# Amazon Keyword Research

> Investigación de keywords y análisis de oportunidad de mercado en Amazon: sugerencias de autocompletado, competencia y demanda en 12 marketplaces, sin necesidad de API key.

Fuente: https://skillsagentes.com/skills/nexscope-ai/amazon-skills/amazon-keyword-research
Markdown: https://skillsagentes.com/skills/nexscope-ai/amazon-skills/amazon-keyword-research.md

Repositorio: https://github.com/nexscope-ai/Amazon-Skills
Autor: nexscope-ai
Licencia: MIT
Actualizado: hace 5 meses
Coste de contexto: 241 tok instalada, 2k tok al activarse, 2.8k tok con todos los archivos del bundle
Bundle: 3 archivos, 11 KB
Permisos que pide: ninguno declarado

## Instalación

Un skill son archivos markdown: los mismos archivos valen para cualquier agente y lo único que cambia es el directorio de destino, es decir la bandera `--agent`. Añade `-g` para instalarlo en todos los proyectos de la máquina.

```bash
# Claude Code
npx -y skills add nexscope-ai/Amazon-Skills --skill amazon-keyword-research --agent claude-code
# Cursor
npx -y skills add nexscope-ai/Amazon-Skills --skill amazon-keyword-research --agent cursor
# Codex
npx -y skills add nexscope-ai/Amazon-Skills --skill amazon-keyword-research --agent codex
# Gemini CLI
npx -y skills add nexscope-ai/Amazon-Skills --skill amazon-keyword-research --agent gemini
# Windsurf
npx -y skills add nexscope-ai/Amazon-Skills --skill amazon-keyword-research --agent windsurf
# Cline
npx -y skills add nexscope-ai/Amazon-Skills --skill amazon-keyword-research --agent cline
```

## Qué hace

- Extrae 100-200 palabras clave long-tail desde el autocompletado de Amazon
- Analiza el panorama competitivo: número de competidores, rango de precios, rating medio y marcas top
- Detecta tendencias estacionales con 12 meses de datos de Google Trends
- Calcula un score de oportunidad de mercado de 1-10
- Compara varias keywords lado a lado

## Cuándo usarla

- El usuario menciona investigación de producto en Amazon, ideas de keywords o análisis de nicho
- Preguntas vagas como '¿es buen producto para vender?' o '¿qué competencia tiene X en Amazon?'
- Quiere comparar dos o más keywords para decidir qué vender
- Necesita ver demanda estacional para un producto de Amazon

## Cuándo no

- Se necesitan volúmenes de búsqueda mensuales exactos o estimaciones de ventas precisas

## Qué la activa

- "Investiga la keyword "portable blender" en Amazon US"
- "Encuentra keywords long-tail para "yoga mat" en Amazon"
- "Quiero vender bandas de resistencia, ¿cómo está el panorama de keywords en Amazon?"
- "Compara "laptop stand" vs "monitor stand" en Amazon US, ¿cuál tiene más oportunidad?"

## Antes de instalar

- No requiere API key; usa el script scripts/research.sh incluido y las herramientas web_search/web_fetch.
- Necesita en el PATH: curl, npx, python3
- Variables de entorno: DOMAIN, ENCODED, KEYWORD, MARKETPLACE, RESULT, SEARCH_TERM
- makes network requests
- reads environment config

## Archivos

- SKILL.md — 8 KB
- _meta.json — 113 B
- scripts/research.sh — 3 KB

## SKILL.md

Reproducido tal cual desde nexscope-ai/Amazon-Skills bajo MIT. Esta sección es el documento original y está en inglés.

# Amazon Keyword Research 🔍

Free keyword research for Amazon sellers. No API key — works out of the box.

## Installation

```bash
npx skills add nexscope-ai/Amazon-Skills --skill amazon-keyword-research -g
```

## Capabilities

- **Long-tail keyword mining**: Extract 100-200 real search terms from Amazon's autocomplete engine
- **Competitor landscape analysis**: Product count, price range, average rating, review distribution, top brands
- **Seasonal trend detection**: 12-month Google Trends data to identify peak seasons and demand shifts
- **Market opportunity scoring**: 1-10 score combining competition density, price room, and demand signals
- **Multi-marketplace support**: US, UK, DE, FR, IT, ES, JP, CA, AU, IN, MX, BR
- **Keyword comparison**: Side-by-side analysis of multiple keywords

## Usage Examples

Users can ask naturally. Examples:

```
Research the keyword "portable blender" on Amazon US
```

```
Find long-tail keywords for "yoga mat" on Amazon
```

```
I want to sell resistance bands. What does the Amazon keyword landscape look like?
```

```
Compare "laptop stand" vs "monitor stand" on Amazon US — which has more opportunity?
```

```
Analyze "Küchenmesser" on Amazon Germany
```

```
Research "water bottle" across Amazon US, UK, and DE
```

## Workflow

### Step 1: Gather Autocomplete Data

Run the bundled script to collect Amazon autocomplete suggestions:

```bash
<skill>/scripts/research.sh "<keyword>" [marketplace]
```

**Parameters:**
- `keyword` (required): The seed keyword to research
- `marketplace` (optional): `us` (default), `uk`, `de`, `fr`, `it`, `es`, `jp`, `ca`, `au`, `in`, `mx`, `br`

**What the script does:**
- Queries Amazon's autocomplete API with the seed keyword
- Expands with prefixes: "best [keyword]", "cheap [keyword]", "top [keyword]"
- Expands with a-z suffixes: "[keyword] a", "[keyword] b", ... "[keyword] z"
- 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:
```bash
<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:

1. Search `"<keyword>" site:amazon.com` — note approximate result count for competition density
2. Search `"<keyword>" amazon best sellers price review` — extract price patterns, rating averages, dominant brands
3. 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.

### Step 3: Check Seasonality

Use `web_fetch` on Google Trends:

```
https://trends.google.com/trends/explore?q=<keyword>&geo=US
```

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.

## Output Format

Present the final report in this structure:

```
## Keyword Research Report: [keyword]
**Marketplace:** Amazon [US/UK/DE/...]
**Date:** [current date]

### 1. Long-tail Keywords ([count] found)

**High Commercial Intent:**
- [keyword with "buy", "best", "vs", "for" etc.]
- ...

**Informational / Research:**
- [keyword with "how to", "what is", "review" etc.]
- ...

**Niche / Specific:**
- [long, specific keywords indicating clear purchase intent]
- ...

### 2. Competition Landscape

| Metric | Value |
|--------|-------|
| Estimated competitors | [number] |
| Price range | $[min] - $[max] |
| Average price | $[avg] |
| Average rating | [stars] |
| Top brands | [brand1, brand2, brand3...] |

### 3. Seasonal Trends

[Describe 12-month trend: peaks, valleys, stable periods]
[Note any upcoming peak seasons relevant to the keyword]

### 4. Market Opportunity Score: [X/10]

**Score breakdown:**
- Competition density: [low/medium/high] — [why]
- Price room: [low/medium/high] — [why]
- Demand trend: [growing/stable/declining] — [why]
- Niche potential: [low/medium/high] — [why]

**Recommendation:** [1-2 sentence actionable recommendation]
```

## Multi-Keyword Comparison

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:
```bash
<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, check out **[Nexscope](https://www.nexscope.ai/?co-from=skill)** — Your AI Assistant for smarter E-commerce decisions.

---

**Built by [Nexscope](https://www.nexscope.ai/?co-from=skill)** — research, validate, and act on e-commerce opportunities with AI.

## Dónde encaja

- Categoría: [Datos y analítica](https://skillsagentes.com/categorias/datos-analitica.md) — Consulta, limpia y visualiza datos sin salir del agente.
- Creador: [nexscope-ai](https://skillsagentes.com/creators/nexscope-ai.md) — 52 skills en el directorio
- [Todas las skills](https://skillsagentes.com/skills.md)
- [Ranking de instalaciones](https://skillsagentes.com/ranking.md)

## Otras skills del mismo repositorio

- [Amazon Product Photography](https://skillsagentes.com/skills/nexscope-ai/amazon-skills/amazon-product-photography.md): Planifica fotografía de producto para Amazon lista para rodaje: sets de imágenes de listing, infografías, escenas de estilo de vida y briefs de producción.
- [Amazon Global Selling](https://skillsagentes.com/skills/nexscope-ai/amazon-skills/amazon-global-selling.md): Evalúa y planifica la expansión a marketplaces de Amazon entre países, cubriendo demanda, economía, impuestos, cumplimiento, logística y localización; no sustituye asesoría legal, fiscal, aduanera o de certificación.
- [Amazon Fba Prep](https://skillsagentes.com/skills/nexscope-ai/amazon-skills/amazon-fba-prep.md): Construye un plan específico por producto para preparación FBA, etiquetado, empaque y disponibilidad de envío en Amazon; no sustituye los requisitos vigentes de Seller Central.
- [Amazon Deal Finder](https://skillsagentes.com/skills/nexscope-ai/amazon-skills/amazon-deal-finder.md): Planificación de deals y optimización de estrategia promocional en Amazon: Lightning Deals, Best Deals, Coupons, Prime Exclusive Discounts, elegibilidad, timing y cálculo de ROI.
- [Amazon Listing Images](https://skillsagentes.com/skills/nexscope-ai/amazon-skills/amazon-listing-images.md): Estrategia y optimización de imágenes para listings de Amazon: shot list, infografías, fotografía de estilo de vida, optimización móvil y contenido visual enfocado en conversión.

---

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