Google Trends Scraper — Google Trends API Alternative

Google Trends Scraper is a NexGenData tool on Apify that returns interest scores by date plus top and rising related queries from Google Trends.

Google Trends data and keyword trends over time, one row per date per keyword.

Get Google Trends data as clean rows: one row per date per keyword with the interest score, plus rows for top and rising related queries and for interest by region. Compare up to five keywords, pick a country and a time range, and export to JSON, CSV or Excel. No API key.

Proxy: this actor uses Apify residential proxy because on Apify's datacenter proxy Google Trends returns interest-over-time and regional rows but no related queries (tested Nov 3, 2026: 203 rows vs 278 on residential). Residential proxy costs more: Apify bills residential traffic to you per GB.

What you get

Every row has a type field. A run returns four kinds of rows:

type	One row per	Fields
interest_over_time	date × keyword	keyword, date, interest (0–100), geo, timeframe
related_query_top	top related search × keyword	keyword, relatedQuery, value, geo
related_query_rising	rising related search × keyword	keyword, relatedQuery, value (growth, e.g. "+250%" or "Breakout"), geo
interest_by_region	region × keyword (interest above 0)	keyword, region, interest, geo

How many dates you get depends on the time range Google returns for it: a 12-month range gives about 52 weekly dates per keyword, 90 days gives daily dates, 5 years gives weekly dates. Related queries and regions appear only when Google publishes them for the keyword (low-volume keywords may have none).

About the interest score: it is Google's relative search interest, scaled 0–100, where 100 is the peak of the most-searched keyword in your set. It is not absolute search volume. Keywords in the same run are scaled together, so they compare directly.

Example output

[
  {"type": "interest_over_time", "keyword": "apify", "date": "2025-10-19", "interest": 24, "geo": "US", "timeframe": "today 12-m"},
  {"type": "interest_over_time", "keyword": "web scraping", "date": "2025-10-19", "interest": 61, "geo": "US", "timeframe": "today 12-m"},
  {"type": "related_query_top", "keyword": "web scraping", "relatedQuery": "python web scraping", "value": 100, "geo": "US"},
  {"type": "related_query_rising", "keyword": "web scraping", "relatedQuery": "ai web scraping", "value": "+180%", "geo": "US"},
  {"type": "interest_by_region", "keyword": "apify", "region": "California", "interest": 100, "geo": "US"}
]

To chart a keyword, filter rows to type = interest_over_time and plot date against interest.

Input

{
  "keywords": ["apify", "web scraping"],
  "geo": "US",
  "timeframe": "today 12-m"
}

• keywords — up to 5; extra keywords are ignored.
• geo — a country code such as US, GB or IN.
• timeframe — Google Trends ranges such as now 7-d, today 1-m, today 3-m, today 12-m, today 5-y.

Pricing

Pay per row: $0.03 per row of any type, plus $0.00005 per run start. Nothing is charged for retries or for runs that fail.

Because every date is a row, the cost follows the date count. Typical runs:

• Store example (2 keywords, US, 12 months): about 106 interest rows plus related-query and regional rows — on Oct 23 that was 277 rows, about $8.31.
• 1 keyword, 12 months, with few related queries: roughly 60–100 rows, about $1.80–$3.00.

Use fewer keywords or a shorter range to keep runs small. Live prices are always in the Pricing tab.

Who uses it

• SEO and content teams — pick topics with rising search interest and time articles to seasonal peaks.
• Market researchers — compare brands or products by relative search interest and see where demand is strongest by region.
• Ad buyers — line campaign timing up with the weeks search interest climbs.

Reliability

Google Trends rate-limits shared IP addresses. The actor routes requests through Apify residential proxies, rotates the IP on each try and backs off between up to 8 attempts. If every attempt is blocked, the run fails with the reason and nothing is charged. If Google answers but has no data for your keywords, the run succeeds with 0 rows and says so.

Code example — Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nexgendata/google-trends-scraper").call(run_input={
    "keywords": ["apify", "web scraping"], "geo": "US", "timeframe": "today 12-m",
})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    if row["type"] == "interest_over_time":
        print(row["keyword"], row["date"], row["interest"])

Run it on a schedule

Search interest moves weekly, so a weekly run over the same keywords suits most tracking; daily runs with now 7-d suit fast-moving topics. Each run returns the full range again with Google's latest values, so de-duplicate on keyword + date downstream if you keep history. Send each run's results onward with a webhook, Google Sheets, Zapier, Make or the Apify API.

Video guides from Apify: Schedule your Actor · Integrations

FAQ

Is there a Google Trends API?

Google's own Trends API is in limited alpha. This actor returns the same kind of data — interest over time, related queries, regions — as structured rows on demand.

Why one row per date?

So the data drops straight into a spreadsheet, BI tool or database without unpacking nested lists: each row is one keyword on one date.

What does a typical run cost?

$0.03 per row plus $0.00005 per run start. The 2-keyword, 12-month Store example returned 277 rows (about $8.31) on Oct 23. Fewer keywords or a shorter range cost less.

Why is my interest score never above 100?

Google scales interest 0–100 within your request. 100 marks the busiest week for the most-searched keyword in the set; it is relative, not a search count.

Why are there no related queries for my keyword?

Google only publishes related queries above a volume threshold. Low-volume keywords return interest rows only.

Related actors

• Google SERP Scraper — Rankings & Keywords — see which pages rank for the keywords you are tracking.
• China Trends Tracker · 中国趋势汇总(微博/百度/头条/抖音) — trending topics on Weibo, Baidu, Toutiao and Douyin.
• Yahoo! Japan Realtime Trends + Buzz Tracker — real-time trending searches for the Japanese market.