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Google Trends API: access, examples and data limits

Use a Google Trends API to investigate seasonality and build search-interest reports. This guide compares Google’s official alpha with Nexscope’s keyword and trending-topic endpoints, shows a request example and explains how to keep relative interest separate from search volume.

Quick answer: Use a keyword-interest request when you already know the term to investigate. Use a trending-topic request to discover recent queries. Keep the provider, country, dates and scale beside each result. Use a separate keyword-metrics source when the question is monthly search volume.

Documentation reviewed October 28, 2026 by Nexscope Team. No paid Trends request was executed for this article. Input examples are integration examples, not observed trend results.

Is there an official Google Trends API?

Yes: Google’s current Trends API page describes an alpha that requires an application. It lists a rolling five-year window, several aggregation intervals, regional data and consistently scaled data. The page does not establish open access for every developer.

Nexscope’s endpoints are separate services with Nexscope authentication, credits and schemas. Do not use a Google alpha example as a drop-in Nexscope request or assume that access to one grants access to the other.

The distinction matters in a dashboard: labeling every column “Google Trends volume” would combine different measurements under one name.

Which Nexscope Trends endpoint matches your task?

The keyword endpoint accepts keyword, region, dayRangeStart and dayRangeEnd. Its documented series includes trendInfoForKeys, keyword labels and dated trendValues.

The time-based endpoint accepts region and days. It describes recent query records rather than the same keyword-history series. Inspect the definitions of any returned volume or growth field before mixing it with another dataset.

For example, a team considering a seasonal product starts with the product term and a fixed historical window. A team scanning recent public interest starts with the time-based route, then checks whether the discovered queries have any relevant commercial intent. A breaking news query can be popular and still have no useful connection to the product.

What does a keyword request look like?

The current keyword route is:

POST https://api.nexscope.ai/googleTrend/getTrendByKeys
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

This is a documentation-derived input example:

{
  "keyword": "portable blender",
  "region": "US",
  "dayRangeStart": "2025-10-01",
  "dayRangeEnd": "2026-09-30"
}

The request defines a past annual window; it does not imply that the example has been run or that a complete series will be returned. The current keyword field is a string. Start with one term and inspect the documented rules before assuming that a JSON array or a list of comma-separated terms is supported.

A Python application can submit that JSON with an HTTPS client and then retain the original response. Check HTTP errors, the outer business code and the presence of usable data separately. Do not construct a successful chart from an authentication error or a null payload. Keep the API key on your server or in your local environment rather than in browser source.

How do you interpret the 0–100 interest scale?

An interest index is not a search count. Google’s Trends data FAQ explains that the website’s results use sampled, normalized search data and that low-volume terms can appear as zero. Nexscope’s keyword contract also describes a normalized 0–100 series. Google’s alpha page describes consistently scaled data, so its behavior should not be inferred from the website index.

Consider a synthetic example: one independently collected series peaks at 100, and another also peaks at 100. That does not establish equal demand. Each peak may have been normalized within a different request.

Retain returned values as supplied before converting types. If a field is a string, distinguish a valid numeric string from an empty or nonnumeric value. Do not quietly convert every parse failure to zero.

How can a developer build a useful seasonal report?

Separate the observation from the business hypothesis. A proposed report can follow this sequence:

1. Define one question, such as when a product-related term attracts interest in the target country.
2. Fix the keyword wording, region and historical window before comparing results.
3. Save the request, collection time and returned series, including gaps.
4. Inspect recurring patterns across comparable periods rather than selecting only the largest spike.
5. Check keyword-volume estimates separately and inspect which search pages serve the query.
6. Add marketplace evidence before making an assortment or inventory decision.

Use the keyword research API workflow for demand estimates and the Google SERP API guide to inspect query intent. These are different questions, so keep the original field names and source labels in your report.

What should you validate before scheduling repeat calls?

Use a small acceptance checklist before adding a scheduler:

Store the last usable observation alongside a failed refresh. A failed request should make the report stale, not make demand disappear. Repeated execution, storage and alerts are application responsibilities; one API response does not configure a monitoring service.

Last reviewed: 2026-10-28 · Maintained by the official Nexscope team · Editorial & evidence policy.