Enterprise Use Case | AscendBase
Use Case / Enterprise

From Siloed Functions to a Unified Revenue Architecture

How a €21.6M ARR manufacturing enterprise with dedicated SDR, AE, and CS teams unified its revenue operations, recovered €2.6M in annual revenue, and achieved 118% NRR.

Revenue Before
€21.6M
ARR
Revenue After
€24.2M
+€2.6M in 12 months
NRR Improvement
91% to 118%
+27 points
Pipeline Velocity
+165%
€240 to €630 daily
This is a hypothetical use case for illustrative purposes only. Actual results vary based on business context, market conditions, and engagement scope.

The Situation

Company Profile

Precision industrial equipment manufacturer, 7 years established, €21.6M ARR. Growth stalling despite adding headcount in sales, engineering, and operations.

Organizational Structure

15 SDRs, 20 AEs, 10 CSMs, 2 marketing managers, and VP Sales. Each function operating independently.

Tech Stack

Salesforce CRM, Marketo, Zendesk for CS, ERP integration incomplete, plus 8 separate spreadsheets for forecasting and inventory coordination. Data completely siloed.

Core Problem

Each function optimized for its own metrics with zero unified revenue view. Attribution wars consumed leadership energy.

The Problems

Acquisition Phase

Lead Generation Misalignment: 60% of booked meetings were unqualified, measured on volume not quality
Marketing-Sales Disconnect: Sales rejected 72% of leads to unqualified accounts. No shared ICP definition across functions
Prospect Qualification Crisis: Cost-per-SQL €1,200 vs benchmark €600-800 (150% overspend)
Speed Failures: Average time-to-contact 14 hours. Lead routing manual and slow
ABM Ineffectiveness: ABM programme running with zero integration to SDR sequences

Conversion Phase

Pipeline Corruption: 55% zombie deals with no activity in 30+ days
Poor Handoff: AEs received meetings without context, pain data, or qualification
Low Win Rate: 19% vs benchmark 30-40%. Single-threaded deals (80%)
Long Sales Cycle: 108 days vs benchmark 45-65 days. Proposals sent without scheduled walkthroughs
Bad Forecasting: Actual revenue 35-40% below forecast. No deal inspection framework

Retention & Expansion

Churn Crisis: 18% annual churn vs benchmark 5-8%. 45% due to technical integration complexity, 35% in first year
Failed Onboarding: Zero documentation in sales-to-CS handoff. CS learned through trial and error
Poor Health Visibility: No health scoring. At-risk accounts identified only at renewal
No Expansion Motion: Expansion just 3% of revenue vs benchmark 15-25%. Zero expansion playbook
Missing QBRs: Client QBRs not happening. CS entirely reactive

Cross-Functional Breakdown

No Feedback Loops: Marketing unaware of lead quality issues. CS unable to flag expectation gaps
Misaligned Comp Plans: SDRs paid for meetings, AEs for revenue, CS for retention. No shared incentive
Unreliable Forecasting: VP Sales forecast based on gut feel, not pipeline probability

The Analysis

Revenue Waterfall

Monthly Leads
620
MQL Rate
28%
174 MQLs
MQL-to-SQL Acceptance
28%
49 SQLs
SQL-to-Close
19%
Monthly Closes
9.3
ACV: €28K
Pipeline Velocity
€49/day
Benchmark: €130/day
Revenue Leaks Identified: Conversion losses €1.14M/year, Acquisition quality €720K/year, Retention €475K/year, Expansion €280K/year. Total recoverable: €2.6M annually.

The Solutions

1

Phase 1: Foundation (Weeks 1-10)

  • Executive alignment session with CEO, VP Sales, Marketing Manager
  • Unified ICP document created across all three functions (firmographic + psychographic + triggers)
  • CRM pipeline rebuilt: separate inbound/outbound pipelines, 6 milestone-based stages
  • Mandatory fields enforced with validation rules
  • SDR-to-AE handoff protocol redesigned with structured handoff documents
  • SQL definition agreed in writing with explicit SPICED criteria
  • Lead scoring v1: ICP match + intent signals + engagement score
  • Lead routing automated: high-intent to senior AE, standard to round-robin
  • Speed-to-lead: <5 minute SLA for inbound with automated task + notification
  • Revenue operations dashboard (CEO): 12 metrics, daily refresh
  • Sales performance dashboard (VP Sales): per-rep metrics
2

Phase 2: Operations (Weeks 11-22)

  • SPICED qualification training across all SDRs and AEs
  • Deal inspection framework (7-question protocol) in weekly pipeline reviews
  • Champion identification added as mandatory pipeline field
  • Multi-threading requirement for deals above €20K
  • Proposal walkthrough protocol: no proposal without scheduled call
  • Stale deal automation: 10-day flag for SDR pipeline, 14-day for AE
  • Forecasting system: pipeline-weighted + commit + best/worst bands
  • SDR compensation restructured: tied to SQL acceptance rate
  • AE compensation: accelerators at 100%, 120%, 150% of quota
  • CS compensation: GRR as gating metric + expansion bonus
  • Sales-to-CS handoff document integrated into CRM (auto-populated)
  • Onboarding playbook: pre-kickoff, Day 7/14/30/60/90 milestones
  • Health scoring system: 5-category weighted model
  • Weekly lead quality review (marketing + SDR lead)
3

Phase 3: Scale (Weeks 23-36)

  • Multi-touch attribution model live (30/40/30 weighting)
  • Marketing channel mix restructured based on SQL attribution
  • ABM programme integrated with SDR outbound sequences
  • Expansion playbook deployed with signal identification and conversation framework
  • Expansion triggers automated: health score >80 + 6 months tenure + NPS 9+
  • Client QBR cadence: quarterly for all, monthly for top 20%
  • Churn early warning system: 8 signals monitored with save protocol
  • Call review cadence: weekly for SDRs, bi-weekly for AEs
  • Full BI dashboard suite live (CEO, VP Sales, Marketing, CS views)
  • Cross-functional revenue review: monthly with all function leads
  • Voice-of-customer programme: quarterly language harvest for marketing

The Results (After 12 Months)

Annual Recurring Revenue
€21.6M to
€24.2M
+€2.6M (+12%)
Net Revenue Retention
91% to
118%
+27 points
Win Rate
19% to
33%
+73% improvement
Sales Cycle
108 days to
58 days
-46% reduction
Pipeline Velocity
€240/day to
€630/day
+165%
Annual Churn
22% to
8%
-64% reduction
Expansion Revenue
3% to
19%
of total revenue
MQL-to-SQL Acceptance
28% to
61%
+118%
Cost-per-SQL
€890 to
€410
-54% reduction
Forecast Accuracy
~60% to
89%
+48% improvement
CRM Completeness
42% to
94%
+124%
Pipeline Zombie Rate
55% to
6%
-89% reduction
Time-to-Contact (Inbound)
14 hours to
8 minutes
-105x faster
SDR Quota Attainment
1 of 3 to
3 of 3
100% attainment
AE Quota Attainment
1 of 4 to
3 of 4
75% attainment

Operating with this level of complexity?

Your revenue architecture is likely leaving significant value on the table. A unified, data-driven approach to go-to-market can recover the same gains across acquisition, conversion, retention, and expansion.

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