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Interest over time API

Google Trends interest over time API: a weekly series per keyword

One row per week, each with its own date and score. Drop it into a sheet, chart it, or feed it to your reorder plan. €0.0015 per call.

Start freeSee all data APIs
per 1,000 calls
€1.50
per call
€0.0015
0.15 cents
rows per call
up to 53
per 1,000 rows
≈ €0.0283

A clean trend line, one row per week

The interest over time API returns Google Trends search interest as a dated series: about 53 weekly points for a 12-month range, each scored 0 to 100. One call costs €0.0015, and 1,000 calls cost €1.50. Prices for every other source are on our all data APIs and prices page. Save your keywords once, and each run's series is stored in your Scrapewise account for the table, Excel, your AI assistant or the API.

It returns the line and nothing else. No region rows, no related searches. That's on purpose. If you build forecasts or seasonality charts, you want a column of dates and a column of numbers, and you don't want to filter out rows you never asked for.

Here's a slice of a real call for "bitcoin" in the US, run on 16 September 2026. The week of Aug 16 to 22 scored 28. Three weeks later, Sep 6 to 12, it was down to 16. That drop is visible in a sheet in seconds, and the same call on your own products shows you when buyers start and stop looking.

Every point keeps the week it describes. The date you ran the call is stored in its own column, so a series you pulled in March still lines up with one you pulled in September.

Who needs the line on its own

  • Sellers planning stock

    Reorder sheets need weeks and numbers. Pull 5 years for your top sellers and see which weeks demand peaks, then place orders with your supplier's lead time in mind.

  • Analysts and data teams

    Load the series into Python, R or BigQuery without cleaning. The dates sort, the values are numbers, and each row says which keyword it belongs to.

  • Brand owners watching a rival

    Put your product name and a competitor's on the same call and watch which one people search more, week by week, over the last year.

How it works

  1. Enter your keywords

    Type one term, or several separated by commas, like 'air fryer, slow cooker'. Add a two-letter country code, or keep the US default.

  2. Choose the range and schedule

    Pick from past hour to 2004 to today. 12 months gives weekly steps. Schedule it weekly, and every run is saved with the date you ran it.

  3. Chart the rows

    Download Excel, pull rows from your own code, or ask your AI assistant: 'did air fryer or slow cooker grow faster over the last 3 months?'

Set it up once. The data keeps coming.

Save your search once and it runs by itself. Every run lands in your own Scrapewise database, and you pick how to read it.

  1. Set it up once

    Add your ASINs, keywords, places or apps to a scraper in the web app. New accounts get 5 free requests.

  2. Runs on your schedule

    Pick daily, weekly on the days you choose, every few days, or the first or last day of the month. Scheduled runs start at night, European time. Need it more often? Start runs from your own code.

  3. Saved in your database

    Each run adds dated rows, so this week sits next to last week. Rows are kept for 90 days.

  4. Use it your way

    Open the table in the web app and download the latest run as an Excel file. Ask your own AI assistant about it. Or pull the rows into your code with an API key.

Ask your AI assistant about your own data

Connect Claude Desktop, Claude Code or another MCP app with a read-only key. The assistant reads the rows you've already collected, at no extra cost on Scrapewise. With a full-access key it can start a run for you too.

  • Which of my ASINs lost the Buy Box this week?
  • Which competitor cut prices the most since Monday?
  • Show the keywords where I dropped out of the top 10.

What you send and what you get back

You send a keyword, and if you like a country code and a time range. You get one row per point in time: about 53 rows for 12 months, each with a week label, an ISO date, a Unix timestamp and a 0 to 100 score.

You give
  • Search termrequired
    bitcoin
  • Location (country code)optional
    US
  • Time rangeoptional
    today 12-m
  • Data typeoptional
    TIMESERIES
You get

Up to 53 rows per call, 19 columns each

  • sw status
  • sw source url
  • sw position
  • sw title
  • sw url
  • sw external id
  • sw id kind
  • sw published at
  • sw location
  • sw fetched at
  • date
  • timestamp
  • +7 more, see all columns

Sample rows: "bitcoin" in the US, weekly

Real rows from a call on 16 September 2026, past 12 months. The eight most recent weeks are shown.

All 19 columns

  • sw status
  • sw source url
  • sw position
  • sw title
  • sw url
  • sw external id
  • sw id kind
  • sw published at
  • sw location
  • sw fetched at
  • date
  • timestamp
  • values[0]_query
  • values[0]_value
  • values[0]_extracted_value
  • ctx_search_parameters_q
  • ctx_search_parameters_geo
  • ctx_search_parameters_date
  • ctx_search_metadata_google_trends_url

8 sample rows, 19 columns. One call returns up to 53 rows.

8 sample rows, 19 columns. One call returns up to 53 rows.
sw status_sw_statusResult of this row: OK, no results, or an errorsw source url_sw_source_urlThe input you gave: a link, keyword or IDsw position_sw_positionRank of the item as the site shows itsw title_sw_titleMain name of the itemsw url_sw_urlDirect link to the itemsw external id_sw_external_idThe site's own ID for this itemsw id kind_sw_id_kindWhat kind of ID the external ID issw published at_sw_published_atPublish or update date in ISO formatsw location_sw_locationPlace the result is priced or ranked forsw fetched at_sw_fetched_atWhen we collected this row (UTC)datedateDatetimestamptimestampTimestampvalues[0]_queryvalues[0]_queryValues #1 queryvalues[0]_valuevalues[0]_valueValues #1 valuevalues[0]_extracted_valuevalues[0]_extracted_valueValues #1 extracted valuectx_search_parameters_qctx_search_parameters_qRequest context: search parameters qctx_search_parameters_geoctx_search_parameters_geoRequest context: search parameters geoctx_search_parameters_datectx_search_parameters_dateRequest context: search parameters datectx_search_metadata_google_trends_urlctx_search_metadata_google_trends_urlRequest context: search metadata google trends url
OKhttps://trends.google.com/trends/explore?q=bitcoin&geo=US46bitcoinhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D1785024000topic2026-07-26T00:00:00ZUS2026-09-16T11:01:50ZJul 26 – Aug 1, 20261785024000bitcoin2121bitcoinUStoday 12-mhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D
OKhttps://trends.google.com/trends/explore?q=bitcoin&geo=US47bitcoinhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D1785628800topic2026-08-02T00:00:00ZUS2026-09-16T11:02:27ZAug 2 – 8, 20261785628800bitcoin2121bitcoinUStoday 12-mhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D
OKhttps://trends.google.com/trends/explore?q=bitcoin&geo=US48bitcoinhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D1786233600topic2026-08-09T00:00:00ZUS2026-09-16T11:03:04ZAug 9 – 15, 20261786233600bitcoin2020bitcoinUStoday 12-mhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D
OKhttps://trends.google.com/trends/explore?q=bitcoin&geo=US49bitcoinhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D1786838400topic2026-08-16T00:00:00ZUS2026-09-16T11:03:41ZAug 16 – 22, 20261786838400bitcoin2828bitcoinUStoday 12-mhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D
OKhttps://trends.google.com/trends/explore?q=bitcoin&geo=US50bitcoinhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D1787443200topic2026-08-23T00:00:00ZUS2026-09-16T11:04:18ZAug 23 – 29, 20261787443200bitcoin2525bitcoinUStoday 12-mhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D
OKhttps://trends.google.com/trends/explore?q=bitcoin&geo=US51bitcoinhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D1788048000topic2026-08-30T00:00:00ZUS2026-09-16T11:04:55ZAug 30 – Sep 5, 20261788048000bitcoin2121bitcoinUStoday 12-mhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D
OKhttps://trends.google.com/trends/explore?q=bitcoin&geo=US52bitcoinhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D1788652800topic2026-09-06T00:00:00ZUS2026-09-16T11:05:32ZSep 6 – 12, 20261788652800bitcoin1616bitcoinUStoday 12-mhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D
OKhttps://trends.google.com/trends/explore?q=bitcoin&geo=US53bitcoinhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D1789257600topic2026-09-13T00:00:00ZUS2026-09-16T11:06:09ZSep 13 – 19, 20261789257600bitcoin1717bitcoinUStoday 12-mhttps://trends.google.com/trends/embed/explore/TIMESERIES?hl=en&tz=420&req=%7B%22category%22%3A0%2C%22comparisonItem%22%3A%5B%7B%22geo%22%3A%22US%22%2C%22keyword%22%3A%22bitcoin%22%2C%22time%22%3A%22today+12-m%22%7D%5D%2C%22property%22%3A%22%22%7D

What each column means

Columns starting with sw are shared by every Scrapewise data API. The rest come from Google Trends.

The point in time

date is Google's week label, like Jul 26 to Aug 1, 2026. sw published at turns the start of that week into an ISO date that sorts and charts properly, and timestamp holds the same moment in Unix seconds. sw position is the point's order in the series, oldest first.

  • date
  • sw published at
  • timestamp
  • sw position

The score

values query names the keyword. values value is the score as text, the way Google shows it, and values extracted value is the same score as a number you can calculate with.

  • values[0]_query
  • values[0]_value
  • values[0]_extracted_value

Row identity

sw title is the keyword. sw external id is the week timestamp, so the same week matches across runs, and sw id kind says what kind of ID that is. sw location is the country code the series was measured in. sw status is OK, no results or error.

  • sw title
  • sw external id
  • sw id kind
  • sw location
  • sw status

Links and collection time

sw source url opens the Trends page for your keyword. sw url is the chart link the data came from. sw fetched at is when we collected the row, in UTC, kept apart from the week the row describes.

  • sw source url
  • sw url
  • sw fetched at

Your request

The keyword, country and time range you asked for, plus the Trends link, are repeated on every row. When a sheet holds 50 products, these are the columns you filter on.

  • ctx_search_parameters_q
  • ctx_search_parameters_geo
  • ctx_search_parameters_date
  • ctx_search_metadata_google_trends_url

What people build on a weekly series

01

Seasonality charts

Pull 5 years for a product and mark the peak weeks. If the peak lands in the same week four years out of five, you can plan around it.

02

Two product names on one line

Send both terms in one call and see which one people search more each week. Useful when you're picking a listing title or a brand name.

03

Reorder forecasts

Feed the weekly scores into your reorder sheet as a demand signal next to your own sales. A rising line with flat sales can mean your listing is losing to someone else.

04

Is the fad over?

Compare the last 8 weeks with the same 8 weeks last year. Fidget toys, cold plunge tubs, whatever is hot in your group this month: the numbers tell you before your inventory does.

05

Before and after a launch

Pull the series before and after a TV spot, a TikTok push or a price change and check if searches for your brand moved.

What it costs in real life

  • Seller with 400 products

    Refreshes 5 years of weekly interest for 400 products once a month to plan orders. 400 calls, €0.60 a month.

    calls per month
    400
    cost per month
    €0.60

  • Analyst tracking 100 terms daily

    Pulls the past 7 days for 100 search terms every day for a dashboard. About 3,000 calls, €4.50 a month.

    calls per month
    3,000
    cost per month
    €4.50

  • Reseller watching fads

    Checks 30 trending product names every week to see if they're still rising. About 130 calls, under €0.20 a month.

    calls per month
    130
    cost per month
    €0.195

Why use this API for time series

  • Dates you can trust

    Each row keeps the week it describes in date, sw published at and timestamp. The collection time lives in its own column and never overwrites them.

  • Only what you asked for

    About 53 rows for a year, all of them points on the line. No region rows to filter out before you chart.

  • Cheap enough to run daily

    At €0.0015 a call, 100 keywords a day for a month is €4.50. No subscription to cancel when the season ends.

What your trend lines cost

Each call costs €0.0015, whether it returns 53 weeks or 5 years. Enter your keyword count and how often you refresh. Compare all data APIs

Rows (up to)
53,000
You pay
€1.50
FAQ

Frequently asked questions

Yes. Each point carries its own week, both as Google's label and as a sortable ISO date. The day you ran the call goes in the separate sw fetched at column, so old and new pulls line up on the same weeks.

Ready to pull Google data into your stack?

Try it with 5 free requests. Then top up from €5 and pay €0.0015 per call, no plan. See pay-as-you-go pricing for the wallet details.

Start freeSee all data APIs

Explore other data APIs

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Google TrendsGoogle Trends API: demand over time and by region in one callGet Google Trends data as rows: weekly interest over time plus interest by region, both in one call for €0.0015. No pytrends breakage.View data API →Google TrendsCompare keywords by region: which term wins whereCompare 2 or more search terms and see which one leads in each state or region. €0.0015 per call, about 51 rows for the US.View data API →Google TrendsGoogle Trends interest by region API: where one keyword is hotSee where one keyword is searched most, region by region, scored 0 to 100. €0.0015 per call. Pick ad targets and stock locations.View data API →Google TrendsGoogle Trends related queries API: top and rising searchesGet the searches people make around your keyword: 25 top and 25 rising, including breakouts. €0.0015 per call. New keyword ideas each week.View data API →