CASE STUDY
$2.8B ARR Enterprise SaaS
Pre-IPO
420-Person Sales Org
CASE STUDY
$2.8B ARR Enterprise SaaS
Pre-IPO
420-Person Sales Org
Revenue: $2.8B ARR | 4,600 employees | Fortune 500 buyer base
Sales Org: 420 people across AEs, SDRs, Deal Desk, Sales Ops, Enablement
Tech Stack: Salesforce Enterprise, Gong, Clari, DocuSign CLM, Slack, CPQ, Tableau, Highspot
Average enterprise deal was $1.2M ACV with a 9-month sales cycle. Reps were strong closers but spent 38% of their time on internal work: updating Salesforce, chasing deal desk approvals, routing contracts through legal, reconciling comp disputes, and prepping forecast calls.
The deal desk processed 140 deals per quarter, and every deal over $500K required pricing approval, legal review, security questionnaire, and buyer-side procurement paperwork. The internal handoff chain on a large deal touched 6 teams across 11 distinct handoff points. Deals didn't die because the buyer said no. They died because internal process took so long that the buyer's budget cycle moved on.
Forecast accuracy was plus or minus 25%. Security questionnaire responses were written from scratch every time despite 70% of questions being identical. Lead routing took 4-6 hours. Comp disputes consumed 2 weeks of sales ops time every quarter. Customer handoff to CS took 10-15 days after contract signature.
FDE embedded across the full sales org, shadowing 3 enterprise AEs, sitting with the deal desk for a full week, spending time with sales ops, enablement, and the SDR team. Mapped every touchpoint from lead to closed-won to CS handoff.
Systemic patterns
Full sales operating layer from lead intake to customer handoff.
Lead scoring agent enriching inbound leads with firmographic, technographic, and intent data, scoring against ICP, and routing to the right SDR based on territory, segment, and current capacity. SDR assist agent pre-researching accounts, drafting personalized sequences, and logging all activity automatically.
CRM enrichment agent auto-updating Salesforce records from Gong transcripts, email threads, calendar events, and Slack conversations. Pipeline hygiene agent identifying stale deals, missing fields, and inconsistent stage criteria.
Deal routing agent monitoring every open enterprise deal, tracking position in the internal approval chain, auto-triggering next steps, and escalating stalled approvals after SLA breach. Pricing agent validating proposed pricing against margin thresholds and historical precedents. Contract acceleration agent generating first-draft redlines based on buyer markup patterns.
Security questionnaire agent matching questions against 2,000+ prior responses, auto-filling the 70% that are standard. RFP response agent pulling relevant case studies, technical specs, and compliance certifications.
Forecast intelligence agent building weekly forecasts from actual deal signals (email velocity, Gong sentiment, stakeholder engagement, legal progress) rather than rep self-reporting. Flags deals where objective signals disagree with stated probability.
Content recommendation agent surfacing relevant Highspot assets based on deal context and flagging stale content. Win/loss analysis agent ingesting Gong transcripts to identify recurring patterns.
Commission calculation agent tracing every closed deal from Salesforce through CPQ through DocuSign through NetSuite, validating against comp plan rules. Territory and quota agent modeling territory balance using pipeline distribution and market potential data.
CS transition agent assembling a complete implementation kickoff package from Gong transcripts, Salesforce, and DocuSign, delivering it to the CS team on the day the deal closes.
Month-by-month focus and results.
Revenue attribution uses conservative methodology: cycle compression value calculated from historical pipeline velocity and conversion rates, not top-down assumptions. Win rate improvement measured against matched control cohort. All estimates discounted to 70-85% for year-one realization.
Value Drivers
Sales agents fed closed-deal data into finance revenue recognition, eliminating 2-week lag. Finance margin data surfaced inside deal orchestration. CS handoff context fed back into win/loss analysis. These cross-department effects are not included in the value estimate above.
Revenue: $2.8B ARR | 4,600 employees | Fortune 500 buyer base
Sales Org: 420 people across AEs, SDRs, Deal Desk, Sales Ops, Enablement
Tech Stack: Salesforce Enterprise, Gong, Clari, DocuSign CLM, Slack, CPQ, Tableau, Highspot
Average enterprise deal was $1.2M ACV with a 9-month sales cycle. Reps were strong closers but spent 38% of their time on internal work: updating Salesforce, chasing deal desk approvals, routing contracts through legal, reconciling comp disputes, and prepping forecast calls.
The deal desk processed 140 deals per quarter, and every deal over $500K required pricing approval, legal review, security questionnaire, and buyer-side procurement paperwork. The internal handoff chain on a large deal touched 6 teams across 11 distinct handoff points. Deals didn't die because the buyer said no. They died because internal process took so long that the buyer's budget cycle moved on.
Forecast accuracy was plus or minus 25%. Security questionnaire responses were written from scratch every time despite 70% of questions being identical. Lead routing took 4-6 hours. Comp disputes consumed 2 weeks of sales ops time every quarter. Customer handoff to CS took 10-15 days after contract signature.
FDE embedded across the full sales org, shadowing 3 enterprise AEs, sitting with the deal desk for a full week, spending time with sales ops, enablement, and the SDR team. Mapped every touchpoint from lead to closed-won to CS handoff.
Systemic patterns
Full sales operating layer from lead intake to customer handoff.
Lead scoring agent enriching inbound leads with firmographic, technographic, and intent data, scoring against ICP, and routing to the right SDR based on territory, segment, and current capacity. SDR assist agent pre-researching accounts, drafting personalized sequences, and logging all activity automatically.
CRM enrichment agent auto-updating Salesforce records from Gong transcripts, email threads, calendar events, and Slack conversations. Pipeline hygiene agent identifying stale deals, missing fields, and inconsistent stage criteria.
Deal routing agent monitoring every open enterprise deal, tracking position in the internal approval chain, auto-triggering next steps, and escalating stalled approvals after SLA breach. Pricing agent validating proposed pricing against margin thresholds and historical precedents. Contract acceleration agent generating first-draft redlines based on buyer markup patterns.
Security questionnaire agent matching questions against 2,000+ prior responses, auto-filling the 70% that are standard. RFP response agent pulling relevant case studies, technical specs, and compliance certifications.
Forecast intelligence agent building weekly forecasts from actual deal signals (email velocity, Gong sentiment, stakeholder engagement, legal progress) rather than rep self-reporting. Flags deals where objective signals disagree with stated probability.
Content recommendation agent surfacing relevant Highspot assets based on deal context and flagging stale content. Win/loss analysis agent ingesting Gong transcripts to identify recurring patterns.
Commission calculation agent tracing every closed deal from Salesforce through CPQ through DocuSign through NetSuite, validating against comp plan rules. Territory and quota agent modeling territory balance using pipeline distribution and market potential data.
CS transition agent assembling a complete implementation kickoff package from Gong transcripts, Salesforce, and DocuSign, delivering it to the CS team on the day the deal closes.
Month-by-month focus and results.
Revenue attribution uses conservative methodology: cycle compression value calculated from historical pipeline velocity and conversion rates, not top-down assumptions. Win rate improvement measured against matched control cohort. All estimates discounted to 70-85% for year-one realization.
Value Drivers
Sales agents fed closed-deal data into finance revenue recognition, eliminating 2-week lag. Finance margin data surfaced inside deal orchestration. CS handoff context fed back into win/loss analysis. These cross-department effects are not included in the value estimate above.
