Most healthcare organizations have more data available to them than ever before:
demographics, claims history, enrollment records, awareness metrics. And yet a familiar
problem keeps showing up in clinical trial recruitment: two sites, two communities, or two
regions can look nearly identical on paper and still produce completely different results.
When that happens, the answer usually isn't in the data teams already have. It's something
most organizations have never had a consistent way to track: whether a community actually
trusts the organization running the trial, what's standing in the way of participation, and whether
people are genuinely ready to act or simply aware that an opportunity exists. That layer is what
we call community intelligence.
Community intelligence is the continuous understanding of the trust, beliefs, barriers,
needs, readiness, and behaviors that shape how communities engage with health
opportunities, including clinical trial participation.
It's not a replacement for the data organizations already rely on. It's the layer most of them are
missing.
● Demographic data tells you who people are.
● Claims and real-world data tell you what already happened.
● Market research tells you what people say when asked directly, at a single point in time.
● Social listening tells you what people are willing to say publicly.
None of those sources can tell you whether someone trusts a site enough to show up, what's
quietly standing in their way, or whether they're actually ready to participate. Community
intelligence is built specifically to answer that.
A recruitment plan can be well-designed and still underperform, not because the strategy is
wrong, but because it's built on data that was never able to capture certain barriers in the first
place. This is especially visible in clinical research patient recruitment, where trust and logistics
often matter as much as awareness or interest.
Consider a Phase 3 trial running in Dallas and Chicago at the same time. Both metros show
similar demographics and similar awareness of the trial. Enrollment tells a different story: 60% in
Dallas, 20% in Chicago. The data available to most teams can't explain that gap.
Community intelligence can. In this case, the real barrier in Chicago isn't awareness, it's
transportation. Community members in the ZIP codes closest to the site rely on public transit,
and the nearest routes require two transfers and add up to 90 minutes each way for a single
visit. In Dallas, most participants live within a 15-minute drive of the site, and the site has
already arranged rideshare vouchers for those who don't.
Once that barrier is visible, the fix is specific and immediate: transportation stipends and a
shuttle partnership in a handful of ZIP codes, rather than another awareness campaign spread
across the whole metro.
Approach |
What it's strong at |
What it misses |
| Claims / real-world data | Historical behavior for people already visible in the system |
People not yet in the system, and the reasons behind their behavior |
| Market research, panels | Stated opinions, captured at a single point in time |
Whether those opinions hold up once someone actually has to act |
| Social listening | What people are discussing publicly |
Everything people don't say publicly, which is most of it |
| Community/patient advisory boards | Depth and authenticity | Scale, and a way to track it continuously over time |
Community intelligence doesn't replace any of these. It's the layer that connects them to an
actual decision.
There's a meaningful difference between a platform that reports what happened and one that
directs what to do next. A lot of what gets labeled "community insight" today stops at the first
part.
The more useful version of community intelligence functions as a leading indicator, not a lagging
one. Rather than confirming after the fact that enrollment stalled, it's built to surface a barrier
early enough that a team can still act on it: adjusting outreach, addressing a trust gap, or fixing a
logistics problem before a trial timeline is already at risk. That's the real test of whether an
organization has a community intelligence practice or just another dashboard: does the insight
arrive in time to change what happens next?
FDA Diversity Action Plan requirements and broader health equity commitments have made this
gap harder to overlook. Sponsors and CROs are increasingly expected to explain not just who
enrolled in a trial, but why certain communities didn't, and what was done in response. "The
data didn't show it" is a much weaker answer than it used to be.
Community intelligence exists to close that gap: an ongoing understanding of trust, barriers,
needs, readiness, and behavior, tracked closely enough to be useful before enrollment falls
behind, not just explained afterward.
AVA, Acclinate's community intelligence platform, is built around exactly this layer. It's designed
to answer the questions most profile data can't: where opportunity exists, why engagement isn't
turning into action, what barriers stand in the way, where intervention is needed, and what to do
next. That intelligence connects directly to NOWINCLUDED, Acclinate's community activation
platform, so the loop runs from understanding to action and back again.
Curious what AVA would surface for your next trial? Request a demo →
What is community intelligence? Community intelligence is the continuous understanding of
the trust, beliefs, barriers, needs, readiness, and behaviors that shape how communities
engage with health opportunities, including clinical trial participation. It complements
demographic, claims, and social-listening data rather than replacing it.
How is community intelligence different from market research? Market research typically
captures stated opinions at a single point in time. Community intelligence is gathered
continuously, through sustained relationships, so it reflects how trust and readiness actually
change over time.
Why does community intelligence matter for clinical trial diversity? It surfaces the specific
barriers, such as trust, access, or logistics, that keep certain communities from enrolling in
clinical trials, early enough for a team to address them before enrollment timelines are affected.
Is community intelligence the same as social listening? No. Social listening tracks what
people say publicly. Community intelligence includes barriers, needs, and readiness that people
don't necessarily post about, gathered through direct, sustained community engagement.