Survival Youtubers For Authentic Outdoor Campaigns
We analyzed channels, content and audiences to surface 13 verified survival YouTubers you can hire fast - solving hours of manual vetting. Each creator is hand-picked with semantic relevance, engagement, fraud filters and audience snapshots so you can launch authentic outdoor campaigns with confidence.
How recent are the audience and engagement metrics for these YouTubers?
We refresh key audience and engagement figures on a rolling last-30-days basis - paste a channel and its profile stats refresh in seconds so you see normalized ER%, views and posting cadence based on the most recent 30-day window.
Can I export these YouTuber profiles and audience reports after signup?
Yes. After signing in you can export YouTuber profile analyses and audience reports — PDF and JSON for individual profiles, CSV for saved lists, and live Google Sheets for media plans. Exports require an account and are available from the profile and Media Plan Builder views.
How does IQFluence prevent fake views and follower fraud on these channels?
We detect and downweight suspicious signals across creators and audiences - abnormal view spikes, engagement patterns, bot-like follower growth and duplicate accounts. Metrics are normalized over the last 30 days, engagement consistency is compared to posting cadence, and fraud flags surface before shortlisting.
Can I compare these YouTubers side-by-side across platforms?
Yes — creators on Instagram, TikTok and YouTube are standardized so you can view apples-to-apples metrics in one grid. ER%, views and posting cadence are normalized across platforms, and profile sheets let you compare audience demographics, engagement and reach side-by-side.
Can I build a media plan with these YouTubers and export it?
Yes. Use the Media Plan Builder to add YouTube rows, edit outreach fields and notes, then export a live Google Sheet for approvals. Exports and profile PDFs/JSON/CSV are available after signing in. Note - IQFluence provides historical stats for your projections but does not auto-forecast outcomes.
How are YouTuber views and ER% normalized for fair cross-platform comparison?
YouTube views and ER% are normalized using the rolling last-30-days window: recent-post distributions produce min/avg/max view bands, ER% is computed as likes+comments relative to subscribers with posting cadence context, and consistency checks downweight spikes or anomalous activity for fair cross-platform comparisons.