yet placed	Backend search terms
Everything winnable	PPC, grouped by match type

Step by step

1. Collect inputs. The product, what problem it solves, the target audiences, the category, and any keywords or competitor listings the user already has.

2. Generate seeds. From the product itself, its use cases, its audiences, its materials and attributes, the problems it solves, and the occasions it fits.

3. Expand each seed. Synonyms, alternate phrasings, modifiers (size, color, material, audience, use case), question forms, and common misspellings.

4. Classify every keyword by intent stage and relevance, per the framework.

5. Cut the noise. Drop Loose keywords with no real intent. an irrelevant keyword that brings the wrong shopper hurts conversion-based ranking.

6. Build the map. Assign every surviving keyword a placement. Mark the launch priority set: core long-tail and winnable mid-tail.

7. Run the quality check, then deliver.

Output format

## Keyword Map. [product]

### Title keywords (highest-volume core mid-tail)
[keywords]

### Bullet and A+ keywords (core and adjacent)
[keywords grouped by theme]

### Backend keywords (loose, synonyms, misspellings)
[keywords]

### PPC groups
Exact (proven intent): [keywords]
Broad and phrase (discovery): [keywords]

### Launch priority
[the 10 to 15 winnable keywords to rank for first]

Worked example

Product: a 32 oz insulated water bottle for hiking.

• Title: "insulated water bottle", "32 oz water bottle". core mid-tail, real volume, winnable.
• Bullets and A+: "leakproof water bottle", "water bottle for hiking", "wide mouth bottle". core and adjacent.
• Backend: "thermos", "canteen", "hydro flask alternative", "watter bottle" (misspelling). loose and synonyms.
• Launch priority: the long-tail set, "32 oz insulated bottle for hiking", "leakproof hiking water bottle". low competition, high conversion, rankable in weeks.

Quality check

• Every keyword is classified by both intent stage and relevance.
• Loose, low-intent keywords are cut, not stuffed into the title.
• Every surviving keyword has a placement.
• The launch priority set is winnable long-tail and mid-tail, not head terms.
• PPC keywords are split into proven-intent exact and discovery broad.

Common mistakes

• A list with no map. 300 keywords and no decision about any of them.
• Chasing head terms at launch. Spending the launch fighting "water bottle" against entrenched sellers instead of winning long-tail fast.
• Stuffing irrelevant keywords. An off-target keyword that brings non-buyers lowers conversion and hurts rank.
• Translating keywords by logic. Real shoppers use words you would not guess. expand from how people actually search, not from a thesaurus.

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Built by Jay GPT Pro

Part of Amazon Pro Skills. Production-grade skills for serious Amazon sellers. Free and open. Built by Jay Margaliot.

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