Original research
The State of Mission Storytelling 2026
How US nonprofits actually perform on YouTube
Summary
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 across 18 metro areas, measured through the public YouTube Data API. 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.
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:
- In four months the median nonprofit channel published one video and gained eight subscribers. 38.6% published nothing at all.
- The fastest-growing 1% of channels captured 76% of all subscriber growth.
- Foundations have the smallest audiences and the highest dormancy of any organization type measured.
- Engagement rate, the metric most benchmark reports lead with, does not distinguish a channel reaching 167 people from one reaching 6,366.
- Reach varies more by mission than by city. Animal welfare organizations have 48 times the median audience of housing organizations.
- Twelve of 214 Miami nonprofits publish any Spanish-language video, in a county where 67% of residents speak Spanish at home.
Every relationship described here is an association. Nothing in this data establishes cause.
The findings
- 01Four months, one video, eight subscribers38.6% of nonprofit channels published nothing over a 111-day window.
- 02Audience growth went almost entirely to the topThe fastest-growing 1% of channels captured 76% of all new subscribers.
- 03Foundations rank last on reach and first on dormancyA median of 151 subscribers, below the operating nonprofits they fund.
- 04Engagement rate does not measure reachEngagement moves 1.6× across the cohort while views per video move 38×.
- 05Reach varies more by mission than by cityAnimal welfare organizations out-reach housing organizations by 48 times.
- 06Miami publishes less Spanish-language video than Denver12 of 214 Miami nonprofits publish in Spanish, in a 67% Spanish-speaking county.
Four months, one video, eight subscribers
Between April and August 2026 we observed 2,752 nonprofit channels more than once, across an average window of 111 days.
| Over the window | Result |
|---|---|
| Published nothing at all | 1,063 channels (38.6%) |
| Median new videos published | 1 |
| Median subscriber change | +8 |
| Ended with fewer videos than they started with | 76 channels |
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.
Audience growth went almost entirely to the top
| Share of channels | Share of new subscribers | Share of new videos |
|---|---|---|
| Top 1% | 76.0% | 28.1% |
| Top 5% | 92.7% | 53.4% |
| Top 10% | 96.5% | 69.3% |
Roughly thirty organizations account for three quarters of everything the cohort gained in audience over four months.
Publishing effort is distributed more evenly than audience growth. The top 1% of channels by output produced 28% of the new videos, while the top 1% by growth captured 76% of the new subscribers. Effort spreads across the sector. Attention collects at the top.
Foundations rank last on reach and first on dormancy
| Organization type | Channels | Median subscribers | Dormant | Median views per video |
|---|---|---|---|---|
| University | 210 | 2,800 | 12.9% | 786 |
| Healthcare | 199 | 1,120 | 36.7% | 701 |
| Nonprofit | 2,325 | 274 | 43.8% | 337 |
| Foundation | 254 | 151 | 54.3% | 288 |
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.
Engagement rate does not measure reach
| Subscribers | Channels | Median engagement rate | Median views per video |
|---|---|---|---|
| Under 100 | 899 | 1.21% | 167 |
| 100–1K | 1,065 | 1.16% | 342 |
| 1K–10K | 665 | 1.21% | 713 |
| 10K–100K | 272 | 1.24% | 1,746 |
| 100K+ | 87 | 1.96% | 6,366 |
Across a thousandfold range of channel size, median engagement rate moves by a factor of 1.6. Median views per video moves by a factor of 38.
Engagement rate is a ratio of interactions to followers, so it holds roughly steady as a channel grows. That is what makes it comparable across industries, and it is also what makes it silent on the question a communications director is actually asking. A team comparing its engagement rate to a published industry average learns almost nothing about whether its work reached anyone. Median views per video carries that information.
Any nonprofit benchmarking its social performance should report reach alongside engagement. Most published benchmarks report engagement alone.
Reach varies more by mission than by city
| Mission category | Channels | Median subscribers | Dormant | Median views per video |
|---|---|---|---|---|
| Science & Research | 246 | 5,295 | 22.4% | 546 |
| Animal Welfare | 55 | 3,500 | 30.9% | 1,060 |
| Arts & Culture | 397 | 1,930 | 34.5% | 816 |
| International Development | 120 | 1,155 | 33.3% | 410 |
| Environment & Conservation | 194 | 553 | 39.7% | 447 |
| Health & Wellness | 575 | 459 | 37.7% | 402 |
| Education & Youth | 1,251 | 358 | 41.2% | 380 |
| Civil Rights & Advocacy | 468 | 292 | 41.0% | 324 |
| Workforce & Economic Development | 252 | 152 | 45.6% | 199 |
| Social Services | 748 | 112 | 52.9% | 207 |
| Housing & Community Development | 234 | 73 | 53.8% | 176 |
The spread across mission categories runs from 73 to 5,295 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.
Miami publishes less Spanish-language video than Denver
| Metro | Nonprofits | Publish any Spanish-language video | Share |
|---|---|---|---|
| Denver | 216 | 20 | 9.3% |
| Houston | 135 | 11 | 8.1% |
| San Francisco | 186 | 14 | 7.5% |
| Los Angeles | 218 | 15 | 6.9% |
| Miami | 214 | 12 | 5.6% |
| Chicago | 233 | 11 | 4.7% |
| New York City | 255 | 12 | 4.7% |
| Dallas | 133 | 5 | 3.8% |
About 67% of Miami-Dade County residents aged five and over speak Spanish at home. Twelve of the 214 Miami nonprofits in this cohort publish any Spanish-language video, and across all 214 organizations the cohort holds 90 Spanish-language videos in total.
Nationally the figure is 5.0%. Language coverage tracks neither the size of the Spanish-speaking population nor the missions most likely to serve it: social services sits at 6.3% and housing at 6.8%.
What we checked and left out
A benchmark is only as good as the numbers it declines to print.
The nonprofit-versus-business comparison
Comparing the nonprofit cohort to the full commercial comparison set produces a 57-fold subscriber gap. That set is weighted toward large brands, including a segment with a median of 3.13 million subscribers. The defensible comparison is against local service businesses: median 6,970 subscribers against 345 for nonprofits, a 20-fold gap. A neighbourhood business out-reaches a neighbourhood charity by roughly twenty to one.Shorts
Channels whose libraries are mostly Shorts have a median of 23 subscribers, against 1,170 for channels where Shorts are a small minority. That 51-fold gap is largely an artefact: a channel with ten videos, eight of them Shorts, has a high Shorts share by construction and is small for unrelated reasons. Controlling for library size collapses it. What survives is smaller and steadier — within a library-size band, views per video rise with Shorts share while subscriber counts do not follow.Budget against reach
The most useful cut available would test whether organizational budget predicts audience. Employer identification numbers are present for 17% of the cohort, which is too sparse to support it. This is the first gap we intend to close.Method
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.
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.
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.
Limits
Curated cohort, not a census
Organizations absent from the compiled list are absent from the figures.Metro is the organization's headquarters
Nationally-scoped organizations headquartered in Washington DC or New York lift those metros' figures.Associations, not causes
This applies to every finding, and most strongly to publishing cadence.Dormancy is measured over 90 days
Organizations that publish around a single annual event can read as dormant in an off month.Survivorship
A channel created and then deleted does not appear in a list compiled in 2026. Real abandonment is higher than what is measured here.Public counts only
Engagement has no access to watch time or retention.Figures reflect what YouTube reported on August 6, 2026. Any citation should carry that date. Current figures move with the daily pull and live on the benchmark.
Use it, and cite it
The underlying aggregate extract is published openly under Creative Commons Attribution 4.0 International. Use it in reporting, in a grant application, or in a board deck. Attribution is the only condition.
How to cite
The State of Mission Storytelling 2026, RiseWorks Media, PBC — https://www.storyos.org/reports/state-of-mission-storytelling. Snapshot August 6, 2026.
The underlying data
Metro aggregates (CSV) — one row per metro with channel counts, median subscribers, active share, and average engagement.
Full aggregate extract (JSON) — national activity bands, engagement by channel size, caption coverage, sector comparison, and mission-category breakdowns.
Working on a story that needs a cut of the data this extract does not cover? Ask us.