Engagements

Case studies

TCGWhere deals slip

+$44k revenue recovered in two weeks. 50 hours of sales time back every week.

  • AI reply triage
  • 50 hours of reps time back per week
  • Never lose a single deal
  • Retired unused tools
  • CRM as single source of truth
TOTAL+$44k in 2 wks
Fashion partnerships agency, New YorkRead the case study →
C/OWhere customers come from

Cut $62,961 of marketing spend to make $1.1m in sales

  • Redirected spend to highest ROI campaign
  • Drove $1.1m in sales
  • One definition of revenue, one quota basis
  • Tracking marketing to sales handoff
TOTAL$62,961 cut
Managed services provider, cloud infrastructureRead the case study →
LunchboxWhere deals slip

14 hours saved per rep, every week.

  • Salesforce built from scratch
  • Auto lead scoring and assignment
  • Automated deal stage progression
  • Automated dialing
TOTAL14 hrs/rep/wk
Restaurant ordering and marketing platformRead the case study →
D3 InvestmentsWhat the numbers say

No more “how much am I getting paid?”

  • Sales process from scratch
  • Old data migrated and cleaned
  • Auto comp tracking
TOTALLive in two weeks
Real estate investment, multifamily syndicationRead the case study →
Diana Deng LLCWhere customers come from

1.5× conversions from Chinese TikTok. Same content, same spend.

  • Mapped video → inquiry conversion path
  • Fixed how people reach out
  • Automated comment replies
  • Team trained to run it alone
TOTAL1.5× conversion
Real estate agencyRead the case study →
PatchWhat the numbers say

Automated forecast. AI-driven lead scoring as early as 2023.

  • HubSpot → Salesforce migration, end to end
  • Data pipeline and BI layer from zero
  • Automated forecast
  • Quarterly planning: two months → two weeks
  • LLM lead scoring
TOTALPlanning in two weeks
SaaS, Series ARead the case study →
RitualWhat the numbers say

CRM, marketing, billing and in-person bookings on one integration layer.

  • Automated CRM ↔ billing: closed-won means paid
  • Automated Marketing ↔ CRM: one customer, one history
  • Auto optimize CRM ↔ in-person visits
TOTAL4 systems, one record
Restaurant techRead the case study →

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