Google Trends

Search-demand data from Google Trends without scraping the site or fighting its rate limits: an interest-over-time series for up to five keywords compared head to head, and the related-query lists that tell you what is actually driving a trend. Both endpoints are 5 credits.

Base URL: /v1/google_trends/...

Getting started

Every endpoint is a GET with query parameters and an x-api-key header.

# How big is this term, and how does it compare?
curl "https://www.socialcrawl.dev/v1/google_trends/explore?keywords=voice%20changer,reverse%20audio&timeframe=past_12_months&location=US" \
  -H "x-api-key: $SOCIALCRAWL_API_KEY"

# What is rising underneath it?
curl "https://www.socialcrawl.dev/v1/google_trends/rising?keyword=voice%20changer&timeframe=past_90_days" \
  -H "x-api-key: $SOCIALCRAWL_API_KEY"

Interest over time

GET /v1/google_trends/explore takes 1-5 comma-separated keywords and returns dated points scored 0-100 for each, plus each keyword's average across the window. With more than one keyword the values are normalised across the set, which is what makes them directly comparable: the single highest point across all keywords in the window is the 100, and everything else is relative to it.

category scopes the query to one numeric Google Trends category code, defaulting to 0 for all categories. That matters for ambiguous terms — "jaguar" in the automotive category and "jaguar" overall are two different series.

Rising and top related queries

GET /v1/google_trends/rising expands one keyword into two lists: rising queries with their growth percentage, and top queries with a 0-100 popularity score. Rising is where breakouts appear before they are big enough to move the main series, and top is what the demand is currently concentrated in.

It takes a single keyword, not a list, because Google Trends only returns related queries for one term at a time. The natural order is explore first to size a trend, then rising on the winner to find out what is behind it.

Endpoints

2 endpoints available.

Read this before you build

The 0-100 numbers are an index, not a volume. Google publishes no absolute search counts, and neither endpoint returns one. Two separate requests are not comparable to each other, because each is normalised to its own window. If you need to compare two terms, put both in one explore call rather than making two.

timeframe is a fixed preset list. past_hour, past_4_hours, past_day, past_7_days, past_30_days, past_90_days, past_12_months, past_5_years. There is no arbitrary date range on this platform, and the default is past_12_months.

Short windows change the granularity. past_hour and past_4_hours return minute-level points; past_5_years returns weekly ones. Do not assume a fixed point spacing when you chart the series.

For Korean demand, use Naver instead. Google Trends underrepresents Korea because Naver carries much of the search volume there. /v1/naver/search-trend is the equivalent, with the same relative-index caveat.

Notes

• All endpoints use GET with query parameters
• Authentication via the x-api-key header
• Responses follow the unified SocialCrawl schema
• location accepts an ISO country code (US), a full name (United States), or a numeric code (2840)
• A keyword with no measurable volume returns an empty series rather than an error