We use public, time-stamped signals to target a micro-segment that shares your current pressure, then hand-write the first messages—context-driven and reputation-safe.
Seed round + 2 SDR roles + Salesloft live → 12 accounts flagged; first messages and scoring included.
A walkthrough of the exact process—from following the paper trail to writing messages that lead with evidence, not assumptions.
Why outbound fails when it starts with a generic list
How I qualify with public deal evidence
What ruthless disqualification looks like
Extracting strategic intelligence (not just emails)
Peer-to-peer messages that don’t read like vendors
The payoff: context-driven ABM that earns respect and replies
No generic lists. We pull public, time-stamped signals that point to real, shared pain—then write messages that fit that reality. Here are examples.
We track: new-geo hiring/subdomains, policy-page diffs (≤30 days), audit/backlog mentions.
You get: bottleneck alert + relevant audit snapshot.
We track: price gaps vs. marketplaces, review-velocity swings, offer changes.
You get: SKU-level recovery targets + a pricing opener that lands.
We track: visible stack, integration-complaint trails, fresh budget/RFP/new owner.
You get: right-timed outreach + a 3-step switch plan.
We track: incident spikes, status-page history, hiring for escalation roles.
You get: contract-exposure message + a renewal-risk account list.
We track: public integration complaints, ticket-backlog heat, changelog gaps.
You get: time-to-value reframed + prioritized unblock tasks.
MSPs, cybersecurity, SaaS, and professional services—anywhere risk, cost, or revenue leaves public footprints. We prove why you, why now before the first email.
capacity shifts · incident patterns · contract cycles
regulatory moves · control gaps · team signals
geo expansion · churn risk · integration friction
margin pressure · backlog spikes · scope creep
“Noticed you’re adding regulated-state pages while security questionnaires pile up. Teams hit a wall around 50+ controls with manual reviews. Those who broke through automated evidence pre-request and cut cycle time 60%. Sound familiar?”
“Found 63 multi-location targets with 18–26% price gaps vs marketplaces and high review velocity. Here’s a redacted snapshot. Want the full sheet with URLs and timestamps?”
Human-written. No AI prose. AI only for facts/list hygiene. Inbox placement ~95%+ (verified weekly).
Adapt per person: Move prospects from unaware to solution-aware with tailored messaging.
Assemble from human-written blocks: Ensure every email sounds genuinely human because it is.
Rotate domains: Maintain high deliverability with full SPF, DKIM, DMARC, and seed list monitoring.
We turn evidence into pipeline. Stats below come with segment context and proof on request.
Reply Lift
vs. AI-generated benchmarks over 60-day windows
Inbox Placement
verified weekly across active inboxes
Lower Cost/Meeting
vs. SDR teams at similar volumes
Methodology: n=XX campaigns; time frame YY–ZZ; segments scored with 2–5 public signals; details on request.
We pick one tight segment, pull public signals, write/send the first messages, and measure replies. If it works, we scale. If not, you keep everything.