Topics and search suggestions

Resolve a name to a Google Trends topic id. A topic aggregates every spelling and translation of a concept, so it measures far more search activity than a literal phrase.

JavaScript Python

Topics and search suggestions

Google distinguishes a search term (the literal string) from a topic (the entity, in every spelling and language). suggestions() finds the topic; every query method already accepts one — pass the mid where you would pass a keyword.

const topics = await tf.suggestions("artificial intelligence");
// [{ mid: "/m/0mkz", title: "Artificial intelligence", type: "Professional field" }]

const data = await tf.interestOverTime(
  [topics[0].mid, "artificial intelligence"],
  Timeframe.PAST_YEAR,
  Region.US,
);
// { "/m/0mkz": 62, "artificial intelligence": 1 }

That gap is the point: the topic scores 62 where the literal phrase scores 1, because it aggregates every phrasing and translation people actually search.

suggestions() needs no cookie and no proxy — it answers on IPs the widgetdata endpoints reject with 429, same as trendingNow(). type disambiguates same-name entities ("Nike" returns both the company and the goddess) and is null when Google omits it.