Youtubers Database - Fast AI-Curated Creator Matches
Worried the “right” creator will hide in noise? Our AI filters semantic relevance, flags fraud, benchmarks engagement and audits audience reachability so matches are verifiable — not guesswork. Explore two proven Youtuber picks now and start a 7-day trial to export contact-ready reports.
We selected two high-fit creators from our youtubers database using semantic AI, audience audits, engagement benchmarks and fraud detection - ready to contact.
How recent is the data for YouTuber metrics and audience snapshots?
Metrics and audience snapshots refresh on a rolling last-30-days window - profile stats and snapshots update in seconds when you paste a handle, giving normalized ER%, views and cadence for fair cross-platform comparison.
Can I export contact details and reports after the 7-day trial?
Yes. Exports (profile analysis PDFs/JSON, saved lists CSV, Media Plan Google Sheets, campaign CSV/Excel) become available after signup/sign-in. If you start the 7-day trial you can export contact-ready reports and saved lists during the trial period.
How does IQFluence normalize ER, views and cadence across platforms?
We convert raw cross-platform signals into comparable metrics by using last-30-day averages and posting cadence context - ER% uses likes+comments relative to followers over 30 days; views are summarized as min/avg/max from recent-post distributions; cadence is posts/month. That standardization yields fair apples-to-apples comparisons.
Does IQFluence show audience language and city breakdowns per creator?
Yes. Every creator profile includes audience language and city breakdowns - shown in the one-view profile sheet alongside gender, age buckets and top countries. These audience slices are part of the rolling 30-day snapshot used for verification and side-by-side comparisons.
Can I build a shared media plan sheet from shortlisted creators?
Yes — you can shortlist creators in Discovery and produce a shared Media Plan as a live Google Sheet. The sheet lists apples-to-apples rows (followers, L30D ER%, min/avg/max views, posts/mo, audience gender/age/countries) plus outreach fields ready for approvals and collaboration after signup.
How do you detect and flag fraudulent audience behavior?
We combine behavioral and audience signals from the rolling L30D feed - sudden follower surges, abnormal ER distributions, view-to-follower mismatches, repeat comment patterns and geographic/language inconsistencies. Semantic and engagement benchmarks flag outliers; flagged creators get audit notes in the one-view profile for reviewer verification.