How Evoco Used Signal-Based GTM to Break Into Automotive OEMs and Hospital Systems
See how Evoco used signal-based GTM to win meetings with automotive OEMs and hospital systems using buyer intent signals.
FAQ
What is signal-based GTM?
Signal-based GTM uses real-time market events and buyer intent indicators to identify when organisations are most likely to evaluate new solutions.
Why did signal-based GTM work for Evoco?
It allowed Evoco to engage buyers during innovation and transformation cycles instead of relying on untimed cold outreach.
What signals are useful for automotive OEM sales?
Vehicle platform announcements, leadership changes, CES commentary, and innovation partnerships are strong intent signals for OEM sales.
What healthcare signals indicate buying intent?
Patient experience initiatives, digital health expansion, leadership commentary, and hospital infrastructure projects are strong healthcare buying signals.
TLDR: Evoco used signal-based GTM to enter automotive OEMs and hospital systems by tracking intent signals like platform announcements, patient experience initiatives, and leadership changes.
4.1× increase in qualified meetings
1,600+ ICP accounts mapped
58% signal-to-meeting conversion on hot-trigger accounts
Multiple OEM pilots launched
Hospital proof-of-concepts launched within months
Most Startups Struggle to Sell Into One Enterprise Vertical
Evoco was trying to break into two enterprise verticals simultaneously: automotive OEMs and hospital systems.
Both markets were relationship-driven. Both had long procurement cycles. And both had deeply hidden buying committees.
But the bigger challenge was category definition.
Evoco had built an emotion-aware voice companion platform capable of detecting and adapting to human emotional states during conversations.
The technology was differentiated.
The problem was that most buyers didn't yet have a named budget category for it.
The Real Problem Wasn't Outreach - It Was Timing and Visibility
Evoco didn't need more cold emails.
They needed to identify:
Which organisations were entering innovation cycles
Which executives were already thinking about emotional AI
Which market events created natural entry points for a product like theirs
Because enterprise adoption doesn't happen randomly.
Instead of Prospecting Companies, They Started Tracking Intent Signals
getGTM.ai built a dual-vertical signal intelligence system operating across automotive OEMs and healthcare systems.
Each vertical had:
its own signal map
its own ICP model
its own buyer personas
its own trigger workflows
Vertical 1: Automotive OEMs
Selling into automotive OEMs requires entering conversations years before products reach vehicles.
The buying cycles are long. Technology decisions happen during platform architecture planning, not after launch.
Signal #1: Vehicle Platform Announcements
getGTM.ai monitored:
OEM investor communications
Automotive trade publications
EV platform announcements
Software-defined vehicle initiatives
HMI refresh cycles
Signal #2: Leadership Changes in Experience and Product Roles
The system tracked hiring and role changes for:
VP of HMI
Head of Connected Services
Chief Product Officer
In-Vehicle Experience leadership
Signal #3: CES and Auto Show Intent Signals
getGTM.ai monitored CES announcements, Munich IAA, Detroit Auto Show commentary, executive interviews, and OEM innovation narratives.
Signal #4: Innovation Partnership Activity
OEMs publicly partnering with AI companies, wellness platforms, voice technology vendors, and connected experience startups often signal openness to emerging technologies.
Vertical 2: Healthcare Systems
Signal #1: Patient Experience Initiatives
getGTM.ai monitored HCAHPS publications, CMS reporting, hospital press releases, patient experience investments, and care transformation initiatives.
Signal #2: Digital Health Expansion
Hospitals launching innovation labs, digital health partnerships, AI strategy teams, or hiring Chief Innovation Officers were more likely to evaluate emerging technologies.
Signal #3: Public Discussion Around Care Gaps
getGTM.ai monitored healthcare leadership commentary around patient loneliness, nurse overload, emotional care gaps, patient engagement challenges, and wellness technology adoption.
Signal #4: Hospital Expansion and Infrastructure Projects
The system tracked construction permits, hospital expansion announcements, capital programme investments, and facility growth initiatives.
The Outreach Was Built Around the Signal, Not Around the Product
Every message referenced:
The exact platform announcement
The exact patient experience initiative
The exact leadership change
The exact operational challenge being discussed publicly
The signal created the relevance. That's why the messaging worked.
Dual Lookalike Models Identified Fit While Signals Identified Timing
The automotive model prioritised:
Gen 5+ vehicle architectures
EV-focused OEMs
Connected services maturity
Personalised in-cabin experience investments
The healthcare model prioritised:
200+ bed hospitals
Teaching institutions
Low patient communication scores
Digital health maturity
Innovation-oriented nursing environments
Why Signal-Based GTM Works for Category-Creating Companies
Most outbound assumes buyers are already searching.
But category-creating companies rarely win that way.
Evoco succeeded because the GTM system focused on:
Detecting internal momentum
Identifying strategic timing windows
Entering conversations before formal buying processes existed
The Outcome
Qualified meetings increased 4.1×
1,600+ accounts were mapped and prioritised
Hot-trigger accounts converted to meetings at 58%
Two OEM pilot agreements were signed
Three hospital proof-of-concepts were launched
Evoco stopped trying to force category creation through cold outreach.
Instead, they inserted themselves into conversations already being created by market signals.
And that's what made enterprise adoption possible.