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Deep Dive: The Autocomplete Scraping Mechanism

Understanding how Answer the Public works requires looking under the hood of search engines. It relies on a feature called Google Suggest (or Autocomplete), which was originally designed to reduce typing latency for users.

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The Autocomplete API

When you type in Google, your browser sends a request to an endpoint similar to this: 
GET https://suggestqueries.google.com/complete/search?client=chrome&q=marketing%20automation
Google returns a JSON response with predictions based on:
  1. Global Search Volume: What most people search for.
  2. Freshness: Recent trending topics.
  3. Localization: Queries relevant to your IP address.

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The “Wildcard” Technique

The secret sauce of tools like ATP is the systematic use of wildcards and modifiers. Instead of just querying marketing automation, the scraper iterates through:
  • marketing automation a...
  • marketing automation b...
  • marketing automation for...
  • marketing automation vs...

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The Combinatorial Explosion

For a single keyword, the system might generate:
  • 26 Alphabetical variations
  • 10 Question modifiers (who, what, where…)
  • 12 Preposition modifiers (for, with, without…)
Total API calls = ~50 requests per keyword.

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Challenges in Scraping

Building your own scraper for this is difficult due to:
  1. Rate Limiting: Google will block your IP after ~50 rapid requests.
  2. Geo-Targeting: You need residential proxies to see what users in London vs. New York see.
  3. Parsing: The JSON structure changes occasionally.

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The Apify Solution

Our Answer the Public Actor handles this complexity for you.
  • Proxy Rotation: We use a pool of residential proxies to prevent IP bans.
  • Browser Fingerprinting: We emulate real user behavior to avoid detection.
  • Queue Management: We handle the concurrency of thousands of requests.
By abstracting this infrastructure, we allow you to focus on the data, not the scraping.