# Keyword Research — Google Autocomplete, YouTube, Bing, Amazon (`suitable_sunspot/keyword-ideas-autocomplete`) Actor

Turn one seed into hundreds of long-tail keywords and questions from Google, YouTube, Bing and Amazon autocomplete. Each keyword gets a cross-engine demand score, intent and a topic cluster. 7 languages, any country. $1 per 1,000 keywords.

- **URL**: https://apify.com/suitable_sunspot/keyword-ideas-autocomplete.md
- **Developed by:** [Dmitry Melikhov](https://apify.com/suitable_sunspot) (community)
- **Categories:** SEO tools, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 keywords

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Keyword Ideas & Questions — Google, YouTube, Bing, Amazon

Give it a topic, get back hundreds of long-tail keywords and questions that real people type into **Google, YouTube, Bing and Amazon**. Each keyword is ranked by a **cross-engine demand score**, tagged with its **search intent** and grouped into **topic clusters**, so the list arrives sorted and ready for content planning.

**$1 per 1,000 keywords.** No API keys, no subscription, no accounts to connect.

### What you get

One seed such as `yoga mat` with the default settings returns about 1,500 unique suggestions in under 5 seconds. The best 500 come out ranked:

| demandScore | keyword | intent | cluster | engines |
|---|---|---|---|---|
| 100 | yoga mat towel | informational | towel | Amazon, Bing, Google, YouTube |
| 99 | yoga mat with strap | informational | strap | all 4 |
| 97 | yoga mat cleaner | informational | cleaner | all 4 |
| 93 | yoga mat for kids | informational | kids | all 4 |
| 87 | yoga mat near me | local | near me | Amazon, Bing, Google |
| 83 | yoga mat price | transactional | price | Bing, Google, YouTube |
| 83 | yoga mat alternative | comparison | alternative | all 4 |

Questions are tagged too: *which yoga mat is best*, *how thick should a yoga mat be*, *are yoga mats waterproof*, *can yoga mats be recycled*. They work well as blog topics, FAQ entries and "People also ask" targets.

#### One dataset row

```json
{
  "keyword": "yoga mat towel",
  "seed": "yoga mat",
  "demandScore": 100,
  "intent": "informational",
  "cluster": "towel",
  "sources": ["amazon", "bing", "google", "youtube"],
  "sourceCount": 4,
  "timesSuggested": 12,
  "bestPosition": 1,
  "googleRelevance": 1251,
  "wordCount": 3,
  "country": "us",
  "language": "en"
}
```

#### Cluster summary

The run's key-value store gets an `OUTPUT` record with every cluster: its size, its top keywords and its intent mix.

```json
{"cluster": "best", "keywords": 31, "avgDemandScore": 54,
 "topKeywords": ["which yoga mat is best", "best yoga mat for hot yoga", "best yoga mat brands"],
 "intents": {"commercial": 22, "question": 7, "local": 1, "transactional": 1}}
```

### How the demand score works (and what it is not)

Autocomplete does not publish search volume, and this actor does not invent one. **`demandScore` is a relative rank inside your run.** It is built only from signals the engines actually return:

- **How many engines suggested the keyword (40%).** Google, YouTube, Bing and Amazon each rank completions by what people type, so a phrase that all four suggest is in demand everywhere.
- **How many different probes surfaced it (30%).** A keyword that comes back for `yoga mat`, `yoga mat t`, `best yoga mat` and `yoga mat for` is popular.
- **Its best position in any suggestion list (20%).**
- **Google's own suggest relevance score, when Google returns one (10%).**

If you need exact monthly volumes and CPC, take the shortlist from this actor to a Keyword Planner–based tool. Checking 200 good keywords costs far less than checking 5,000 raw ones.

### How it finds keywords

For every seed and every engine you pick, the actor sends autocomplete probes:

- the seed itself, then the seed followed by a space;
- **question words** in front: how, what, why, which, can, is… They are built in for English, French, German, Spanish, Italian, Portuguese and Dutch, so a French run asks *comment*, *pourquoi*, *quel*…;
- **modifiers**: best, cheap, vs, for, with, without, near me, price, review, alternative, free… (in French: *pas cher*, *avis*, *comparatif*…);
- **the alphabet**: `seed a` … `seed z`, and in deep mode `seed 0` … `seed 9` plus the question words with a trailing space.

The results are lowercased and de-duplicated across engines, scored, labelled and sorted. Your seed itself is not returned or charged.

#### Intent labels

`question`, `commercial` (best, review, top), `transactional` (price, buy, cheap, coupon), `comparison` (vs, alternative), `local` (near me), `navigational` (login, app, download, official) and `informational` (everything else). The rules cover the same seven languages.

#### Clusters

Each keyword joins the topic word it shares with the most other keywords: *bag*, *kids*, *price*, *near me*… Plurals and accents are folded, so *epais* and *épais* land together, and two-word phrases such as *near me* and *pas cher* stay whole. A keyword whose extra words appear nowhere else goes to `(other)`.

### Input

| Field | Default | Notes |
|---|---|---|
| `keywords` | `["keyword research"]` | Seed topics, up to 50. |
| `sources` | google, youtube, bing | Add `amazon` for product research. Amazon covers US, CA, UK, DE, FR, ES and IT, and falls back to US elsewhere. |
| `country` | `us` | Two-letter code: gb, de, fr, es, it, ca, au, in… |
| `language` | `en` | Two-letter code. |
| `depth` | `standard` | `quick` ≈ 30 probes per seed and engine, `standard` ≈ 55, `deep` ≈ 80. |
| `maxKeywords` | 500 | The best-ranked keywords come first, and you pay per delivered row. |
| `minDemandScore` | 0 | Drops weaker keywords. |
| `intents` | all | For example `["question"]` or `["commercial", "transactional"]`. |
| `questionsOnly` | false | A shortcut for FAQ and blog-topic research. |

Example: French product research on Amazon and Google.

```json
{
  "keywords": ["tapis de yoga"],
  "sources": ["google", "amazon"],
  "country": "fr",
  "language": "fr",
  "maxKeywords": 300
}
```

### Pricing

Pay per event:

- **$0.001 per keyword row delivered**, which is $1 per 1,000 keywords;
- Apify's standard run-start event: $0.00005.

There are no other fees. Set **Max total charge** on the run and the actor stops cleanly at your limit. A run with the defaults (500 keywords) costs about $0.50.

### Use it from an AI agent

The actor works as a tool in Apify's MCP server:
`https://mcp.apify.com?tools=suitable_sunspot/keyword-ideas-autocomplete`.
An agent can ask "find question keywords about home insurance in France" and get back ranked rows with intent and cluster.

### Use cases

- **Content plans:** pick a cluster, write one article per cluster, and answer the questions inside it.
- **Product and marketplace listings:** with Amazon enabled, the keyword list shows what shoppers type: materials, sizes, audiences.
- **YouTube topics:** YouTube suggestions show what people want to *watch*.
- **Local and multilingual SEO:** run the same seed per country and language.
- **PPC seed lists:** filter `intents` to commercial and transactional.

### Limits and notes

- The data is autocomplete suggestions only. There are no search volumes, CPC or difficulty scores.
- The engines change their suggestions over time and by location, so two runs a week apart can differ slightly.
- A probe that fails is retried twice and then skipped. It never fails the run, and the log reports how many failed. If many fail, turn on the proxy setting.
- Unofficial. Not affiliated with Google, YouTube, Microsoft or Amazon; the names only describe where the suggestions come from.

# Actor input Schema

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

One topic per line, up to 50. Each seed is expanded with questions, modifiers and the alphabet, then sent to every engine you pick.

## `sources` (type: `array`):

Which engines to ask. A keyword suggested by several engines gets a higher demand score. Amazon covers US, CA, UK, DE, FR, ES, IT and falls back to US elsewhere.

## `country` (type: `string`):

Two-letter country code: us, gb, de, fr, es, it, ca, au, in ...

## `language` (type: `string`):

Two-letter language code. Question words and modifiers are built in for en, fr, de, es, it, pt, nl; other languages use English probes but the engines still answer in your market.

## `depth` (type: `string`):

How many autocomplete probes per seed and engine. Deeper finds more long-tail keywords.

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

Stop after this many keyword rows. The best-ranked keywords are delivered first. You pay per delivered row.

## `minDemandScore` (type: `integer`):

Drop keywords with a lower demandScore (0-100, relative inside the run).

## `intents` (type: `array`):

Keep only keywords with these intents. Empty = all.

## `questionsOnly` (type: `boolean`):

Shortcut: only question keywords (how / what / why ... and their fr, de, es, it, pt, nl equivalents). Good for FAQ and blog topics.

## `concurrency` (type: `integer`):

Parallel autocomplete requests.

## `proxyConfiguration` (type: `object`):

Autocomplete endpoints normally answer without a proxy. Turn it on only if many queries fail.

## Actor input object example

```json
{
  "keywords": [
    "yoga mat"
  ],
  "sources": [
    "google",
    "youtube",
    "bing"
  ],
  "country": "us",
  "language": "en",
  "depth": "standard",
  "maxKeywords": 200,
  "minDemandScore": 0,
  "questionsOnly": false,
  "concurrency": 8,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

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

No description

## `clusters` (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": [
        "yoga mat"
    ],
    "maxKeywords": 200
};

// Run the Actor and wait for it to finish
const run = await client.actor("suitable_sunspot/keyword-ideas-autocomplete").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": ["yoga mat"],
    "maxKeywords": 200,
}

# Run the Actor and wait for it to finish
run = client.actor("suitable_sunspot/keyword-ideas-autocomplete").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": [
    "yoga mat"
  ],
  "maxKeywords": 200
}' |
apify call suitable_sunspot/keyword-ideas-autocomplete --silent --output-dataset

```

## MCP server setup

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

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/SEGO8HwHs4owj2FyM/builds/GtSlZeJ93eU8e4HaS/openapi.json