Go-To-Market Intelligence Case Study

Stop Guessing. Start Integrating.

An innovative developer of AI operating systems for medical practices was struggling with low response rates to their cold outreach. Practice owners have one immediate gatekeeping question: "Does this integrate with our current EHR?" Guessing wrong meant an instant rejection. See how they fixed their pitch.

Discover Your Target's Tech Stack ➔

The "One-Size-Fits-All" Trap

Outbound sales fails when it lacks context. If you pitch a seamless AI integration to a clinic without knowing what system they use, your message sounds generic and risky.

The U.S. hospital and practice landscape is heavily fragmented. If you blindly guess they use Epic, you are wrong more than 50% of the time.

U.S. EHR Market Share Snapshot

Epic Systems
43.9%
Oracle Cerner
18.9%
MEDITECH
10.7%
TruBridge
4.3%
WellSky
3.4%

The Intelligence Pivot: Tailored Outreach

The client leveraged Intent.Health's ecosystem mapping to identify the exact EHR running inside their target practices before sending a single email or making a call.

1. Identify Practice

Target list of priority ambulatory & specialty clinics ingested.

2. Map Technology

Intent.Health platform identifies the installed EHR (e.g., Epic, Cerner).

3. Tailored Pitch

"Our AI agent integrates natively with your [Insert EHR] instance."

500,000+

Outpatient Sites Mapped & Indexed by Intent.Health

The Outcome

By knowing the practice's tech stack beforehand, the client transformed their generic AI pitch into a highly relevant, deeply welcomed operational solution.

Warmer Reception

Practice owners instantly trusted the vendor, knowing the solution wouldn't require a painful platform migration.

Higher Conversions

Emails explicitly mentioning the practice's actual EHR system saw significantly higher open and reply rates.

Faster Sales Cycle

Bypassed the initial "discovery" phase of figuring out IT compatibility, moving straight to value presentation.

Zero Wasted Spend

Marketing budgets were safely reallocated away from clinics running legacy systems the AI couldn't support.