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← Work/YouTube Talent Vault

YouTube Talent Vault.

From manual requests to a self-serve creator database used across every YouTube office.

Role
Research · Product Management · Design
Year
2017
Stack
Internal Data Tools · Crowdsourcing Platform · Custom Dashboard
Status
ARCHIVE
Product DesignResearch & AnalysisInternal ToolsYouTube
jeremys-five-star-site-def3a0.webflow.io/portfolio/talent-discovery-tools
The problem

YouTube employees couldn't find the creators they needed.

Across YouTube, employees regularly needed to identify creators for brand deals, events, product feedback, and original programming. Most only knew the platform's biggest names. Finding niche or emerging talent required raw data access and specialized knowledge that most teams didn't have — so they came to us, one request at a time.

[ Hero screenshot — workflow in motion ]
The solution

A curated, searchable database that scales the service.

We established a tag taxonomy across three dimensions — talent type, format, and topic — derived from the hundreds of requests we'd fulfilled. All previously curated channels were added to a central database, tagged via a crowdsourcing platform, and surfaced through a front-end dashboard with daily-refreshed channel data and multi-tag filtering.

01

Structured taxonomy

Three-axis tagging (talent, format, topic) built from real request patterns — not guesswork.

02

Crowdsourced at scale

Used a data crowdsourcing platform to tag thousands of channels against the taxonomy without a large internal team.

03

Live data integration

Dashboard pulled fresh subscriber, view, and upload data daily so searches always reflected current channel state.

[ Detail · before/after ]
[ Detail · close-up ]
[ Wide screenshot ]
Users reached
100s
across all global offices
Growth
10x+
from dozens to hundreds of users
Impact
Platform-wide
brand deals, events, product, originals
◉ Process

How it came together

  1. 01

    Identified the bottleneck

    Tracked incoming talent requests and realized we couldn't keep up with demand — the manual service needed to scale.

  2. 02

    Designed the taxonomy

    Analyzed hundreds of past requests to define a three-axis tag system covering talent type, content format, and topic niche.

  3. 03

    Crowdsourced the data

    Used a data crowdsourcing platform to apply tags to our existing channel library and batch-add new ones at speed.

  4. 04

    Shipped the dashboard

    Built a self-serve front-end with multi-tag search and quantitative filters, with channel data refreshed daily from internal APIs.

◉ Outcome

Manual requests dropped sharply; the platform became the go-to tool for creator discovery across YouTube's global teams — and the project marked a turning point in my career from research into product management.

Visit live site
◉ Next project
YCC · 2016

YouTube Creator Charts

Billboard-style creator rankings that reached every YouTube employee in six countries.