Pinterest Trending Topics & Shopping Category Scraper

Pinterest Trending Topics & Shopping Category Scraper produces shop, seller and product lists: online sellers, brands and products with prices, ratings and stock. Columns include term, name or title, name, region, trend type, rank.

A seller list is a business list; a product list is market research. Check the columns before you buy.

$0.99per 1,000 results, plus a start fee and platform usage
7columns in the output
0lists on this site use it
2026-10last updated on the Store

The columns you get

  • Termterm
  • Name or titletitle
  • Namename
  • Regionregion
  • Trend typetrendType
  • Rankrank
  • Week over week changeweekOverWeekChange

From the published output schema, checked 2026-11-14.

What it costs

  • 100 rows in one run$0.50
  • 1,000 rows in one run$1.39
  • 10,000 rows in one run$10.30

Free-plan prices: $0.99 per 1,000 results plus a $0.40 start fee (4 GB run) per run, plus Apify platform usage at $0.20 per compute unit. The Free plan includes $5 a month (Apify pricing).

What you fill in

  • Mode (required)
    Choose a Pinterest Trends dataset.
  • Region
  • Trend type
  • Lookback window
  • End date
  • Interest
  • Moment
  • Keywords to include
  • Keywords to exclude
  • Age group
    Pinterest audience age filter for trending searches and keyword research.

Other shop, seller and product lists

Questions

What does Pinterest Trending Topics & Shopping Category Scraper cost?

$0.99 per 1,000 results on the Apify Store (Free plan), plus a start fee per GB of run memory and Apify platform usage: one run of 1,000 rows costs about $1.39 before platform usage. The Free plan includes $5 a month.

Do I need to code to use it?

No. You fill in a form on the Apify Store page, start the run and download the results as CSV, Excel or JSON. You need a free Apify account.

Is it a good fit for a business list?

A seller list is a business list; a product list is market research. Check the columns before you buy.

Store data checked 2026-11-14Columns from the published schema