The State of Mission Storytelling 2026

Nonprofits are told to make video. Very little published evidence describes what happens when they do.

Every nonprofit benchmark in the field is self-reported by organizations that chose to take part. M+R surveys 215 participating nonprofits on email, SMS, advertising, and web traffic. Nonprofit Tech for Good asks NGOs which platforms they use. Rival IQ samples 150 companies per industry across Facebook, Instagram, TikTok, and X. None of them observe YouTube channel performance, and none follow the same organizations over time.

This report does both. It draws on 2,988 US nonprofit, foundation, university, and healthcare YouTube channels, measured through the public YouTube Data API across 15 US metro areas and two national lists of large nonprofits and foundations. Seven of those channels were later found to be matched to the wrong organization and removed, taking the cohort to 2,981; the figures below were computed before that and do not move at this scale. For 2,752 of those channels we hold repeat observations across an average window of 111 days, which makes it possible to describe what changed rather than only what is. Collection is continuous and the panel window lengthens every month, so these findings will sharpen as the record grows longer.

The audience is already there. 84% of US adults use YouTube and 35% regularly get news there, second only to Facebook (Pew Research Center, 2025). What follows is what the sector does with that.

Six findings:

Between April and August 2026 we observed 2,752 nonprofit channels more than once, across an average window of 111 days.

Dormancy holds. Of the 1,200 channels already dormant when the window opened, 892 were still dormant when it closed — 74.3% of them. Another 255 channels that were publishing at the start had stopped by the end.

The cross-sectional figure agrees with the panel. 42.1% of the full cohort has published nothing in the trailing 90 days, and 43.6% of the panel was dormant at the opening observation. Two independent measurements landing within a point and a half of each other is the strongest evidence available that both are sound.

This is the finding that most needs a longitudinal dataset, and it is the reason this report exists. A single snapshot can tell you how many channels look inactive. Only repeat observation can tell you that three quarters of them stay that way.

Foundations have a median of 151 subscribers and 54.3% of their channels are dormant. Both figures are the weakest of any organization type in the cohort, and both sit below the operating nonprofits foundations fund.

Universities sit at the other end at 12.9% dormant. They also employ communications staff, which is the most obvious structural difference between the two groups.

The spread across mission categories runs from 74 to 5,330 median subscribers, a factor of 72. The spread across the 15 tracked metros runs from 108 to 1,930, a factor of 18.

Animal welfare organizations have 48 times the median audience of housing and community development organizations. Housing, social services, and workforce development sit at the bottom on reach and at the top on dormancy together.

This describes what audiences on YouTube reward. The causes sit outside this data.

Channels enter the cohort when the organization is a nonprofit, foundation, university, or healthcare organization and the sector is anything other than for-profit. The cohort holds 2,988 channels. Commercial channels are tracked separately and used only for comparison.

Statistics come from the public YouTube Data API: subscribers, total views, total videos, uploads in the trailing 90 days, average views per video, caption coverage, Spanish-language video counts, and an engagement rate derived from public views, likes, and comments.

Channel-level totals cover the whole library. The per-video figures do not. Average views per video, engagement rate, caption coverage, and Shorts share are computed across each channel's most recent uploads, up to fifty of them. For a large library that window is genuinely recent and can diverge sharply from the lifetime figure. For the 1,005 cohort channels holding fifty videos or fewer, a third of the total, the window covers the entire history instead, and a single old success can dominate it: their median top video accounts for 31.2% of all views the channel has ever received, against 3.0% for larger libraries. Read average views per video on a small channel as a career average rather than a current one. Where the question is what an organization is reaching people with now, the better figure is its best-performing video of the last 90 days.

Cross-sectional figures use one row per channel, its most recent snapshot, so long-tracked channels carry no extra weight. Panel figures compare each channel's earliest and latest complete observations and require at least 90 days between them.

Collection is continuous. A rotating daily job re-samples the cohort, so the panel window grows for as long as this runs. At 111 days it answers whether a channel published and whether it grew. A year of observation will reach seasonality and whether steady publishing compounds. Several years will reach the question we most want to answer, which is what changes for an organization that commits to a channel and stays committed. Every figure here is an early reading, and later editions will sharpen it.

Everything published is aggregate. No per-channel rows appear in this report or in the open extract, because the benchmark is built from public data about named organizations that never opted into a ranking.

The full collection method, refresh cadence, and cohort definition are documented on the benchmark methodology page.