Pipeline Playbooks
Case Study
Juno
AI Tax Accounting11–50 EmployeesPhiladelphia

How Juno Scaled From £20k/mo to a £700k Record Month

$200k→$1.8M
ARR IN 10 MONTHS
87
MEETINGS BOOKED
$6.5M
PIPELINE GENERATED
~50%
TRIAL → PAID LIFT

The Challenge

  • Launching a new product with almost no inbound
  • No sales team or repeatable GTM motion
  • CRM not set up to scale with pipeline
  • Lean team: Founder + COO running marketing
  • Generic prospect lists producing poor reply rates
  • No clear self-serve vs sales-led motion defined
  • Founders stuck in every deal, blocking scale

The Solution

  • Signal-based outbound playbook for hyper-relevant targeting
  • Email infrastructure + LinkedIn automation at scale
  • HubSpot pipeline rebuild + n8n automations
  • AI sales engineer agent + Fireflies auto-logging
  • Clear sales-led vs self-serve motion with usage-based nurture
  • Partner quoting tool unlocking partner-driven revenue
  • Automated follow-ups saving ~15 hrs/week of rep time

The 3-Phase Playbook

1
Build Pipeline
Signal-based outbound
+ custom messaging
2
Fix Conversion
On-site GTM audit
+ HubSpot rebuild
3
Scale Without Hiring
AI agents + automated
follow-up workflows
MetricBefore Pipeline PlaybooksAfter
ARR~$200k$1.8M
Pipeline GeneratedNo outbound motion$6.5M total
Meetings BookedAlmost none87 qualified meetings
Trial → PaidManual, inconsistent~50% lift, no new hires
Sales Team CapacityFounders in every deal~45 hrs/week saved via AI

Key Learnings

1
Signal Beats Volume
Signal-based targeting unlocked hyper-relevant messaging that generic list-builders couldn’t match.
2
Outbound Reveals the Real Bottleneck
Meetings grew fast. The next constraint wasn’t pipeline — it was conversion.
3
On-Site Changes Everything
Sitting with the sales team in Philadelphia surfaced problems no Slack audit ever would.
4
Systems > Headcount
AI agents and automations scaled revenue 9x without adding a single sales rep.