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.

topics = tf.suggestions("artificial intelligence")
# [TopicSuggestion(mid='/m/0mkz', title='Artificial intelligence', type='Professional field')]

data = tf.interest_over_time(
    keywords=[topics[0].mid, "artificial intelligence"],
    timeframe=Timeframe.PAST_YEAR,
    region=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 trending_now(). type disambiguates same-name entities ("Nike" returns both the company and the goddess) and is None when Google omits it.