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Spot seasonal search patterns over 5 years

Pull 5 years of weekly Google search interest for seasonal keywords to see when demand starts, peaks and fades each year. Useful for SEO content calendars, ad budgets and inventory timing.

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Google Trends Scraper (Reliable)
Google Trends Scraper (Reliable)seodatalab/google-trends-scraper
Search term
Geo
Time range
Interest over time
+2 fields
Text
Number
Boolean
List
Object

Input

Search terms(required):sunscreen+3
Country / region code:US
Time range:today 5-y
Data to collect:interestOverTime

Output fields

Search term
Geo
Time range
Interest over time
Note
Error

How it works

Sign up on Apify or log in

The Google Trends Scraper (Reliable) Actor is ready to run with the inputs already set for "Spot seasonal search patterns over 5 years". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Spot seasonal search patterns over 5 years" task

The Google Trends Scraper (Reliable) Actor will start running based on the input automatically. You can also change all the input fields, like search terms, country / region code, and more, to match your specific use case.

Receive the "Spot seasonal search patterns over 5 years" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as search term, geo, time range, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Spot seasonal search patterns over 5 years" task via API.

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Integrate "Spot seasonal search patterns over 5 years" into your workflow

Connect "Spot seasonal search patterns over 5 years" with 100+ integrations, or run it via API or MCP.

Webhook

Webhook

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LlamaIndex

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OpenAI

OpenAI

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Frequently asked questions

The seasonal search patterns task returns about 260 weekly 0–100 Google search interest scores per keyword covering the last 5 years.

Set the time range to all for monthly data back to 2004, or enter a custom range such as 2010-01-01 2015-12-31.