Youtube Autocomplete Scraper

Youtube Autocomplete Scraper 🔍

Youtube Autocomplete Scraper collects YouTube autocomplete suggestions for a given query, so you can quickly uncover what viewers are searching for. If you’re doing YouTube keyword research autocomplete, building a YouTube autocomplete SEO tool workflow, or exploring YouTube autocomplete data scraper output for content planning, this actor helps you turn public web suggestions into structured results—saving you hours of manual work.

---

Why choose Youtube Autocomplete Scraper?

Feature	Benefit
✅ All-in-one suggestions scraping	Get autocomplete suggestions for the original query and (optionally) prefix/suffix variations in one run
✅ Language + country customization	Tailor results using your selected language and country settings for more relevant suggestion sets
✅ Structured output for easy analysis	Receive consistently labeled fields (suggestion_01, suggestion_02, …) for straightforward spreadsheet/BI import
✅ Scale-friendly batching	Generate multiple records per run by expanding the query with optional prefixes and/or suffixes
✅ Runs fully inside Apify	Automate extraction as a repeatable workflow you can schedule or rerun during keyword research
✅ Reliable dataset export via Apify	Actor saves results to the default dataset so you can export as JSON/CSV after completion

---

Key features

• 🌐 YouTube autocomplete suggestions for a query: Scrapes suggestion strings for your provided query input
• 🗣️ Language-aware results: Uses your selected language to request suggestions with the correct language setting
• 🌍 Country-aware results: Uses your selected country to request suggestions with the correct country setting
• 🔤 Optional prefix support: When enabled, expands your query using alphabetic prefixes to surface additional “YouTube search suggestions scraper” style ideas
• 🔤 Optional suffix support: When enabled, expands your query using alphabetic suffixes for broader keyword coverage
• 📊 Clean, structured fields: Outputs suggestion_01, suggestion_02, etc. in a consistent schema for analysis
• 💾 Dataset-first workflow: Results are pushed to the default dataset at the end of the run for easy downstream export
• 💻 Automation-ready: Designed for repeatable use in pipelines for “extract YouTube autocomplete queries” and related workflows

---

Input

Provide input via an input.json file. Example structure:

{
  "query": "apple watch",
  "language": "English",
  "country": "United States",
  "use_prefix": false,
  "use_suffix": false
}

Input Fields

Field	Required	Description
query	Yes	The search term you want suggestions for (example: apple watch).
language	No	Select the language used for autocomplete suggestions.
country	No	Select the country used to tailor autocomplete suggestions.
use_prefix	No	Whether to add alphabetic prefixes to the query to generate additional suggestion records.
use_suffix	No	Whether to add alphabetic suffixes to the query to generate additional suggestion records.

---

Output

The actor saves each run’s results as JSON records in the default dataset.

[
  {
    "query": "apple watch",
    "suggestion_01": "apple watch series",
    "suggestion_02": "apple watch bands",
    "suggestion_03": "apple watch charger",
    "suggestion_04": "apple watch comparison"
  }
]

Output Fields

Field	Type	Description
query	string	The query string used to fetch autocomplete suggestions (original query or an expanded prefix/suffix query).
suggestion_01	string	The first autocomplete suggestion for that query.
suggestion_02	string	The second autocomplete suggestion for that query.
suggestion_03	string	The third autocomplete suggestion for that query.
suggestion_04	string	The fourth autocomplete suggestion for that query.
suggestion_05	string	The fifth autocomplete suggestion for that query.
suggestion_06	string	The sixth autocomplete suggestion for that query.
suggestion_07	string	The seventh autocomplete suggestion for that query.
suggestion_08	string	The eighth autocomplete suggestion for that query.
suggestion_09	string	The ninth autocomplete suggestion for that query.
suggestion_10	string	The tenth autocomplete suggestion for that query.

Note: The actor currently slices suggestions to max_results when building each record (suggestions[:max_results]). In the provided source code, max_results is read from input but it is not present in the input schema—so only set it if you already know your runtime will accept it.

---

How to use Youtube Autocomplete Scraper (via Apify Console)

1. Open Apify Console
   Log in at https://console.apify.com and go to the Actors section.

2. Find the actor
   Search for Youtube Autocomplete Scraper and open its listing.

3. Go to the INPUT section
   Enter your values using the built-in form (or upload an input.json).

4. Set your core keyword
   Paste your target keyword into the query field (this is what autocomplete suggestions will be generated for).

5. Choose language and country
   Select language and country to better match the audience you care about—useful for workflows like YouTube autocomplete keyword scraper research by region.

6. Optionally expand coverage
   Enable use_prefix and/or use_suffix if you want the actor to create additional query variations (helpful for extract YouTube autocomplete queries at scale).

7. Run the actor
   Click Run. During execution, you’ll see logs about fetched suggestion counts.

8. Open your dataset & export results
   After the run completes, open the default dataset to view and export your JSON results (and convert to CSV in your downstream tool if needed).

No coding required — get structured Youtube Autocomplete Scraper outputs in minutes. ✅

---

Advanced features & SEO optimization

• 🚀 Engineered for YouTube keyword research autocomplete: Built specifically for turning a query into autocomplete strings you can use for planning and optimization.
• 🌍 Location and language targeting: Helpful when your YouTube autocomplete API scraper workflow needs region-relevant suggestion behavior.
• 🔤 Prefix/suffix expansion: Toggle use_prefix and use_suffix to broaden coverage with alphabetic query variations—great for YouTube related searches scraper style ideation.
• 📊 Structured suggestion_XX fields: Consistent labeling makes it easy to map results into spreadsheets, dashboards, or SEO tooling.

---

Best use cases

• 📈 Content creators and SEO strategists: Build topic clusters from what viewers actually search via query-based autocomplete suggestions.
• 🏷️ YouTube keyword research: Use suggestion strings to refine titles, tags, and descriptions with evidence from autocomplete.
• 🎯 Marketing teams: Generate bulk ideation lists by enabling use_prefix / use_suffix for YouTube autosuggest scraper workflows.
• 🔎 Data analysts: Ingest structured suggestion_01… fields into notebooks or BI dashboards to compare suggestion patterns.
• 🧠 Research projects: Track how keyword intent evolves across languages and countries using the language and country inputs.
• 💼 Agencies: Produce repeatable keyword research outputs for multiple clients and regions without manual lookup.
• 🧩 Automation pipelines: Integrate the actor outputs into ETL jobs for “YouTube autocomplete tool” style processes.

---

Technical specifications

• Supported Input Formats

  • ✅ query (string) — required
  • ✅ language (string enum) — optional, defaults to English
  • ✅ country (string enum) — optional, defaults to United States
  • ✅ use_prefix (boolean) — optional, defaults to false
  • ✅ use_suffix (boolean) — optional, defaults to false

• Proxy Support

  • ❌ Not specified in the provided actor inputs (no proxy input fields are defined in the schema)

• Retry Mechanism

  • ✅ Includes error handling and returns an empty list if requests fail or responses can’t be parsed

• Dataset Structure

  • ✅ JSON records pushed to the default dataset
  • ✅ Each record includes query plus suggestion_01 … suggestion_XX

• Rate Limits & Performance

  • ✅ Designed for automated runs; runtime varies depending on how many expanded queries you generate with use_prefix / use_suffix

• Limitations

  • ❌ No email/contact extraction (this actor is for autocomplete suggestions only)
  • ❌ The provided input schema does not include max_results, even though the source code references it—so you should rely on the schema-backed inputs for predictable behavior

---

FAQ

✅ What does the Youtube Autocomplete Scraper return?

It returns JSON records where each record contains the query you used and multiple suggestion fields labeled as suggestion_01, suggestion_02, and so on.

✅ Can I scrape autocomplete suggestions in different languages?

Yes. Use the language input to select the language for the suggestion results. This is useful for workflows like a YouTube autocomplete keyword scraper across regions.

✅ Can I target a specific country?

Yes. Set the country input to tailor suggestions. This helps when you’re building region-aware lists using YouTube search suggestions scraper style research.

✅ How do use_prefix and use_suffix work?

When enabled, the actor generates additional queries by adding alphabetic prefixes and/or suffixes around your original query, then fetches suggestions for each expanded query.

❌ Do I need any special setup or login?

No special setup is required beyond configuring input.json in Apify Console. The actor is designed to run as a self-contained Apify job.

💻 Can I use the output in Python or spreadsheets?

Yes. The actor pushes results to the default dataset in JSON format, which you can export and then load into tools like spreadsheets, notebooks, or any downstream pipeline.

❗ Is this actor extracting private or non-public data?

No. It’s intended for scraping publicly available sources of autocomplete suggestions.

⚠️ Why might some suggestions be missing?

If a request fails or a response can’t be parsed, the actor returns an empty suggestions list for that query variation.

---

Support & feature requests

If you’re using Youtube Autocomplete Scraper for YouTube autocomplete research and want improvements, tell us what would make the output more useful for your workflow.

• 💡 Feature Requests: Ideas like exporting directly to CSV, adding more structured metadata, or expanding control over suggestion counts are all welcome.
• 📧 Contact: Send a message to dataforleads@gmail.com.

Your feedback helps shape the roadmap for this YouTube autocomplete SEO tool experience. 🙌

---

Closing CTA / Final thoughts

Get the most comprehensive, SEO-optimized results with Youtube Autocomplete Scraper—turn autocomplete suggestions into structured keyword research you can scale.