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Extract Records from Google Trends Scraper in 3 Steps

Extract records from Google Trends Scraper — a practical guide with a ready-to-run configuration and structured output.

Sep 16, 2026 · 2 min read · 430 words
See the scraper →

The fastest path from page to dataset is an Actor that already knows the site. Thirdwatch's Google Trends Scraper turns Google Trends Scraper into structured records — the fields you need, ready to export.

Skip the setup: Run this as a ready-to-go task on Apify — pre-loaded with the configuration from this guide.

Why quickstart records

Every data project starts the same way: someone spends a week writing a scraper, then another week un-breaking it. Skipping the build step means the first rows land in minutes.

The Actor takes a short input list and returns structured rows — no selectors, no sessions, no retries to write.

The scraper handles the extraction details so a short input list in means usable records out.

How does this compare to the alternatives?

Approach Cost model Coverage Effort
Manual browsing and copy-paste Free Whatever you can read Doesn't scale
Custom one-off script Your infra and maintenance One brittle path You own the upkeep
Thirdwatch Google Trends Scraper Pay per result row Structured records at scale One run

Why this Actor

  • Purpose-built for this source — keywords in, structured rows out.
  • Pay per result — no subscriptions, free tier to test.
  • Dataset output exports as JSON, CSV, Excel, or via API.
  • Schedulable — save the task and run it daily or weekly.
  • Part of the Thirdwatch portfolio — 140+ public Actors maintained as a fleet.

How to do it in 3 steps

Step 1: Configure the input

Set the inputs as shown below — keywords takes the targets, the optional fields bound run size — start small and scale.

Step 2: Run the Actor

Run it from the console, the API, or the linked saved task. One dataset row is written per record.

Step 3: Use the output

Each row carries the fields this source exposes (title, url, description).

{
  "keywords": [
    "example query"
  ]
}

Each dataset row looks like:

{
  "title": "\u2026",
  "url": "\u2026",
  "description": "\u2026"
}

What to watch for

Results reflect what's publicly visible at run time. Very large pulls take proportionally longer; bound them with the max/limit fields. For data collection, scheduled small runs beat occasional giant ones.

Related use cases

Run the Google Trends Scraper on Apify Store — pay per result, free to try, no credit card to test.

Frequently asked questions

What does Google Trends Scraper return?

One dataset row per record — with the fields shown in the sample output. Export as JSON, CSV, or Excel.

How do I control run size?

`keywords` selects the targets and the max/limit fields bound how many rows come back. Start small, then scale.

Can I run this on a schedule?

Yes — save it as a task and attach a schedule in Apify Console for daily/weekly pulls.

Is this data public?

The Actor collects publicly visible data only — the same information a logged-out visitor sees.

What formats can I export?

JSON, CSV, Excel, XML, or direct API access to the dataset — plus webhooks and integrations.

What if a run returns fewer rows than expected?

The source limits some results; retry once, and widen the query or filters if the target surface is genuinely thin.

Try it yourself

100 free credits, no credit card.

About 30 real searches. Add the MCP to Claude or Cursor in two minutes.