Case Studies

The work
speaks.

Anonymized results from PE portfolio companies and B2B organizations. No client names. No logos. Just what was broken, what got built, and what happened next. Detailed case studies are available in conversation.

01
FinTechSeries BSalesforce

62% Reduction in CAC

62%

CAC Reduction

2.8x

ROAS Improvement

4mo

Time to Results

Situation

Series B FinTech burning $400K/month on paid channels with no attribution. Marketing and sales blamed each other for pipeline gaps. Three different teams tracked leads in three different systems.

Intervention

  • Unified data model across Salesforce, HubSpot, and ad platforms
  • Multi-touch attribution with weighted models for each channel
  • Automated budget reallocation based on pipeline contribution
  • Sales + marketing shared dashboard with real-time pipeline data
  • Lead lifecycle tracking from first touch through closed-won

Shift

Spending decisions moved from intuition to data. Attribution revealed what was working and what was burning budget. Alignment replaced blame.

Outcome

62% reduction in customer acquisition cost within 4 months. Same pipeline, 60% less spend. The attribution model revealed two channels contributing nothing, and one underinvested channel driving 40% of qualified pipeline.

Geometric architectural patterns
02
Healthcare ITPE Portfolio6Sense

$12M Sourced Pipeline, Quarter One

$12M

Sourced Pipeline

90

Days to Launch

0→1

From Nothing

Situation

Newly acquired PE portfolio company. No marketing function existed. Sales team was running on referrals and trade shows. PE sponsors needed pipeline within 90 days.

Intervention

  • HubSpot implementation from zero: CRM, marketing automation, CMS
  • Salesforce integration with bidirectional sync
  • 6Sense deployment: ICP modeling, intent signal activation
  • ABM program targeting 500 named accounts
  • Content engine: 4 assets/month, gated and ungated
  • SDR playbook with intent-triggered outreach sequences

Shift

Marketing went from nonexistent to operational in 90 days. Intent data drove outbound plays. Pipeline became predictable and measurable.

Outcome

$12M in sourced pipeline in the first quarter. 23 qualified opportunities from accounts that had never heard of the company 90 days prior. PE sponsors extended the engagement for two additional portfolio companies.

Modern architectural detail
03
B2B SaaSSeries CMarketo

3.2x Pipeline Growth in 6 Months

3.2x

Pipeline Growth

47%

MQL to SQL Rate

6mo

Time to Results

Situation

A Series C B2B SaaS company had attempted a Marketo migration 18 months prior. The migration failed halfway through, leaving the marketing team operating on a hybrid of broken automation and manual spreadsheets.

No lead scoring existed. Attribution was impossible because campaign membership data was incomplete. Lead routing was done manually by an ops person who was also managing events. Sales and marketing had not shared a dashboard in over a year.

Pipeline had been flat for three quarters despite a 40% increase in ad spend. The board was asking questions.

Intervention

  • Complete Marketo rebuild from scratch. New instance architecture with proper folder structure, naming conventions, and program templates. Legacy data was cleaned, deduplicated, and migrated with full audit trail.
  • Behavioral and demographic scoring model built from 12 months of closed-won analysis. Score decay implemented at 30/60/90 day intervals. MQL threshold validated against actual conversion rates before launch.
  • Multi-touch attribution model in Salesforce using custom campaign influence objects. First-touch, last-touch, and weighted models available for different reporting contexts.
  • Automated routing with round-robin and territory-based logic. SLA alerts for untouched leads. Escalation paths for high-score accounts.
  • 12 nurture sequences across 4 segments (by industry and buying stage). Dynamic content personalization based on firmographic data. Engagement scoring feeding back into the lead scoring model.

Shift

Pipeline grew 3.2x within 6 months of the new infrastructure going live. MQL to SQL conversion improved from 12% to 47%, meaning sales was spending time on leads that actually converted.

The sales team reported spending 30% less time on unqualified leads. Marketing could finally prove channel-level ROI to the board. The system now runs with one part-time ops person maintaining it.

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