Google Trends Scraper - Interest & Trending Topics

Google Trends Scraper: keyword interest and trending topics

Collect relative search-interest timelines for chosen keywords or read the current trending-topic RSS feed for a country. The timeline mode also calculates an average interest value and a recent-period comparison, helping you review topic momentum with the underlying data points.

Use the output for content planning and market research. Interest values are relative indices, not absolute search volume, revenue or buying intent. This Actor exposes two focused modes; it does not collect related queries, related topics, city data or subregion breakdowns.

Start with a small query

{
  "mode": "interest",
  "keywords": ["ai agents"],
  "geo": "US",
  "timeframe": "today 3-m",
  "useProxy": true
}

For trending topics, use:

{
  "mode": "daily",
  "geo": "US",
  "useProxy": true
}

Open the dataset after the run. In interest mode, check for an error field before treating a row as a successful measurement. Export JSON to preserve the nested timeline points, or use the dataset API in your own workflow.

Input

Field	Meaning
mode	interest for keyword timelines or daily for the current trending RSS feed; default interest
keywords	Nonempty keyword list required in interest mode
geo	Country code such as US, GB or BR; default US. An empty value requests worldwide interest; daily mode falls back to US.
timeframe	Interest-mode period such as today 12-m, today 3-m or now 7-d; default today 12-m
useProxy	Default true; requests use Apify's residential proxy group. Access depends on the account and available proxy service.

Country and time-period support depend on Google. The source uses public, unofficial Trends endpoints and may rate-limit or reject requests. Proxy use does not guarantee success.

Understand the output

Interest mode returns one row per keyword with keyword, geo, timeframe, avgInterest, recentTrendPct and points. Each point contains the source's formatted date label and relative interest value.

• avgInterest is the mean of available timeline values, rounded to one decimal place.
• recentTrendPct compares the mean of the last quarter of available points with the mean of the entire timeline: (recent mean / overall mean - 1) × 100, rounded to a whole percent.
• If the overall average is zero or unusable, the percentage is null. This measure is not a prior-period growth rate or a forecast.
• Keywords are requested separately. Their normalized values must not be treated as directly comparable absolute search volumes.

Daily mode returns geo, title, traffic and pubDate from the currently available feed. traffic preserves the source's approximate traffic label when present; it is not a verified exact search count. The Actor does not archive previous daily feeds.

Pricing and repeat use

This Actor charges an Actor-start event per allocated GB of memory, with a minimum of one event. There is no separate per-result event. Open the Pricing tab for the active rate and any subscription-tier discounts, and check memory in the run settings before starting. Startup can be charged even if the run returns no usable results. Output limits cap collection; they do not guarantee coverage.

Save an Apify task and configure a schedule if you want to repeat an input. Keep exported observations in your own storage for comparisons; this Actor does not create schedules, maintain persistent trend history or send alerts itself.

Handling incomplete data

A failed keyword becomes an output row containing keyword, geo and error; other keywords can still succeed. Count useful timelines separately from errors. Daily-feed failures can fail the run, while an empty feed can yield no records. Check logs, source warnings and returned fields before using the data.

For support, open an issue with the run URL and sanitized input. Do not include proxy credentials or API tokens.