How I Build Each Stage

Six stages.
One connected system.

Every customer lifecycle stage — from first touch to expansion — designed, automated, and built to compound revenue. Here's the methodology behind the work.

Proof of Impact

Measurable outcomes
across every engagement.

Key metrics across managed accounts — tracked, reported, and built into every system from day one.

91%
Gross Revenue Retention
<10 min
Speed-to-Lead (from 48hrs)
300+
Accounts managed at full lifecycle depth
Retention Dashboard
Screenshot coming
Pipeline Activity
Screenshot coming
Email Sequence Performance
Screenshot coming
01
Lead Capture
Pipedrive — Lead Pipeline
Screenshot coming
Pipedrive pipeline view — lead stages,
source attribution, routing logic
The Problem
Leads arriving from multiple channels with no unified entry point. No scoring logic, no CRM sync, no routing rules. Marketing and sales teams operating on different data — or no data at all. Speed-to-lead measured in days, not minutes.
The Approach
Built a unified capture architecture — form-to-CRM field mapping, source attribution tracking, and a lead scoring model based on firmographic and behavioral signals. Automated routing by segment ensures every lead reaches the right person within 5 minutes of capture.
<5 min
The Result
Speed-to-lead reduced from 48 hours to under 10 minutes. Every inbound lead reached the right person automatically — no manual triage, no dropped leads.
Speed-to-Lead TargetResponding within 5 minutes makes a lead 21x more likely to convert than responding within 30 minutes. This was the north-star metric for every capture system built.
Tools Used
HubSpot Pipedrive Zapier Segment Google Tag Manager
02
Onboarding
Intercom — Onboarding Sequence
Screenshot coming
Intercom onboarding sequence —
milestone triggers, conditional branches
The Problem
New customers handed off from sales with no structured journey. No triggered sequences, no milestone tracking, no definition of "first value." Onboarding happened inconsistently — dependent on individual CSM effort rather than a system.
The Approach
Built milestone-based pipeline stages (Kickoff → Setup → First Value Achieved) with conditional branching based on activation behavior. Day 1 welcome sequences fire automatically. CSM alert triggers fire at key milestones. Contract details, tier, and billing dates stored as custom CRM fields.
<24h
The Result
Time-to-first-value cut from 3+ days to under 24 hours. Onboarding completion rate improved significantly — customers reached their first meaningful outcome before the end of day one.
Time-to-First-Value TargetIndustry average is 36 hours. The goal was under 24. Every onboarding system was built backwards from this metric — what's the fastest path to a meaningful outcome for this customer?
Tools Used
Pipedrive Intercom PandaDoc Notion Zapier
03
Activation
Activation — Behavioral Trigger Flow
Screenshot coming
Activation trigger sequence —
72hr window, re-engagement branch
The Problem
Users signing up but never reaching the moment where the product clicks. High early churn with no visibility into why. No definition of what "activated" even meant for the business.
The Approach
Defined the activation event per customer segment. Built behavioral trigger sequences — users who don't hit the milestone within 72 hours enter a targeted re-engagement flow. Feature adoption tracked and used to personalize every subsequent communication.
14 days
The Result
Early churn in the first 14 days dropped by over 30%. Users who previously ghosted after signup were re-engaged through targeted behavioral sequences before they disengaged.
Activation Measurement WindowFeature adoption depth within the first 14 days is the single strongest predictor of 90-day retention. Every activation system was built to maximize meaningful engagement within this window.
Tools Used
Intercom Metabase Zapier Pipedrive
04
Adoption
Adoption — Nurture Sequence
Screenshot coming
30/60/90 adoption cadence —
segmented by role and usage gap
The Problem
Activated users plateauing at surface-level usage. Deep features unused, teams not fully onboarded, value perception declining. No system to detect or respond to plateau signals before they became churn signals.
The Approach
Built adoption nurture sequences segmented by role and use case. Feature announcement emails tied to individual usage gaps — not broadcast to everyone. Regular 30/60/90 day check-in cadences with CSM visibility into engagement scores per account.
30/60/90
The Result
Feature adoption depth increased across 30/60/90 day cohorts. Plateau signals were caught early — accounts that received targeted nudges showed measurably deeper engagement within 2 weeks.
Adoption Measurement CadenceFeature adoption breadth — the number of core features actively used — measured at 30, 60, and 90 days. Accounts below threshold at each checkpoint triggered an automated intervention.
Tools Used
Intercom Crisp HubSpot Notion Metabase
05
Retention
Metabase — Customer Health Dashboard
Screenshot coming
Metabase health score dashboard —
at-risk accounts, GRR tracking, churn signals
The Problem
Churn happening reactively — accounts cancelling with no warning. CS team firefighting instead of preventing. No health visibility, no early warning system, no way to distinguish a healthy account from one quietly disengaging.
The Approach
Built a composite health scoring model across login frequency, feature usage, support ticket volume, and contract proximity. Accounts flagged as At Risk trigger an automated CSM alert and re-engagement playbook within 24 hours. Win-back sequences for churned accounts segmented by churn reason and tenure.
90%+
The Result
GRR stabilized at 91% within 60 days of implementing the health scoring system. At-risk accounts were flagged and contacted within 24 hours — response time dropped from 5 days to same-day.
Gross Revenue Retention TargetGRR is the baseline — how much revenue you keep before expansion. Risk-to-outreach SLA was set at under 24 hours. Every at-risk account received a human or automated touchpoint within one business day of flagging.
Tools Used
Pipedrive Metabase Intercom Zapier Notion
06
Expansion
Expansion — Signal & Upsell Pipeline
Screenshot coming
Expansion pipeline — usage thresholds,
CSM alerts, upsell proposal tracking
The Problem
Revenue from existing customers left entirely untapped. No signals, no triggers, no systematic upsell motion. Expansion happened by chance — when a customer happened to reach out — not by design.
The Approach
Instrumented expansion signals in the CRM — usage thresholds, seat limits, power-user behavior flags. When an account hit 80% of plan capacity, CSM received an automated alert to propose the next tier. QBR templates built to surface ROI proof at renewal. Expansion email sequences triggered by health score and account tenure.
110%+
The Result
Expansion ARR grew to represent 35%+ of total new revenue within one quarter. Usage-based triggers replaced manual outreach — CSMs were alerted at exactly the right moment to propose upgrades.
Net Revenue Retention TargetNRR above 100% means existing customers are growing faster than churn. Top-performing SaaS companies target 110–120%+. The goal was to make expansion ARR a predictable, systematic revenue stream — not a pleasant surprise.
Tools Used
Pipedrive Metabase PandaDoc Notion Zapier

Ready to build this for your team?I'm open to full-time CRM, lifecycle automation, and customer success roles.

Get in Touch
Back to Home
01 / 06 Lead Capture