Amazon Keyword Research — Related, Result Count & Reverse ASIN

# Amazon Keyword Research — Related, Result Count & Reverse ASIN (`memo23/amazon-keyword-research`) Actor

Amazon keyword research without a Helium 10 seat. Related autocomplete keywords with a volume-proxy rank, Amazon search-result counts per term, and reverse-ASIN: which of those phrases the product actually ranks for on page one of the SERP. 16 marketplaces. JSON or CSV.

- **URL**: https://apify.com/memo23/amazon-keyword-research.md
- **Developed by:** [Muhamed Didovic](https://apify.com/memo23) (community)
- **Categories:** E-commerce, SEO tools, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

<h1 align="center">Amazon Keyword Research — Related, Result Count & Reverse ASIN</h1>

Amazon keyword research without a Helium 10 or Jungle Scout seat. Three modes, one actor.

| Mode | You give | You get |
|---|---|---|
| `related_keywords` | Seed terms | Autocomplete long-tails + volume-proxy rank |
| `search_volume` | Keywords | Amazon's own “N results” count (competition / demand proxy, **not** a monthly volume estimate) |
| `reverse_asin` | An ASIN | Phrases from the product title's autocomplete where that ASIN actually appears on the SERP, with position |

> `search_volume` is labeled honestly. Amazon does not publish official monthly volumes. This mode records the result-count string Amazon shows on the search page. Feed those keywords into `related_keywords` or a paid volume API if you need a monthly estimate.

### Example inputs

```json
{ "mode": "related_keywords", "keywords": ["coffee grinder"], "marketplaces": ["US"] }
```

```json
{ "mode": "search_volume", "keywords": ["coffee grinder", "burr grinder"], "marketplaces": ["US"] }
```

```json
{ "mode": "reverse_asin", "asin": "B0BDHWDR12", "marketplaces": ["US"], "maxKeywords": 30 }
```

### Output

**related\_keywords** — `keyword`, `seedKeyword`, `volumeProxy`, `amazonRank`, `searchUrl`

**search\_volume** — `keyword`, `resultCount`, `searchUrl`, `source: search_result_count`

**reverse\_asin** — `asin`, `productTitle`, `keyword`, `rank` (SERP position), `resultCount`, `searchUrl`, `source: serp`

Rows where the ASIN was not on the first search page are dropped.

### ⚠️ Disclaimer

Collects publicly available Amazon search and product-page data. No login, no Brand Analytics, no Helium 10. Comply with Amazon's Terms and applicable law. Not affiliated with Amazon.com, Inc.

### SEO Keywords

amazon keyword research, reverse asin, amazon search volume, amazon autocomplete keywords, helium 10 alternative, cerebro alternative, amazon serp rank, amazon ppc keywords

# Actor input Schema

## `mode` (type: `string`):

related\_keywords = autocomplete long-tails + volume proxy. search\_volume = Amazon 'N results' count per keyword (a competition/demand proxy, not a monthly search-volume estimate). reverse\_asin = expand the product title, then record the SERP position of that ASIN for each phrase.

## `keywords` (type: `array`):

Used by related\_keywords and search\_volume.

## `asin` (type: `string`):

Used by reverse\_asin. 10-character Amazon ASIN.

## `asins` (type: `array`):

Optional extra ASINs for reverse\_asin.

## `marketplaces` (type: `array`):

US, UK, DE, FR, IT, ES, CA, MX, AU, JP, IN, BR, NL, AE, SA, IE.

## `maxKeywords` (type: `integer`):

Cap on related phrases or SERP checks.

## `maxItems` (type: `integer`):

Hard cap on rows written to the dataset.

## `expandAlphabet` (type: `boolean`):

Append a–z to each seed to pull more long-tail autocomplete phrases.

## `expandBuyerModifiers` (type: `boolean`):

Append locale-aware buyer-intent suffixes (cheap, best, for home, günstig, …).

## `maxConcurrency` (type: `integer`):

Max simultaneous Amazon requests.

## `requestDelayMs` (type: `integer`):

Optional pause after each Amazon request, in milliseconds.

## `proxy` (type: `object`):

Paying users are routed through built-in residential proxies. Search pages need that more than the completion API.

## Actor input object example

```json
{
  "mode": "related_keywords",
  "keywords": [
    "coffee grinder",
    "laptop stand"
  ],
  "marketplaces": [
    "US"
  ],
  "maxKeywords": 50,
  "maxItems": 200,
  "expandAlphabet": false,
  "expandBuyerModifiers": true,
  "maxConcurrency": 6,
  "requestDelayMs": 0
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `csv` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keywords": [
        "coffee grinder",
        "laptop stand"
    ],
    "marketplaces": [
        "US"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("memo23/amazon-keyword-research").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "keywords": [
        "coffee grinder",
        "laptop stand",
    ],
    "marketplaces": ["US"],
}

# Run the Actor and wait for it to finish
run = client.actor("memo23/amazon-keyword-research").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "keywords": [
    "coffee grinder",
    "laptop stand"
  ],
  "marketplaces": [
    "US"
  ]
}' |
apify call memo23/amazon-keyword-research --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,memo23/amazon-keyword-research"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/jJoAIx06Eyx7HQdI6/builds/tYqBS8SVa5YAe9OF7/openapi.json