Deep on every channel that matters.
ThoughtLeaders has spent eight years building the only complete record of who advertises on YouTube and what actually worked. Competitors can guess at these numbers from public scrapes. Only we have measured them, classified them, and connected them across every real outcome since 2018.
- Transcripts, indexed and searchable, enriched with brand mentions: sponsored and organic, each with the snippet and the timestamp, so you can watch the read.
- View snapshots over time for every video we track, taken in advance, so the curve is there when you need it, not from the day you started looking.
- Sponsorship history per channel: who sponsored, when, and whether they came back.
- Audience demographics, pricing benchmarks, similar channels.
Enough coverage for anyone doing sponsorships. The channels we skip are the ones you could not sponsor anyway, and we add the ones that matter every week.
The numbers, live from our database.
Measured in production on 2026-09-02.
- sponsorship placements detected
- 15.9M sponsorship placements detected
- videos indexed
- 687M videos indexed
- YouTube channels tracked
- 1.3M YouTube channels tracked
- brand profiles
- 67,703 brand profiles
- video time-series snapshots
- 8.5B video time-series snapshots
- channel time-series snapshots
- 1.27B channel time-series snapshots
Measured in production, September 2026.
The Brand Extractor.
We process every brand mention in every video we track, across transcripts, descriptions and on-screen content, and classify each one as sponsored or organic. This is the engine behind every agent query and the most defensible thing we own.
Why sponsored vs. organic matters.
Most data providers can tell you that a brand was mentioned. We can tell you whether they paid to be mentioned. That one bit of metadata is the difference between a database and a marketplace. It powers every repeat-sponsorship calculation, every category analysis, every pricing benchmark your agent gives you.
Why repeat sponsorships are the real signal.
Click-through rates lie. Vanity metrics lie. Impression counts lie. Repeat purchases don't. When a brand comes back to the same channel for a second deal, it's the most honest success signal in the industry — they paid, they waited, they measured, and they decided to do it again.
Which VPN brands actually keep coming back to the same channels?
used tl brands --category vpn --window 12m --md
Two similar brands, opposite retention. Surfshark is running the strongest program in the category, 43 repeat deals across 15 channels. NordVPN has 9 deals across 9 channels and zero repeats, every deal a one-shot.
| Brand | Channels | Deals | Repeat |
|---|---|---|---|
| Northgate VPN | 15 | 58 | 43 |
| ClearRoute VPN | 9 | 9 | 0 |
| Proton-style VPN | 1 | 5 | 4 |
67,703 brand profiles.
Our brands table tracks every brand we've observed advertising on YouTube, with their complete marketing strategy rolled up across every tracked channel. Every sponsorship. Every organic mention. Every repeat.
Give me the full sponsorship history for this personal-care brand.
used tl brands "Acme Grooming" --md
55 sponsorships over 5 years, 30 unique channels, a 45.5% repeat rate: strong retention.
| Metric | Value |
|---|---|
| Total sponsorships | 55 |
| Unique channels | 30 |
| Repeat rate | 45.5% |
| First deal | 2020-10-28 |
| Most recent | 2025-08-19 |
Almost half of this brand's relationships have gone to a second or third deal.
Three data sources. One agent.
Postgres
Deals, brands, channels, pipeline state, users. Every write lands here first.
Elasticsearch
Video transcripts, Brand Extractor output, current channel and video metrics, demographics.
Firebolt
8.5B video snapshots and 1.27B channel snapshots. View curves, growth trajectories, evergreen calculations.
Your agent abstracts all three. It doesn't need to know which store a field lives in, it just asks. See the schema for how the tables and fields map.