# Keyword Research Scraper - Google, YouTube, Amazon & More (`scrapesage/keyword-research-scraper`) Actor
Multi-platform keyword research from autocomplete. One seed explodes into hundreds of long-tail keywords across Google, YouTube, Bing, Amazon, eBay, DuckDuckGo & Wikipedia — each scored for search intent, word count and cross-platform demand. Monitor mode returns only new keywords.
- **URL**: https://apify.com/scrapesage/keyword-research-scraper.md
- **Developed by:** [Scrape Sage](https://apify.com/scrapesage) (community)
- **Categories:** SEO tools, E-commerce, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
$1.50 / 1,000 keyword discovereds
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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## Keyword Research Tool — Google, YouTube, Amazon, Bing, App Store & DuckDuckGo Keywords
Turn a single seed into **thousands of real, long-tail keywords** people are actually searching. This actor mines **live autocomplete suggestions** from **Google, YouTube, Amazon, the Apple App Store, Bing, and DuckDuckGo**, expands every seed with **questions, prepositions, comparisons, and alphabet-soup** modifiers, then **merges and scores** the results into one clean dataset.
No login, no cookies, no browser, no API keys — fast direct calls to each engine's public suggest endpoint with 99%+ reliability.
### Why this keyword research tool?
Most "keyword" scrapers hit Google autocomplete only and dump a flat list. This actor pulls from **six search engines at once**, tells you **which engines surfaced each keyword**, and ranks every term by a **cross-engine opportunity score** — so you instantly see the long-tail winners.
| Capability | Typical keyword scrapers | This actor |
|---|---|---|
| Google autocomplete | ✅ | ✅ |
| YouTube, Amazon, App Store, Bing, DuckDuckGo | ❌ | ✅ all six |
| Questions (who/what/why/how…) | partial | ✅ |
| Prepositions & comparisons (for/with/vs/like…) | ❌ | ✅ |
| Alphabet-soup (a–z) & numbers (0–9) | partial | ✅ |
| Recursive deep expansion (depth 2–3) | ❌ | ✅ |
| Cross-engine merge — which engines surfaced each keyword | ❌ | ✅ `sources[]` |
| 0–100 opportunity score (long-tail + coverage + rank) | ❌ | ✅ |
| Localised by country & language | partial | ✅ |
| **Monitor mode** — only NEW keywords since last run | ❌ | ✅ |
### Use cases
- **SEO & content marketing** — find the exact questions and long-tail phrases your audience searches, and build content, FAQs, and topic clusters around them.
- **PPC / Google Ads** — discover high-intent keyword and negative-keyword candidates fast, localised by country and language.
- **Amazon & e-commerce sellers** — mine Amazon's own autocomplete for product titles, bullet points, and backend search terms that convert.
- **App Store Optimization (ASO)** — pull App Store search hints to optimise app titles, subtitles, and keyword fields.
- **YouTube creators** — surface what viewers type into YouTube to title and tag videos for discovery.
- **Market & trend research** — turn on **monitor mode** + a daily [Schedule](https://docs.apify.com/platform/schedules) to catch rising, emerging long-tail terms the moment they appear.
- **Agencies & SaaS** — power keyword tools, content briefs, and dashboards with a clean, LLM-ready keyword feed.
### How to use
1. [Sign up for Apify](https://console.apify.com/sign-up) — the free plan is enough to try this actor.
2. Open the **Keyword Research Tool**, enter one or more **seed keywords**, pick your **search engines** and **expansion modes**, and click **Start**.
3. Watch keywords stream into the dataset table, sorted by opportunity.
4. **Export** as JSON, CSV, Excel, XML, or RSS — or pull results programmatically via the [Apify API](https://docs.apify.com/api/v2).
### Input
```json
{
"keywords": ["running shoes", "crm software"],
"sources": ["google", "youtube", "amazon", "bing"],
"expansionModes": ["suggestions", "questions", "comparisons"],
"country": "US",
"language": "en",
"maxDepth": 1,
"maxKeywords": 1000
}
````
- **keywords** *(required)* — one or more seed keywords/phrases. Each is expanded independently.
- **sources** *(default `["google"]`)* — any of `google`, `youtube`, `amazon`, `appstore`, `bing`, `duckduckgo`. More sources = broader coverage and a higher cross-engine score.
- **expansionModes** *(default `["suggestions", "questions"]`)* — `suggestions` (raw autocomplete), `questions` (who/what/why/how…), `prepositions` (for/with/near…), `comparisons` (vs/or/like…), `alphabet` (seed + a–z), `numbers` (seed + 0–9).
- **country / language** *(default `US` / `en`)* — localises Google, the Amazon marketplace, the App Store storefront, and Bing/DuckDuckGo region.
- **maxDepth** *(default 1)* — recursively re-expand the strongest discovered keywords (2–3) for deep long-tail mining.
- **maxKeywordsPerSeed** *(default 0 = no cap)* — keep only the top N keywords per seed.
- **maxKeywords** *(default 1000)* — hard total cap; your main cost control.
- **includeMetrics** *(default true)* — add word/character counts, `isQuestion`, `containsNumber`, and the `opportunityScore`.
- **dedupe** *(default true)* — merge identical keywords across seeds into one record.
- **monitorMode** *(default false)* — only output keywords that are **new since the last run** with the same seeds/sources/country.
- **proxyConfiguration** — default Apify proxy is plenty; the suggest endpoints are lightweight.
### Output
One record per unique keyword. Keywords surfaced by several engines are merged into a single record with a `sources` array:
```json
{
"keyword": "running shoes for flat feet",
"seedKeyword": "running shoes",
"expansionType": "suggestions",
"modifier": null,
"depth": 1,
"sources": ["amazon", "bing", "duckduckgo", "google", "youtube"],
"sourceCount": 5,
"bestRank": 0,
"country": "US",
"language": "en",
"wordCount": 5,
"characterCount": 27,
"isQuestion": false,
"containsNumber": false,
"opportunityScore": 88,
"scrapedAt": "2026-06-16T22:00:00.000Z"
}
```
- **sources / sourceCount** — which engines surfaced the keyword (more engines = stronger signal).
- **expansionType / modifier** — how it was discovered (`suggestions`, `questions` + `how`, `comparisons` + `vs`, `alphabet` + `a`, …).
- **bestRank** — best (lowest) position the keyword held in any suggest list (0 = top suggestion).
- **opportunityScore** *(0–100)* — rewards long-tail phrasing (3–5 words), cross-engine coverage, prominent rank, and explicit question intent.
#### What to expect
Autocomplete reflects real, recent search behaviour, so results change over time and by country/language. A keyword is included once any selected engine suggests it. Fields like App Store hints populate mainly for app-related seeds; Amazon hints for product seeds. Nothing is dropped — every suggestion the engines return is captured, merged, and scored.
### Automate & schedule
Run this actor on autopilot and pull results into your own stack:
- **[Apify API](https://docs.apify.com/api/v2)** — start runs, fetch datasets, and manage schedules over REST.
- **[apify-client for JavaScript](https://docs.apify.com/api/client/js/)** and **[apify-client for Python](https://docs.apify.com/api/client/python/)** — official SDKs.
- **[Schedules](https://docs.apify.com/platform/schedules)** — run it daily/weekly with **monitor mode** to capture only newly-appearing keywords; perfect for trend tracking and content pipelines.
- **[Webhooks](https://docs.apify.com/platform/integrations/webhooks)** — trigger downstream actions (content brief, Slack alert, Sheets append) the moment a run finishes.
```js
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' });
const run = await client.actor('scrapesage/keyword-research-scraper').call({
keywords: ['email marketing'],
sources: ['google', 'youtube', 'bing'],
expansionModes: ['suggestions', 'questions', 'comparisons'],
maxKeywords: 800,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Got ${items.length} keywords`);
```
### Integrate with any app
Connect the dataset to 5,000+ apps — no code required:
- **[Make](https://docs.apify.com/platform/integrations/make)** — multi-step automation scenarios.
- **[Zapier](https://docs.apify.com/platform/integrations/zapier)** — push new keywords straight into Sheets, Notion, or your content tool.
- **[Slack](https://docs.apify.com/platform/integrations/slack)** — get pinged when monitor mode finds rising keywords.
- **[Google Drive / Sheets](https://docs.apify.com/platform/integrations/drive)** — auto-export every run to a spreadsheet.
- **[Airbyte](https://docs.apify.com/platform/integrations/airbyte)** — pipe results into your data warehouse.
- **[GitHub](https://docs.apify.com/platform/integrations/github)** — trigger runs from commits or releases.
### Use with AI assistants (MCP)
The output is clean, LLM-ready JSON. Call this actor from Claude, ChatGPT, or any agent framework through the **[Apify MCP server](https://docs.apify.com/platform/integrations/mcp)** — ask your assistant to "find long-tail keyword ideas and questions for 'email marketing' on Google and YouTube" and let it run this tool for you.
### More tools from scrapesage
Build a complete **SEO, ASO & content-research stack**:
- **[Apple App Store Scraper](https://apify.com/scrapesage/app-store-scraper)** — app metadata, rankings & reviews for ASO.
- **[Google Play Store Scraper](https://apify.com/scrapesage/google-play-scraper)** — Android app data, keywords & reviews.
- **[YouTube Scraper](https://apify.com/scrapesage/youtube-scraper)** — channels, videos & creator leads for video SEO.
- **[Chrome Web Store Scraper](https://apify.com/scrapesage/chrome-web-store-scraper)** — extension listings, keywords & developer leads.
- **[Shopify Store Scraper](https://apify.com/scrapesage/shopify-store-scraper)** — products, variants & prices for e-commerce keyword research.
- **[Google News Scraper](https://apify.com/scrapesage/google-news-scraper)** — articles & trending topics for content ideas.
- **[Google Ads Transparency Scraper](https://apify.com/scrapesage/google-ads-transparency-scraper)** — who's advertising what, and the copy they use.
- **[Product Hunt Scraper](https://apify.com/scrapesage/product-hunt-scraper)** — trending launches & maker leads.
### Tips
- **Start narrow, then go wide** — begin with `["suggestions", "questions"]` on Google + YouTube, then add `comparisons`, `alphabet`, and more engines once you see the shape of the niche.
- **Mind the volume** — `alphabet` + `numbers` across six engines generates a *lot* of keywords. Use `maxKeywords` and `maxKeywordsPerSeed` to control cost.
- **Localise** — set `country`/`language` to mine a specific market (e.g. `country: "DE", language: "de"`); the Amazon marketplace and App Store storefront switch automatically.
- **Track trends** — turn on `monitorMode` and schedule daily runs to collect only the keywords that newly appeared, surfacing rising long-tail demand early.
### FAQ
**Where do the keywords come from?** From the public autocomplete (search-suggestion) endpoints of Google, YouTube, Amazon, the Apple App Store, Bing, and DuckDuckGo — the same suggestions you see when you type into each search box. No API keys or logins are used.
**Do I get search volume / CPC?** No. Autocomplete does not expose volume or CPC. This tool focuses on **comprehensive keyword discovery** — every real phrase people search, plus a relative opportunity score based on cross-engine coverage and rank. Pair it with your volume tool of choice for the numbers.
**Can I export to Google Sheets, CSV, or Excel?** Yes — one click in the dataset view, or automatically on every run via the [Google Drive integration](https://docs.apify.com/platform/integrations/drive).
**How does monitor mode work, and does it clash with the Apify scheduler?** Monitor mode remembers the keywords it has already returned (in a named key-value store) and only outputs new ones on the next run. It's independent of scheduling — you schedule the actor with [Apify Schedules](https://docs.apify.com/platform/schedules) and enable monitor mode to receive only fresh keywords each time.
**Which engine should I pick?** Google + Bing + DuckDuckGo for web SEO, YouTube for video SEO, Amazon for e-commerce/product keywords, and the App Store for ASO. Selecting several at once gives the richest, best-scored set.
**Is this legal?** This actor collects publicly available search suggestions only. You are responsible for using the data in compliance with applicable laws and each platform's terms.
### Need help?
Open an issue on the actor's **Issues** tab, or visit the [Apify help center](https://help.apify.com/). Feature requests are welcome — this actor is actively maintained.
# Actor input Schema
## `keywords` (type: `array`):
One or more seed keywords or phrases to expand, e.g. running shoes, crm software. Each seed is expanded into hundreds of real, long-tail keyword ideas.
## `sources` (type: `array`):
Which autocomplete sources to mine. google = web SEO, youtube = video SEO, amazon = product / e-commerce keywords, appstore = ASO, bing & duckduckgo = extra web coverage. The more sources you pick, the broader the keyword set (and the higher cross-engine opportunityScore).
## `expansionModes` (type: `array`):
How to expand each seed. suggestions = raw autocomplete; questions = who/what/why/how… prefixes (great for content & FAQs); prepositions = for/with/near/to…; comparisons = vs/versus/or/like…; alphabet = seed + a–z (the classic 'alphabet soup'); numbers = seed + 0–9. More modes = many more keywords.
## `country` (type: `string`):
Two-letter country code for localised results (affects Google gl, the Amazon marketplace, the App Store storefront, and Bing/DuckDuckGo region).
## `language` (type: `string`):
Two-letter language code (e.g. en, es, de, fr).
## `maxDepth` (type: `integer`):
How many times to recursively expand discovered keywords. 1 = expand the seeds only. 2–3 = re-query the strongest discovered keywords for deep long-tail mining (more keywords, more requests).
## `maxKeywordsPerSeed` (type: `integer`):
Cap on keywords kept for each seed (0 = no cap). The strongest keywords (cross-engine coverage + rank) are kept first.
## `maxKeywords` (type: `integer`):
Hard cap on total keywords across all seeds — your main cost control.
## `includeMetrics` (type: `boolean`):
Add derived fields to every keyword: word/character count, isQuestion, containsNumber, and a 0–100 opportunityScore (rewards long-tail phrasing, cross-engine coverage, and suggest rank).
## `dedupe` (type: `boolean`):
Merge identical keywords discovered from different seeds into a single record. Keywords found on multiple engines are always merged into one record with a sources list.
## `monitorMode` (type: `boolean`):
Only output keywords that are NEW since the last run with the same seeds/sources/country. Perfect for tracking rising search interest and emerging long-tail terms over time. Pair it with Apify Schedules to run daily/weekly. (Uses a named key-value store to remember what it has already seen — it does not interfere with the Apify scheduler.)
## `monitorStoreName` (type: `string`):
Named key-value store used to remember previously-seen keywords for monitor mode. Use distinct names to track separate keyword projects independently.
## `maxConcurrency` (type: `integer`):
Parallel suggest requests. Keep at 8 for a good speed/politeness balance; lower it if you see throttling.
## `proxyConfiguration` (type: `object`):
Proxies to use. The default Apify proxy (datacenter) is plenty — the suggest endpoints are lightweight and keyless.
## Actor input object example
```json
{
"keywords": [
"running shoes"
],
"sources": [
"google",
"youtube"
],
"expansionModes": [
"suggestions",
"questions"
],
"country": "US",
"language": "en",
"maxDepth": 1,
"maxKeywordsPerSeed": 0,
"maxKeywords": 1000,
"includeMetrics": true,
"dedupe": true,
"monitorMode": false,
"monitorStoreName": "keyword-research-monitor",
"maxConcurrency": 8,
"proxyConfiguration": {
"useApifyProxy": true
}
}
```
# Actor output Schema
## `results` (type: `string`):
All discovered keyword records as JSON items in the default dataset.
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"keywords": [
"running shoes"
],
"sources": [
"google",
"youtube"
],
"expansionModes": [
"suggestions",
"questions"
],
"country": "US",
"language": "en",
"proxyConfiguration": {
"useApifyProxy": true
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapesage/keyword-research-scraper").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"keywords": ["running shoes"],
"sources": [
"google",
"youtube",
],
"expansionModes": [
"suggestions",
"questions",
],
"country": "US",
"language": "en",
"proxyConfiguration": { "useApifyProxy": True },
}
# Run the Actor and wait for it to finish
run = client.actor("scrapesage/keyword-research-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).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": [
"running shoes"
],
"sources": [
"google",
"youtube"
],
"expansionModes": [
"suggestions",
"questions"
],
"country": "US",
"language": "en",
"proxyConfiguration": {
"useApifyProxy": true
}
}' |
apify call scrapesage/keyword-research-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapesage/keyword-research-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Keyword Research Scraper - Google, YouTube, Amazon & More",
"description": "Multi-platform keyword research from autocomplete. One seed explodes into hundreds of long-tail keywords across Google, YouTube, Bing, Amazon, eBay, DuckDuckGo & Wikipedia — each scored for search intent, word count and cross-platform demand. Monitor mode returns only new keywords.",
"version": "0.1",
"x-build-id": "K5993RDOkh0cLsFtt"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapesage~keyword-research-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapesage-keyword-research-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapesage~keyword-research-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapesage-keyword-research-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapesage~keyword-research-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapesage-keyword-research-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"keywords"
],
"properties": {
"keywords": {
"title": "Seed keywords",
"type": "array",
"description": "One or more seed keywords or phrases to expand, e.g. running shoes, crm software. Each seed is expanded into hundreds of real, long-tail keyword ideas.",
"items": {
"type": "string"
}
},
"sources": {
"title": "Search engines / platforms",
"type": "array",
"description": "Which autocomplete sources to mine. google = web SEO, youtube = video SEO, amazon = product / e-commerce keywords, appstore = ASO, bing & duckduckgo = extra web coverage. The more sources you pick, the broader the keyword set (and the higher cross-engine opportunityScore).",
"items": {
"type": "string",
"enum": [
"google",
"youtube",
"amazon",
"appstore",
"bing",
"duckduckgo"
],
"enumTitles": [
"Google",
"YouTube",
"Amazon",
"Apple App Store",
"Bing",
"DuckDuckGo"
]
},
"default": [
"google"
]
},
"expansionModes": {
"title": "Expansion modes",
"type": "array",
"description": "How to expand each seed. suggestions = raw autocomplete; questions = who/what/why/how… prefixes (great for content & FAQs); prepositions = for/with/near/to…; comparisons = vs/versus/or/like…; alphabet = seed + a–z (the classic 'alphabet soup'); numbers = seed + 0–9. More modes = many more keywords.",
"items": {
"type": "string",
"enum": [
"suggestions",
"questions",
"prepositions",
"comparisons",
"alphabet",
"numbers"
],
"enumTitles": [
"Raw suggestions",
"Questions (who/what/why/how)",
"Prepositions (for/with/near)",
"Comparisons (vs/or/like)",
"Alphabet soup (a–z)",
"Numbers (0–9)"
]
},
"default": [
"suggestions",
"questions"
]
},
"country": {
"title": "Country",
"type": "string",
"description": "Two-letter country code for localised results (affects Google gl, the Amazon marketplace, the App Store storefront, and Bing/DuckDuckGo region).",
"default": "US"
},
"language": {
"title": "Language",
"type": "string",
"description": "Two-letter language code (e.g. en, es, de, fr).",
"default": "en"
},
"maxDepth": {
"title": "Expansion depth",
"minimum": 1,
"maximum": 3,
"type": "integer",
"description": "How many times to recursively expand discovered keywords. 1 = expand the seeds only. 2–3 = re-query the strongest discovered keywords for deep long-tail mining (more keywords, more requests).",
"default": 1
},
"maxKeywordsPerSeed": {
"title": "Max keywords per seed",
"minimum": 0,
"type": "integer",
"description": "Cap on keywords kept for each seed (0 = no cap). The strongest keywords (cross-engine coverage + rank) are kept first.",
"default": 0
},
"maxKeywords": {
"title": "Max keywords (total)",
"minimum": 1,
"type": "integer",
"description": "Hard cap on total keywords across all seeds — your main cost control.",
"default": 1000
},
"includeMetrics": {
"title": "Include metrics & opportunity score",
"type": "boolean",
"description": "Add derived fields to every keyword: word/character count, isQuestion, containsNumber, and a 0–100 opportunityScore (rewards long-tail phrasing, cross-engine coverage, and suggest rank).",
"default": true
},
"dedupe": {
"title": "De-duplicate across seeds",
"type": "boolean",
"description": "Merge identical keywords discovered from different seeds into a single record. Keywords found on multiple engines are always merged into one record with a sources list.",
"default": true
},
"monitorMode": {
"title": "Monitor mode — only NEW keywords",
"type": "boolean",
"description": "Only output keywords that are NEW since the last run with the same seeds/sources/country. Perfect for tracking rising search interest and emerging long-tail terms over time. Pair it with Apify Schedules to run daily/weekly. (Uses a named key-value store to remember what it has already seen — it does not interfere with the Apify scheduler.)",
"default": false
},
"monitorStoreName": {
"title": "Monitor store name",
"type": "string",
"description": "Named key-value store used to remember previously-seen keywords for monitor mode. Use distinct names to track separate keyword projects independently.",
"default": "keyword-research-monitor"
},
"maxConcurrency": {
"title": "Max concurrency",
"minimum": 1,
"maximum": 20,
"type": "integer",
"description": "Parallel suggest requests. Keep at 8 for a good speed/politeness balance; lower it if you see throttling.",
"default": 8
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Proxies to use. The default Apify proxy (datacenter) is plenty — the suggest endpoints are lightweight and keyless.",
"default": {
"useApifyProxy": true
}
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```