# Google Trends Scraper: Unlimited Keywords & Trending Now (`robertosan16/google-trends-scraper`) Actor Google Trends API alternative with no 5-keyword limit: any number of keywords and countries on one scale, daily data for years, interest by region and city, related and rising queries, ready insights and Trending now with search volumes. - **URL**: https://apify.com/robertosan16/google-trends-scraper.md - **Developed by:** [Robert Khairislamov](https://apify.com/robertosan16) (community) - **Categories:** SEO tools, Marketing, News - **Security:** Limited permissions - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.40 / 1,000 keyword reports This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## Google Trends Scraper: Unlimited Keywords & Trending Now Export Google Trends data for **any number of keywords and countries**: interest over time, interest by region, city and metro area, top and rising related queries, and the **Trending now** lists with search volumes. Every keyword comes with ready **insights**: average, peak, latest value, recent change, year-over-year change, trend direction and the best month of the season. Compare everything on **one 0–100 scale** without Google's limit of 5 terms. No browser, no login, no API key. **$2 per 1,000 keyword reports, $0.50 per 1,000 trending searches.** ### What can this Google Trends scraper do? - 📈 **Interest over time** for any time range on the Google Trends website: past hour, 4 hours, day, 7 days, 30 days, 90 days, 12 months, 5 years, since 2004, or your own dates. - 📅 **Daily data for 5 years or since 2004**: Google gives days only for periods up to about 9 months. Turn on **Daily data for long periods** and every keyword gets one value per day for any period. The Actor reads the days in windows and ties each window to Google's weekly or monthly series, so the days stay on one scale: in our test, 5 years of daily "matcha" matched Google's weekly curve with a correlation of 0.998 and no drift between windows. - ⚖️ **Unlimited keywords on one scale**: Google compares at most 5 terms at a time. Turn on **Compare on one scale** and the Actor compares 10, 50 or 200 keywords and countries on one 0–100 scale. The numbers equal Google's own comparison, and small keywords get decimals (`0.37`) instead of Google's `0` and `<1`. - 💡 **Insights in every record**: average interest, peak and its date, latest complete value, change of the last 4 periods against the 4 before (the last week against the week before for daily data), year-over-year change, trend direction (rising, stable, falling), and the best and worst month of the season. Ready to sort and filter, with no spreadsheet formulas. - 🗺️ **Interest by region**: states and provinces, countries for worldwide searches, **cities** (with coordinates) or US **metro areas (DMA)**. - 🔎 **Related queries**: top and rising, with `Breakout` marked. Each query is flagged when it does not contain your keyword and when it looks like spam (web addresses, emoji), because rising lists also carry bot traffic. - 🆕 **Only new rising queries**: for weekly monitoring, save a keyword only when it has rising queries that earlier runs did not see, listed in `newRisingQueries`. Keywords without anything new are not saved and not charged. - 🔥 **Trending now**: the full list for a country or region for the past 4 hours, 24 hours, 48 hours or 7 days, often 200–500 searches, not just the 10 of Google's RSS feed. Each comes with its search volume (`200K+`), growth, start time, whether it is still trending, categories and related searches. - 🌍 **Many countries in one run**: every keyword is checked in every country or region you add (`US`, `GB`, `US-CA`, `DE-BY`), by code or by name. - 🏷️ **Topics, categories and search types**: search a keyword as a Google topic ("Coffee", the drink, in all languages), limit data to one of Google's categories, and measure web, image, news, Google Shopping or YouTube search. - 🔗 **Explore links**: paste links from the Google Trends website and get exactly the same comparison as data. - 🛡️ **Built to finish**: the Actor keeps Google sessions, opens a new one when Google limits a session, and moves to residential addresses if limits continue. Partial problems (for example no city data for a small country) are noted in the record instead of failing the run. ### What data does it extract? **Keyword reports** (`type: "interest"`), one per keyword and location: | Field | Example | |---|---| | `keyword` / `location` / `locationName` | matcha / US / United States | | `timeRange` / `startDate` / `endDate` / `resolution` | today 5-y / 2021-10-17 / 2026-10-18 / WEEK | | `averageInterest` / `peakInterest` / `peakDate` | 44.4 / 100 / 2026-04-12 | | `latestInterest` / `latestDate` | 62 / 2026-10-11 | | `recentChangePercent` / `yearOverYearPercent` | −11 / 22.2 | | `trendDirection` / `trendPercent` | rising / 160.3 | | `bestMonth` / `worstMonth` / `seasonalityPercent` | April / November / 57.3 | | `topRegion` / `topRelatedQuery` / `topRisingQuery` | Hawaii / matcha tea / ryze matcha | | `interestOverTime` | every point: `date`, `value`, `isPartial` | | `interestByRegion` | `geoCode`, `geoName`, `value` (and `lat`, `lng` for cities) | | `relatedQueriesTop` / `relatedQueriesRising` | `query`, `value` or `increase`, `isBreakout`, `containsKeyword`, `looksLikeSpam` | | `newRisingQueries` | with **Only new rising queries**: the rising queries not seen in earlier runs | | `oneScale` / `comparedWith` | true / \["coffee (US)", "tea (US)"] | | `topicTitle` / `category` / `searchType` | Coffee / 71 (Food & Drink) / youtube | | `trendsUrl` | the same view on the Google Trends website | **Trending searches** (`type: "trending"`): `location`, `rank`, `term`, `searchVolume` (200000), `searchVolumeText` (200K+), `increasePercent`, `startedAt`, `endedAt`, `isActive`, `categories`, `relatedSearches`, `exploreUrl`. ### How to scrape Google Trends 1. Enter your **keywords** and **locations** (leave locations empty for worldwide). 2. Pick a **time range**. Turn on **Compare on one scale** to compare popularity; leave it off to see each keyword's own trend. 3. Optionally add **Trending now** locations, or paste **explore links** from the Google Trends website. 4. Click **Start** and download the results as JSON, CSV, Excel or HTML, or use them through the API. The **Keyword insights** and **Trending now** tabs show the main fields as tables. A step-by-step guide with Python examples, 15 drinks on one scale and a check against Google's own numbers: [How to Compare More Than 5 Keywords in Google Trends on One Scale](https://medium.com/@robertkhairislamov/how-to-compare-more-than-5-keywords-in-google-trends-on-one-scale-88bb538fcc4c). #### Example input ```json { "keywords": ["matcha", "cold brew", "kombucha", "yerba mate", "hojicha", "chai"], "locations": ["US", "GB"], "timeRange": "today 5-y", "compareOnOneScale": true, "includeInterestByRegion": true, "regionResolution": "default", "includeRelatedQueries": true, "trendingLocations": ["US"], "trendingHours": "24", "trendingCategories": ["Food and Drink"] } ``` Time ranges are `now 1-H`, `now 4-H`, `now 1-d`, `now 7-d`, `today 1-m`, `today 3-m`, `today 12-m`, `today 5-y`, `all` and `custom` with `startDate` and `endDate`. #### Example output A keyword report (lists shortened): ```json { "type": "interest", "keyword": "matcha", "searchedFor": "matcha", "location": "US", "locationName": "United States", "timeRange": "today 5-y", "timeRangeName": "Past 5 years", "startDate": "2021-10-17", "endDate": "2026-10-18", "resolution": "WEEK", "category": 0, "categoryName": "All categories", "searchType": "web", "oneScale": false, "comparedWith": null, "hasData": true, "averageInterest": 44.4, "peakInterest": 100, "peakDate": "2026-04-12", "latestInterest": 62, "latestDate": "2026-10-11", "recentChangePercent": -11, "yearOverYearPercent": 22.2, "trendDirection": "rising", "trendPercent": 160.3, "bestMonth": "April", "worstMonth": "November", "seasonalityPercent": 57.3, "topRegion": "Hawaii", "topRelatedQuery": "matcha tea", "topRisingQuery": "ryze matcha", "interestOverTime": [ { "date": "2026-10-04", "value": 63, "isPartial": false }, { "date": "2026-10-11", "value": 62, "isPartial": false }, { "date": "2026-10-18", "value": 62, "isPartial": true } ], "interestByRegion": [ { "geoCode": "US-HI", "geoName": "Hawaii", "value": 100 }, { "geoCode": "US-CA", "geoName": "California", "value": 81 } ], "relatedQueriesTop": [ { "query": "matcha tea", "value": 100, "containsKeyword": true, "exploreUrl": "https://trends.google.com/trends/explore?q=matcha+tea&date=today+5-y&geo=US" } ], "relatedQueriesRising": [ { "query": "ryze matcha", "increase": "Breakout", "increasePercent": 37100, "isBreakout": true, "containsKeyword": true, "looksLikeSpam": false, "exploreUrl": "https://trends.google.com/trends/explore?q=ryze+matcha&date=today+5-y&geo=US" } ], "trendsUrl": "https://trends.google.com/trends/explore?date=today+5-y&geo=US&q=matcha&hl=en-US", "warnings": null, "scrapedAt": "2026-10-20T06:03:40.487Z" } ``` A trending search: ```json { "type": "trending", "location": "GB", "locationName": "United Kingdom", "hours": 24, "rank": 1, "term": "spurs vs coventry", "searchVolume": 200000, "searchVolumeText": "200K+", "increasePercent": 1000, "startedAt": "2026-10-19T16:10:00.000Z", "endedAt": null, "isActive": true, "categories": ["Sports"], "relatedSearches": ["tottenham", "spurs", "james maddison", "tottenham vs coventry"], "exploreUrl": "https://trends.google.com/trends/explore?date=now+1-d&geo=GB&q=spurs+vs+coventry&hl=en-US", "scrapedAt": "2026-10-20T05:51:35.341Z" } ``` ### How does the one-scale comparison work? Google Trends shows every comparison on its own 0–100 scale, where 100 is the highest point of the compared terms, and it compares at most 5 at a time. To put more on one scale, the Actor first finds the keyword with the highest peak by comparing groups of five, then compares every other keyword next to it and rescales each group by how that keyword came out. The result equals what Google would show if it compared all your keywords at once. In our tests the overlapping keywords matched Google's own five-term comparison exactly. Google rounds to whole numbers, so next to a big keyword small ones become `0`, `1` or `<1`. The Actor then measures the small keywords again in groups led by a keyword only a little bigger than them, and brings them back to the shared scale. They get decimals, for example `0.34` for "yerba mate" next to "coffee" at 100. This costs a few extra requests and no extra charge. ### Use cases - **SEO and content planning**: find which topics and queries are rising, when in the year people search for them, and which regions care most. - **Product and market research**: compare demand for products, brands or features across countries on one scale, and see whether interest is growing year over year. - **Ecommerce and seasonality**: get the best month of each product category to plan stock, campaigns and prices. - **Newsrooms and social media**: follow Trending now with search volumes and related searches every few hours. - **Investors and analysts**: track interest in companies, products and tickers as an alternative data signal. - **Datasets and AI**: clean time series and insights for dashboards, forecasting and LLM pipelines. ### How much does it cost? You pay only for results: | Event | Free plan | Starter | Scale | Business | |---|---|---|---|---| | Keyword report (one keyword in one location, with timeline, regions, related queries and insights) | $2.00 / 1,000 | $1.80 / 1,000 | $1.60 / 1,000 | $1.40 / 1,000 | | Trending search (one record of a Trending now list) | $0.50 / 1,000 | $0.45 / 1,000 | $0.40 / 1,000 | $0.35 / 1,000 | There is no start fee, and the extra requests of the one-scale comparison are free. Example: 50 keywords in 2 countries cost 100 reports, $0.20. The $5 monthly credit of the Apify free plan covers about 2,500 keyword reports. To cap a run's cost, set the maximum charge in the run options; the Actor stops cleanly when it is reached. ### Tips - **Trend shape or popularity?** For the shape of each keyword's trend (season, growth), leave **Compare on one scale** off: each keyword gets the full 0–100 range. To rank keywords by popularity, turn it on. - **Weekly tracking**: save your input as a task and add a schedule; connect the dataset to Google Sheets to build a chart over time. - **New rising queries every week**: turn on **Only new rising queries**, save the input as a task and schedule it weekly. Each run returns only the keywords with rising searches you have not seen yet, in `newRisingQueries`, and you pay only for those. - **Daily data for long periods**: with **Daily data for long periods**, 5 years take about a minute per keyword, since Google answers 8 windows of 250 days for each. The current day is marked `isPartial`. - **Big Trending now lists**: 48 hours or 7 days can hold 1,000+ searches per country. Set **Trending now: maximum per location** (for example 50) or pick categories to keep only what you need. - **Rising queries**: filter `relatedQueriesRising` by `containsKeyword` to drop unrelated noise, and by `looksLikeSpam` to drop spam. - **News behind a trend**: run our [Google News Scraper](https://apify.com/robertosan16/google-news-scraper) with the trending term. - **Errors per keyword**: see the `warnings` field of each record and the `SUMMARY` record in the run's key-value store. ### FAQ **Why not just ask an AI chatbot?** A chatbot cannot read Google Trends for you: it guesses from what it learned or from a few articles, and gives no timeline. This Actor reads Google Trends itself and returns the numbers week by week, by region and with related queries, in the same fields every time, at a fixed price. AI agents can call it as a tool through Apify's MCP server. **Are these search volumes?** No. Google Trends shows relative interest from 0 to 100, not the number of searches. Trending now is the exception: Google gives an approximate volume such as `200K+`. **Why do numbers change a little between runs?** Google computes Trends from a sample of searches, so repeated requests can differ by a point or two, especially for small keywords and short time ranges. The last point is often incomplete; it is marked `isPartial` and left out of the insights. **What about related topics?** Google currently returns related topics only to its own website and an empty list to every other client, so the Actor does not offer them. Related queries work. **Is it legal to scrape Google Trends?** The Actor reads publicly available Google Trends data without logging in. Check the terms that apply to your use case. This Actor is not affiliated with Google. ### Integrations and API - **Google Sheets, Slack, email and BI tools**: connect the Actor to Make, Zapier or n8n, or use the **Integrations** tab of this Actor. - **Webhooks**: call your own URL when a run finishes, for example to load the results into your database. - **AI agents (MCP)**: add `https://mcp.apify.com?tools=robertosan16/google-trends-scraper` as an MCP server in Claude, Cursor or VS Code, and your agent can check trends and trending searches with this Actor. - **API**: one request runs the Actor and returns the records, for runs of up to 5 minutes. Start longer runs with the `runs` endpoint and read the dataset when they finish. ```bash curl -X POST "https://api.apify.com/v2/acts/robertosan16~google-trends-scraper/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{"keywords":["matcha","cold brew"],"locations":["US"],"timeRange":"today 12-m","compareOnOneScale":true}' ``` Missing a field or a feature? Open an issue in the Issues tab or email , and we will reply quickly. ### 中文简介 **谷歌趋势（Google Trends）数据导出工具**：导出任意数量关键词和国家/地区的**搜索热度变化**、按地区（省/州、城市、美国 DMA 区域）的热度、热门和**飙升的相关搜索**，以及 “Trending now” **实时热搜榜**（含搜索量）。谷歌趋势一次最多对比 5 个关键词；开启 **Compare on one scale** 后，可以把 10 个、50 个甚至 200 个关键词放在同一个 0–100 标尺上对比，长周期也可以按天输出。每个关键词自带分析指标：平均值、峰值、最新值、近期变化、同比变化、趋势方向和旺季月份。 适合出海市场调研、跨境电商选品、SEO 关键词研究和内容选题。无需浏览器、无需登录、无需 API 密钥。 价格：每 1,000 份关键词报告 2 美元，每 1,000 条热搜 0.50 美元，无启动费；Apify 免费套餐每月约可获取 2,500 份关键词报告。 结果可导出为 JSON、CSV、Excel 或 HTML，也可以通过 API、定时任务、Webhook 或 n8n、Make、Zapier 接入。有问题请在 Issues 页面提问，或发邮件至 support@mozartstandard.com。 # Actor input Schema ## `keywords` (type: `array`): Search terms to check, one per line. Each keyword gets its own record for every location. You can also enter Google topic IDs such as /m/02vqfm. ## `locations` (type: `array`): Countries or regions: codes such as US, GB, US-CA, DE-BY, or names such as Germany. Leave empty or enter Worldwide for the whole world. Every keyword is checked in every location. ## `timeRange` (type: `string`): The period of the data, as on the Google Trends website. Google sets the step: minutes for the past hours, hours for 7 days, days up to 9 months, weeks up to 5 years, months beyond. ## `startDate` (type: `string`): First day of a custom range, from 2004-01-01. Used when the time range is "Custom dates". ## `endDate` (type: `string`): Last day of a custom range. Defaults to today. ## `dailyData` (type: `boolean`): Google gives days only for periods up to about 9 months, weeks up to 5 years and months beyond. Turn this on to get one value per day for any period, also 5 years or since 2004: the Actor reads the period in windows of 250 days and ties every window to Google's weekly or monthly series, so the days stay on one scale. Takes a few more seconds per keyword; no extra charge. ## `compareOnOneScale` (type: `boolean`): Off: each keyword and location gets its own 0-100 scale, which shows the shape of its trend best. On: everything shares one 0-100 scale, so you can compare popularity. Google compares at most 5 terms at a time; the Actor has no such limit, and small keywords get decimals (0.37) instead of Google's 0 and "<1". ## `searchAsTopic` (type: `boolean`): Look up each keyword as a Google topic ("Coffee", the drink) instead of the exact search term. A topic counts searches in all languages and spellings and leaves out other meanings. ## `category` (type: `string`): Limit the data to searches in one category. For subcategories, use an explore link with cat=. ## `searchType` (type: `string`): Which Google search to measure. ## `includeInterestByRegion` (type: `boolean`): Add the interest of every region (states, countries or cities) to each record. ## `regionResolution` (type: `string`): Default: countries for worldwide, regions (states) for a country. Cities works everywhere Google has enough data; metro areas (DMA) only in the United States. ## `includeRelatedQueries` (type: `boolean`): Add the top and rising related queries to each record, with flags for queries that do not contain the keyword and for spam. ## `onlyNewRisingQueries` (type: `boolean`): For scheduled runs: save a keyword only when it has rising related queries that earlier runs of the same saved task did not see; they are listed in newRisingQueries. The first run saves every keyword and remembers its rising queries. Keywords without anything new are not saved and not charged. Turns on related queries. ## `exploreUrls` (type: `array`): Links copied from the Google Trends website, such as https://trends.google.com/trends/explore?date=today%205-y\&geo=US\&q=tesla,rivian. Each link is repeated exactly: its terms, places, dates, category and search type. ## `trendingLocations` (type: `array`): Countries or regions for the Trending now lists, such as US, GB or US-NY. Each trending search becomes one record with its search volume, growth, start time and related searches. ## `trendingHours` (type: `string`): Searches trending in the past 4 hours, 24 hours, 48 hours or 7 days. ## `trendingCategories` (type: `array`): Keep only trending searches in these categories. Leave empty for all. ## `trendingActiveOnly` (type: `boolean`): Keep only searches that are still trending. ## `maxTrendingPerLocation` (type: `integer`): Keep at most this many trending searches per location, in Google's order. 0 keeps all (often 200-500 for 24 hours). ## `proxyConfiguration` (type: `object`): Google Trends limits busy addresses. The Actor starts on Apify Proxy, opens a new session when Google limits one, and moves to residential addresses if limits continue. ## Actor input object example ```json { "keywords": [ "matcha", "cold brew" ], "locations": [ "US" ], "timeRange": "today 12-m", "dailyData": false, "compareOnOneScale": false, "searchAsTopic": false, "category": "0", "searchType": "web", "includeInterestByRegion": true, "regionResolution": "default", "includeRelatedQueries": true, "onlyNewRisingQueries": false, "trendingHours": "24", "trendingActiveOnly": false, "maxTrendingPerLocation": 0, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `insights` (type: `string`): One record per keyword and location: average, peak, latest value, change, trend, season, top region and rising query, with the full timeline, regions and related queries. ## `trending` (type: `string`): Trending searches with search volume, growth, start time, categories and related searches. ## `summary` (type: `string`): Records saved for every comparison and trending list, with errors and request statistics. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "matcha", "cold brew" ], "locations": [ "US" ], "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("robertosan16/google-trends-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "matcha", "cold brew", ], "locations": ["US"], "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("robertosan16/google-trends-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "matcha", "cold brew" ], "locations": [ "US" ], "proxyConfiguration": { "useApifyProxy": true } }' | apify call robertosan16/google-trends-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,robertosan16/google-trends-scraper" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/VTXIJvFaq6YQSEqsn/builds/yXG1TzijrUJNxO8N3/openapi.json