📺 Youtube Most Replayed Scraper

📺 Youtube Most Replayed Scraper

📺 Youtube Most Replayed Scraper is a focused extraction tool that collects YouTube’s “Most Replayed” segments and heatmap popularity data from video watch pages, along with essential metadata like title, channel, views, likes, comments, and dates. It solves the problem of manually guessing highlights by turning the progress bar heatmap into structured insights — a YouTube most replayed data scraper and YouTube popularity graph scraper built for creators, marketers, developers, and researchers. At scale, it helps you automate YouTube key moments extraction and build datasets for engagement analysis and benchmarking.

What data / output can you get?

Below are the exact fields this actor streams to the Apify dataset during a run. Field names match the dataset schema and code that calls Actor.pushData.

Data type	Description	Example value
videoId	Unique YouTube video identifier	dQw4w9WgXcQ
title	Video title	Rick Astley - Never Gonna Give You Up (Official Video) (4K Remaster)
channelOwner	Channel / author name	Rick Astley
viewCount	View count (string as returned by YouTube)	1694624700
likes	Like count (string; if available)	18549049
comments	Comment count (string; if available)	2.4M
dateText	Published date (simple text)	Oct 24, 2009
relativeDate	Relative publish time	15 years ago
mostReplayed	Array of replay decorations with time ranges	[{"visibleTimeRangeStartMillis": 30000, "visibleTimeRangeEndMillis": 60000, "decorationTimeMillis": 45000}]
heatSeek	Heatmap intensity segments (start, duration, normalized score)	[{"startMillis": 120000, "durationMillis": 5000, "intensityScoreNormalized": 0.87}]
error	Error message for failed URLs (only present on failures)	HTTP 429: Too Many Requests

Notes:

• mostReplayed and heatSeek arrays capture the YouTube progress bar heatmap data, enabling a YouTube engagement heatmap extractor workflow and YouTube peak timestamps scraper use cases.
• Download the dataset in JSON, CSV, or Excel from Apify. The actor also writes a full results array to Key-Value Store at most_replayed.json and a summary to OUTPUT.

Key features

• 🔥 Most replayed & heatmap extraction
  Captures both mostReplayed decorations and heatSeek intensity points to power a YouTube heatmap popularity scraper and YouTube most replayed highlights finder workflow.

• 🛡️ Automatic residential proxy fallback
  Starts direct by default and, if blocked, seamlessly switches to Apify Residential proxy and stays there for resilient scraping — a reliable YouTube most replayed API alternative.

• 📦 Live streaming to dataset
  Pushes each video’s result as it’s processed, so you can start analyzing YouTube progress bar heatmap data immediately.

• 🧰 Requests-based, lightweight scraper
  Fetches YouTube watch pages and parses embedded JSON (ytInitialData and ytInitialPlayerResponse) for speed and stability — a fast alternative to heavy browser automation.

• 📈 Batch URL support
  Paste multiple watch URLs and process them in one run — ideal to scrape YouTube most replayed segments across videos and compare highlights.

• 👨‍💻 Developer-friendly JSON
  Structured arrays (mostReplayed, heatSeek) with millisecond timestamps and intensityScoreNormalized values make it easy to integrate into analysis pipelines.

• 🔗 Workflow-ready on Apify
  Export to JSON/CSV/Excel, chain with other actors, or call via the Apify API for “automate YouTube most replayed extraction” pipelines.

How to use 📺 Youtube Most Replayed Scraper - step by step

1. Create or log in to your Apify account.
2. Open the “📺 Youtube Most Replayed Scraper” actor in the Apify Store.
3. Add input URLs: paste one or more YouTube watch-page URLs (https://www.youtube.com/watch?v=...).
4. (Optional) Configure Proxy: leave it empty to start direct; the actor auto-falls back to Residential if blocked, or customize the proxy object.
5. Start the run: the actor fetches each URL, parses most-replayed segments and heatmap data, and streams results to the dataset.
6. Monitor progress: each processed URL is logged; errors (if any) are stored with an error message.
7. Download results: export the dataset as JSON, CSV, or Excel from the run’s Dataset tab.
8. Check Key-Value Store: find most_replayed.json (full results array) and OUTPUT (summary with totals and proxy fallback flag).

Pro Tip: Chain this with your analytics scripts or dashboards to build a YouTube watch heatmap JSON parser pipeline and compare engagement peaks across channels.

Use cases

Use case name	Description
Content creators – Highlight detection	Identify replay spikes and repurpose them into Shorts/reels to boost engagement.
Marketers – Competitor hooks	Compare replay hotspots to learn which intros, hooks, or CTAs perform best.
Data analysts – Peak segment analysis	Aggregate heatSeek intensity scores across videos for trend detection and A/B testing.
Researchers – Audience behavior	Study viewer attention curves and key-moment dynamics using normalized heatmap data.
Editors – Efficient trimming	Jump straight to the most replayed timestamps to accelerate highlight reel production.
API pipeline – Automated extraction	Feed structured outputs (mostReplayed, heatSeek) into your ETL stack for scoring and alerts.
Product teams – UX studies	Quantify which tutorial steps or demos users rewatch most to inform content design.

Why choose 📺 Youtube Most Replayed Scraper?

• 🎯 Precision heatmap focus: Purpose-built for Most Replayed data — not a generic scraper trying to do everything.
• 🔁 Resilient by design: Automatic fallback to Apify Residential proxy when blocked, reducing failed runs.
• 📊 Structured outputs: Clean JSON fields (mostReplayed, heatSeek) with millisecond timestamps and normalized intensity for analysis.
• 🚀 Scales to batches: Paste multiple URLs to build datasets quickly across playlists or competitor sets.
• 🧪 Developer-friendly: Works seamlessly with Apify’s dataset and API for downstream automation.
• 🔒 No login required: Extracts public watch-page data without cookies or authentication.
• 💸 Cost-effective: Pay for what you run on Apify infrastructure — more reliable than unstable extensions or ad‑hoc scripts.

In short, this is a production-ready YouTube most replayed highlights finder — a robust scraper vs fragile browser extensions.

Is it legal / ethical to use 📺 Youtube Most Replayed Scraper?

Yes — when done responsibly. This actor processes publicly available YouTube watch pages and extracts Most Replayed/heatmap data plus video-level metadata.

Guidelines:

• Only target public content and avoid private or gated data.
• Do not collect personal or sensitive information.
• Respect platform terms and applicable laws (e.g., GDPR, CCPA).
• Use results for analytics and research, not spam or misuse.

If you have edge cases or special compliance requirements, consult your legal team.

Input parameters & output format

Example JSON input

{
  "urls": [
    "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
  ],
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Parameters

• urls (array of strings)
  Description: Paste one or more YouTube watch URLs. One per line. At least one URL is required.
  Default: ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"]
  Required: Yes

• proxy (object)
  Description: Proxy (optional). Proxy is off by default. If the site blocks the request, the actor turns on Apify Residential proxy and stays on it. Configure here to customize.
  Default: {}
  Required: No

Example JSON output

Successful items include video metadata and both arrays; failed items include an error message with empty arrays and blank strings for metadata.

[
  {
    "channelOwner": "Rick Astley",
    "title": "Rick Astley - Never Gonna Give You Up (Official Video) (4K Remaster)",
    "videoId": "dQw4w9WgXcQ",
    "viewCount": "1694624700",
    "likes": "18549049",
    "comments": "2.4M",
    "dateText": "Oct 24, 2009",
    "relativeDate": "15 years ago",
    "mostReplayed": [
      {
        "visibleTimeRangeStartMillis": 30000,
        "visibleTimeRangeEndMillis": 60000,
        "decorationTimeMillis": 45000
      }
    ],
    "heatSeek": [
      {
        "startMillis": 120000,
        "durationMillis": 5000,
        "intensityScoreNormalized": 0.87
      }
    ]
  },
  {
    "channelOwner": "",
    "title": "",
    "videoId": "",
    "viewCount": "",
    "likes": "",
    "comments": "",
    "dateText": "",
    "relativeDate": "",
    "mostReplayed": [],
    "heatSeek": [],
    "error": "HTTP 429: Too Many Requests"
  ]
]

Also written to the Key-Value Store:

• most_replayed.json: Full array of results.
• OUTPUT: Summary object with total, succeeded, failed, residentialFallbackUsed, timestamp.

FAQ

Do I need to log in or provide cookies to use this scraper?

No. The actor extracts data from public YouTube watch pages without login or cookies. It fetches each URL with standard HTTP requests and parses embedded JSON.

Which fields are included in the output?

The dataset includes videoId, title, channelOwner, viewCount, likes, comments, dateText, relativeDate, mostReplayed, heatSeek, and an error field on failures. Arrays hold replay segments and heatmap intensity points in milliseconds.

What if YouTube blocks my requests?

The scraper starts direct by default. If requests are blocked or rejected, it automatically falls back to the Apify Residential proxy and stays on it for the remainder of the run.

Will every video have Most Replayed and heatmap data?

Not necessarily. YouTube only shows the Most Replayed graph for videos with sufficient engagement. For videos without a heatmap, mostReplayed and heatSeek arrays will be empty.

Can I process multiple videos in one run?

Yes. Add multiple watch URLs to the urls input array. The actor processes them sequentially and streams each result to the dataset — ideal to scrape YouTube most replayed segments across a batch.

In what formats can I export the results?

You can export the Apify dataset as JSON, CSV, or Excel directly from the platform. This makes it easy to plug into a YouTube watch heatmap JSON parser or analytics workflow.

Is this a replacement for a YouTube Most Replayed API?

It’s a practical YouTube most replayed API alternative. Instead of relying on an official endpoint, it extracts the same insights from public watch pages: replay segments and heatmap intensity.

Does this use Puppeteer or a headless browser?

No. It’s a lightweight, requests-based extractor that parses ytInitialData and ytInitialPlayerResponse from the page HTML — often faster and simpler than a Puppeteer YouTube most replayed scraper.

Final thoughts

📺 Youtube Most Replayed Scraper is built to turn YouTube’s progress bar heatmap into structured, analysis-ready data. With precise replay segment extraction, automatic proxy fallback, and batch URL support, it gives creators, marketers, analysts, and researchers a reliable way to find highlights and measure engagement. Developers can integrate the clean JSON (mostReplayed, heatSeek) into pipelines via Apify’s dataset and API. Start extracting smarter YouTube key moments and build scalable insights from replay behavior today.