Wikipedia Pageview Trends: Google Trends Alternative

Google Trends only gives you a score out of 100, and scraping it tends to get you blocked. Wikipedia views are a good stand-in for how much people care about something, and you get the actual numbers.

Put in some topics (titles, links or just search terms) and you get the views month by month or day by day, whether it's going up or down, and when it peaked. Works in any Wikipedia language.

What it does

• Finds the right article from a title, a link or a plain search term, following redirects
• Monthly or daily view counts with total, average, peak and a rising / steady / falling trend
• Fills in periods with no views, so every series is complete
• Topics it can't find, or that are ambiguous, get a clear error row and aren't charged
• Only counts complete months, so the latest figure isn't a half-month
• Adds views from redirects, so renamed articles keep their full history

Use cases

• Checking a topic is actually growing before you write about it or build for it.
• Comparing interest in rival products, brands or tech.
• Following a launch, an event or a news story day by day.
• Spotting seasonal patterns for content and campaigns.
• Real numbers to back up a pitch or a report.

How to use

1. Add topics: a title (Electric bike), a link (https://en.wikipedia.org/wiki/E-bike) or just a search term.
2. Pick monthly or daily, and how far back.
3. Hit Start. Each topic takes about a second.

You can also call it from the Apify API, run it on a schedule, or hook it up to Make, Zapier or n8n. AI agents can use it through Apify's MCP server.

Input

{
  "topics": [
    "ChatGPT",
    "Electric bike",
    "Taylor Swift"
  ],
  "period": 24
}

Output

You get one row per result, with these fields: topic, article, language, url, redirectedFrom, redirectsIncluded, granularity, start, end, totalViews, averageViews, latestViews, trendPct, trend, peakDate, peakViews, series, error.

Here's a real result:

{
  "topic": "Electric bike",
  "article": "E-bike",
  "language": "en",
  "url": "https://en.wikipedia.org/wiki/E-bike",
  "redirectedFrom": "Electric bike",
  "redirectsIncluded": 18,
  "granularity": "monthly",
  "start": "2024-10",
  "end": "2026-09",
  "totalViews": 223230,
  "averageViews": 9301,
  "latestViews": 9604,
  "trendPct": -0.2,
  "trend": "steady",
  "peakDate": "2025-03",
  "peakViews": 22253,
  "series": [
    {
      "date": "2026-06",
      "views": 8001
    },
    {
      "date": "2026-07",
      "views": 8122
    },
    {
      "date": "2026-08",
      "views": 7657
    },
    {
      "date": "2026-09",
      "views": 9604
    }
  ],
  "error": null
}

Pricing

$0.003 per topic analysed. You only pay for results that work. Anything that fails comes back with an error and is free. You can set a max spend per run in the run options.

So 100 topics cost about $0.30, and 1,000 about $3.00.

FAQ

Is it the same as Google Trends?

No, it's Wikipedia views rather than Google searches, but they tend to move together. The difference is you get real numbers and it doesn't get blocked.

What does 'trend' mean?

The last 3 months against the 3 before (or the last 30 days against the 30 before for daily). More than 15% up is rising, more than 15% down is falling.

Why does it say a page is a disambiguation page?

Some words mean a few things (Mercury). Use the full title, like Mercury (planet), or paste the link.

Why add views from redirects?

When Wikipedia renames an article, the old views stay under the old name. Adding them keeps the history in one piece. You can turn it off.

Where's the data from?

The Wikimedia pageviews API. It's free to reuse.

Limitations

• Views through up to 20 redirects get added in. Articles with loads of redirects might be slightly undercounted.
• Monthly data only goes back to July 2015.
• Wikipedia views show curiosity, not buying intent, so use it as one signal among a few.

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Support

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