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Social Intelligence

YouTube Activity Signals

When a prospect delivers a keynote, reviews a product, or walks through a migration on YouTube, Autobound captures it: video metadata, engagement counts, and LLM-extracted pain points, initiatives, technologies, and competitors.

4M+

Contacts Searched

9

Signal Subtypes

Monthly

Refresh Cadence

1-5% of contacts

Coverage Rate

Social Intelligence9 subtypes · Monthly refresh

What Are YouTube Activity Signals?

YouTube activity signals surface when prospects post or appear in YouTube content: conference talks, product reviews, technical walkthroughs, and webinar recordings. Autobound searches YouTube across 4M+ contacts, validates matches against video descriptions and channel names, then analyzes each video with LLMs to extract pain points with intensity scores, initiatives with urgency scores, technologies mentioned with adoption status, and competitors referenced.

Coverage is deliberately narrow and deep: 1-5% of contacts have detectable YouTube activity, but matches skew toward keynote speakers, reviewers, and industry voices. Because videos run 30-60 minutes, a single signal often carries more evaluation detail (a migration walkthrough or a head-to-head tool comparison) than a month of LinkedIn posts. Refreshed monthly.

Example Signal Subtypes

youtubeVideo

Data Schema

YouTube Signal Schema

YouTube signals include video metadata, engagement metrics, channel information, and classification across 9 subtypes covering mentions, reviews, and engagement.

youtube_activity.schema.json
{
  "signal_id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
  "signal_type": "youtube-video-contact",
  "signal_subtype": "youtubeVideo",
  "signal_name": "Contact posted YouTube video",
  "association": "contact",
  "detected_at": "2026-06-22T15: 36: 11.235Z",
  "contact": {
    "email": "sarah.martinez@growthco.io",  // match on email
    "name": "Sarah Martinez",
    "first_name": "Sarah",
    "last_name": "Martinez",
    "job_title": "VP of Revenue Operations"
  },
  "company": {
    "name": "GrowthCo",
    "domain": "growthco.io",  // match on domain
    "description": "B2B SaaS platform for sales engagement",
    "industries": ["Software Development"],
    "employee_count_low": 51,
    "employee_count_high": 200
  },
  "data": {
    "videoLink": "https://www.youtube.com/watch?v=xR7qK3mPzL4",
    "channelTitle": "RevOps Unplugged",
    "publishedAt": "2026-06-18T10: 00: 00.000Z",
    "viewCount": "4,892",
    "commentCount": "127",
    "video_title": "Why We're Ripping Out Looker (and What We're Replacing It With)",
    "video_description": "After 2 years on Looker, our BI stack hit a wall. I walk through why Looker stopped working for our RevOps team, what we evaluated (Sigma Computing, ThoughtSpot, Hex), and why we chose Sigma.",
    "contact_youtube_channel_url": "https://www.youtube.com/@smartinez_revops",
    "tags": ["Business Intelligence", "Migration", "Revenue Operations"],
    "summary": "VP of RevOps explains migration from Looker to Sigma Computing after evaluating alternatives.",
    "pain_points": [
      { "topic": "BI stack unable to scale with growth", "intensity": 0.8 }
    ],
    "initiatives": [
      { "topic": "migrating BI stack from Looker to Sigma", "urgency": 0.9 }
    ],
    "technologies_mentioned": [
      { "name": "Looker", "status": "migrating_from" },
      { "name": "Sigma Computing", "status": "migrating_to" },
      { "name": "ThoughtSpot", "status": "evaluating" }
    ],
    "competitors_mentioned": []
  }
}
GCS Bucket
gs://autobound-youtube-v1/
Formats
JSONL · Parquet
Refresh
Monthly

Applications

What teams build with YouTube Activity Signals

04 documented applications

  1. 01

    Executive Thought Leadership Engagement

    When prospects deliver conference keynotes or appear in industry panels captured on YouTube, reference their specific talk in outreach for a deeply personalized conversation opener.

  2. 02

    Competitor Product Review Targeting

    Detect when prospects post or engage with YouTube reviews of competitor products. Someone reviewing your competitor's tool is actively evaluating solutions in your category.

  3. 03

    Industry Influencer Identification

    YouTube activity signals identify the most visible voices in your target market. High view counts and engagement rates indicate prospects with outsized influence on purchasing decisions.

  4. 04

    Content Co-Marketing Opportunities

    Find prospects who actively create video content about topics related to your product. These contacts may be interested in co-marketing partnerships, webinars, or case study collaborations.

Measured, Not Estimated

What's actually inside YouTube Activity Signals

Volumes, subtypes, geography, and join-key fill rates audited directly from our production database, so you can verify coverage before you buy.

Measured coverageaudited from production · minimums, not ceilings
120,000
companies with fresh data / month
basis: published baseline
192,966
records created / month
basis: 3-mo avg

Top subtypes

1 total
Youtube Video855K · 100%
🇺🇸United States22K · 41%
🇬🇧United Kingdom2.6K · 4.9%
🇮🇳India2.6K · 4.8%
🇨🇦Canada1.5K · 2.8%
🇩🇪Germany1.4K · 2.6%
🇦🇺Australia1.2K · 2.2%
🇫🇷France1.2K · 2.1%
CA 5.9KNY 3.8KTX 3.5KFL 2.4KIL 1.8KPA 1.5K

Top industries

all industries
Hospitals and Health Care3.0K · 5.6%
Higher Education1.4K · 2.6%
IT Services and IT Consulting1.4K · 2.5%
Retail1.3K · 2.4%
Financial Services1.3K · 2.4%
Building Construction1.2K · 2.2%
Software Development1.2K · 2.1%

Join keys

fill rate
Domain100%
LinkedIn URL0%
Company name100%
Records measured 854,567+Companies reached 54,322+Full schema & examples →

See the real records for yourself.

Real records from production, delivered to your inbox.

See full coverage & segmentation across all 35 signal types →

Worked Example

One signal, traced to outcome

One YouTube Activity Signals record followed from detection, through the action a rep took on it, to the measured result. Illustrative composite of observed customer workflows.

01 signal → 02 action → 03 outcome

01

Signal detected

Atlassian's Head of AI appears in a SaaStr keynote video titled 'Why Most Enterprise AI Projects Fail,' hitting 8,500 views and 120 comments in the first week.

02

Action taken

An MLOps platform sends a message:

Watched your SaaStr keynote on enterprise AI failure modes. Your point about data pipeline fragility is exactly what we solve. Would love to show you how we prevent the #1 cause of AI project failure.
03

Outcome

Meeting booked

Because the outreach engaged with a specific talk instead of name-dropping it. The prospect felt understood.

FAQ

Frequently Asked Questions

What are YouTube activity signals?
YouTube activity signals detect when prospects appear in, are mentioned in, or engage with YouTube videos. Autobound's 9 signal subtypes cover prospect appearances in videos, company and competitor mentions, product reviews, and comments on relevant content. This captures a content engagement layer that LinkedIn and Twitter signals miss entirely.
How does Autobound detect YouTube activity signals?
Autobound monitors YouTube on a monthly cadence, using AI to match videos to tracked contacts and companies through title analysis, transcript processing, and comment monitoring. Each signal includes the video URL, view count, engagement metrics, and the specific context (mention, review, discussion, or comment) with confidence scoring.
How should I use YouTube activity data in my outreach?
YouTube signals are most powerful when you reference specific content the prospect created or engaged with. Watching a prospect's keynote or product review and citing specific points they made demonstrates a level of genuine interest that generic outreach cannot match. This works especially well for thought-leader prospects who invest significant effort in their video content.

How It Works

From Raw Data to Your Stack

Autobound ingests from LinkedIn API, Glassdoor, GitHub, Reddit, G2, extracts structured signals with AI, and delivers them however your infrastructure needs.

01

Autobound Ingests

Raw data from LinkedIn API, Glassdoor, GitHub, Reddit, G2 is continuously collected and normalized across millions of sources.

02

AI Extracts & Scores

ML models extract 9 signal subtypes with relevance scoring, confidence levels, and entity resolution.

03

You Receive

Structured JSONL delivered via your preferred method, updated on a monthly cadence.

REST API

Real-time access with subtype filtering

300 req/min

GCS Push

Automated delivery to your bucket

JSONL + Parquet

Enrich API

On-demand LLM-ranked insights

AI relevance scoring

Flat File

Bulk exports for data warehouses

CSV, JSON, Parquet
3 vendors consolidated
By consolidating three data vendors into Autobound's Enrich API, we added 100+ new signal types and saved 4 months of engineering time.

AiSDR Team

Engineering, AiSDR

Ready to License YouTube Activity Signals?

Custom pricing based on signal types, delivery frequency, and volume. Full schema documentation and integration guides included.