How to Scrape Google Trends Data with Apify
Monitor search trends, compare terms, and ship market intelligence without maintaining your own Google Trends automation stack.
Quick Answer
Apify's Google Trends Scraper extracts trending keywords, interest over time, geographic interest data, and related queries from Google Trends.
Google Trends is a core signal for SEO, content calendars, and competitive research. This guide uses the official Apify Actor so you get structured outputs (not brittle copy-paste from the UI), with a path to scheduling and API access. Pricing and platform behavior were checked against Apify docs and the Store listing in 2026.
Step-by-step: scrape Google Trends (no code)
Step 1: Open the Actor
- Go to Google Trends Scraper on the Apify Store.
- Click Try for free to open the input form in the Console.
You need an Apify account; the free plan includes monthly credits for small tests.
Step 2: Configure keywords, time range, and geography
Typical inputs (exact field names follow the Actor’s INPUT_SCHEMA):
- Queries: One or more keywords or topics you want to compare.
- Time range: e.g. past 7 days, 90 days, or custom (as offered in the form).
- Geo: Country, subregion, or city-level interest where the Actor supports it.
- Category: Optional. Narrows Trends to a vertical (when available).
Start with a small batch (one region, few terms) to validate output shape and cost before scaling concurrency or long date windows.
Step 3: Run the Actor
- Click Start.
- Watch the Log for blocking, captchas, or validation errors.
- Wait until the run finishes with SUCCEEDED.
If results are empty, reduce scope (fewer terms, shorter window), confirm geo spelling, and retry before increasing volume.
Step 4: Download results or call the API
- Open Storage or Output for the run.
- Export JSON, CSV, or Excel for analysis.
- For automation, use the Apify API or a client library to read the default dataset the same way you would for any other Actor.
To run the same configuration repeatedly, save a Task and attach a Schedule (daily/weekly trend snapshots).
Sample output (illustrative)
Actor schemas evolve; treat this as illustrative of the kind of structured rows you get (field names may differ slightly per version):
{
"keyword": "web scraping",
"date": "2026-03-15",
"interestScore": 78,
"geo": "US",
"relatedQueries": [
{ "query": "apify scraper", "score": 100 },
{ "query": "python web scraping", "score": 84 }
]
}
Regional breakdowns often arrive as one row per region or nested objects. Inspect your first successful run’s dataset columns before building dashboards.
Other ways to get “trend-like” data on Apify
Option A: Google Search Results Scraper (SERP monitoring)
Actor: Google Search Results Scraper
Use when you care about rankings, SERP features, and query coverage rather than Trends’ normalized interest index.
- Maintain a keyword list.
- Run on a schedule and append datasets over time.
- Join with Trends output for “interest + visibility” views.
Option B: Website Content Crawler (fallback)
For one-off extraction from public Trends HTML, see Website Content Crawler. Prefer the dedicated Trends Actor for production.
Option C: Custom Actor
Build your own pipeline with Crawlee and Build an Actor when you need proprietary filters or downstream enrichment inside the same run.
Google Trends: official API vs scraping vs managed Actors
| Approach | Pros | Cons |
|---|---|---|
| Official API / exports | Clear contracts where available | Limited public access for many Trends workflows |
| Raw DIY scraping | Full UI coverage possible | High maintenance, blocking, CAPTCHAs |
| Managed Actor (Apify) | Proxies, scaling, scheduling, API access | Ongoing usage cost, vendor dependency |
For recurring production loads, a managed Actor + proxies is usually the lowest operational risk.
Use cases
- SEO & content: Spot rising queries and seasonality before competitors.
- Brand & competitor intel: Compare interest across brands and regions.
- Product discovery: Validate demand spikes for features or categories.
- Campaign planning: Align media spend with geographic interest hotspots.
- News & crisis monitoring: Track breakout topics and related queries quickly.
Combine Trends with other Apify sources
| Data source | Actor / guide | What it adds |
|---|---|---|
| Google Trends | Google Trends Scraper | Normalized interest, geo, related queries |
| Google Search | Google Search Scraper | Rankings, SERP features |
| YouTube | Scrape YouTube | Video demand signals |
| TikTok | Scrape TikTok | Short-form trend velocity |
| Scrape Reddit | Discussion breadth |
Schedule each source, store datasets in Apify, and merge on keyword + date for a simple multi-channel trend stack.
Save a Task + Schedule so every Monday’s dataset lands in the same place, ideal for week-over-week charts in Sheets or BI tools. Open Apify
It is built for Google Trends-style signals: trending keywords, interest over time, geographic interest, and related queries (exact fields depend on the Actor version, so inspect the dataset after your first run).
Yes. Use the official Google Trends Scraper for maintained selectors, cloud runs, and exports.
Create a Task with your input, attach a Schedule, and store each run’s dataset. Compare files by run date or load items into a database / Google Sheets.
Run the Trends Actor and consume results via the Apify REST API or SDKs. It is the same automation model as other Store Actors, without self-hosting browsers.
You pay platform compute (CUs) plus any Actor-specific pay-per-event or pay-per-result fees shown on the Actor’s Pricing tab. Start with a tiny run to read the usage breakdown on the finished run.
Reduce concurrency, narrow geo/time scope, and confirm inputs match Trends UI expectations. If blocks persist, enable Apify Proxy options the Actor recommends and avoid hammering the same query in tight loops.
Yes. Use Crawlee with Playwright or HTTP mode inside an Actor, store output in datasets, and deploy via Git or the CLI. See Build an Actor.
