Case Studies

Revenue systems
rebuilt.
Results measured.

Every engagement starts with a Revenue Diagnostic that baselines the current state. Every outcome is measured against that baseline. The results shown here reflect real improvements across real revenue systems — client identities kept confidential by agreement.

Case Study 01 — GTM Architecture
Unifying a fragmented go-to-market organization across three disconnected revenue teams
SaaS-Adjacent · B2B Software €18M ARR 7 Month Engagement
+41%
Improvement in marketing-to-sales conversion rate
−68%
Reduction in lead response time across the funnel
+€3.2M
Additional ARR captured in the first two quarters post-engagement
The situation
  • Marketing, sales and customer success operating as three independent functions with no shared objectives or definitions
  • MQL definitions disagreed upon — marketing passing leads sales consistently rejected
  • No ICP framework at the organizational level — each team targeting different customer profiles
  • Revenue stagnating despite increased marketing spend and headcount growth
  • Leadership unable to identify where in the funnel growth was breaking down
What the diagnostic found
  • 34% of marketing-qualified leads rejected at sales acceptance — no agreed qualification criteria
  • Average lead response time of 4.2 days — well above the threshold where conversion probability collapses
  • Three separate CRM configurations with no shared data model or reporting taxonomy
  • Customer success had no visibility into deal context at handoff — onboarding misaligned with sales promises
  • No unified KPI framework — each team reporting success against different metrics to the same leadership
Strategic interventions
  • Designed unified ICP framework and segmentation model across all GTM functions
  • Redefined MQL, SQL and SAO with shared, measurable criteria agreed by both marketing and sales leadership
  • Built GTM operating cadence — weekly pipeline reviews, monthly alignment rituals, quarterly GTM planning
  • Designed and implemented SLA framework with response time standards and escalation protocols
  • Built unified KPI taxonomy from board level to rep level — one set of numbers for the whole organization
Diagnose
3-week full GTM assessment. Interviewed stakeholders across all three functions, mapped the complete lead lifecycle, baselined 14 KPIs, and quantified €4.8M in annual revenue leakage from funnel misalignment and lead rejection rates.
Optimize
Redesigned the entire GTM architecture — unified ICP, shared funnel definitions, SLA framework, operating cadence, and a single revenue data model across all three teams. Facilitated organizational alignment workshops with senior leadership to establish shared accountability structures. Implemented a unified KPI dashboard visible to all GTM functions simultaneously.
Scale
Embedded as strategic advisor for two quarters post-implementation. Monitored KPI performance, facilitated monthly GTM alignment reviews, and advised on expansion into two new market segments using the same GTM architecture.

We had been growing the team without growing the revenue. The problem was never the people — it was that three teams were operating three different playbooks with no shared definition of what success looked like. Once the architecture was in place, everything else fell into line.

— Chief Revenue Officer · SaaS-Adjacent B2B Company · €18M ARR · Identity confidential

Client identity withheld by mutual agreement. Metrics reflect actual measured outcomes against pre-engagement baselines established in the Revenue Diagnostic.

Case Study 02 — Revenue Forecasting & Operational Intelligence
Building a forecasting infrastructure that leadership and investors could trust
Professional Services · B2B €22M Revenue 8 Month Engagement
−74%
Reduction in forecast variance vs actual revenue
+€4.1M
Revenue recovered through pipeline health intervention
+28%
Improvement in net revenue retention within 6 months
The situation
  • Company preparing for a Series B raise — investors challenging revenue projections at every meeting
  • Forecasting based entirely on rep-submitted estimates with no historical modeling
  • Consistent gap of 25–35% between forecast and actual revenue over 6 consecutive quarters
  • Pipeline stages undefined — no exit criteria, no velocity metrics, no coverage ratios
  • Retention tracked informally — no customer health model, churn consistently surprising leadership
What the diagnostic found
  • No single source of truth for revenue data — finance, sales and CS each maintaining separate numbers
  • Pipeline inflated by 40% due to deals aging beyond realistic close probability with no governance
  • Rep-submitted forecasts showed no correlation with historical close rates — the model had no predictive value
  • Customer health entirely unmeasured — 18 at-risk accounts identified immediately upon diagnostic completion
  • No cohort analysis — leadership unable to distinguish between new revenue growth and retention deterioration
Strategic interventions
  • Designed multi-method forecasting model combining historical trend analysis, rep-submitted data, and pipeline health scoring
  • Implemented pipeline governance framework — stage exit criteria, deal aging policies, coverage ratio targets
  • Built unified revenue data model eliminating three competing sources of truth
  • Designed customer health scoring system with early warning signals for churn risk
  • Delivered board-level revenue intelligence dashboard with real-time KPI visibility
Diagnose
3-week assessment focused on forecasting methodology, pipeline structure, and retention systems. Baselined forecast accuracy over prior 8 quarters, audited the full data model across three systems, and immediately identified 18 at-risk accounts representing €2.3M in revenue at risk. Quantified pipeline inflation at €6.1M.
Optimize
Designed and implemented a three-method forecasting model reconciled into a single executive number. Rebuilt the revenue data architecture with one source of truth. Introduced pipeline stage governance and deal health scoring. Built customer health model identifying at-risk cohorts 60–90 days before churn signals became visible. Designed a retention and expansion playbook for CS to act on health signals proactively.
Scale
Advised through the Series B fundraising process — supported investor data room preparation and revenue model presentation. Continued as strategic advisor embedding into the quarterly planning cadence to maintain forecasting discipline as the organization scaled.

Our investors were losing confidence in our numbers because frankly we were too. We had been running the company on instinct. What we built with RevOpsBI was the operational intelligence layer we should have had two years earlier — and it changed the quality of every strategic conversation we had from that point on.

— CEO · Professional Services Company · €22M Revenue · Identity confidential

Client identity withheld by mutual agreement. Metrics reflect actual measured outcomes against pre-engagement baselines established in the Revenue Diagnostic.

Case Study 03 — M&A GTM Integration
Integrating two revenue organizations into a single high-performance commercial engine post-acquisition
IT Services · B2B Technology €35M Combined Revenue 10 Month Engagement
+€5.8M
Incremental revenue from cross-sell motion in first year post-integration
−60%
Reduction in revenue tech stack cost through rationalization
+38%
Improvement in combined pipeline conversion rate at 12 months
The situation
  • Two companies merged — both continuing to operate as independent commercial organizations 9 months post-close
  • Separate CRM systems, separate sales methodologies, separate customer databases with significant overlap
  • Combined leadership unable to see a unified view of total pipeline, revenue, or customer base
  • Cross-sell opportunity between the two customer bases entirely uncaptured
  • Revenue tech stack duplicated across both organizations — 14 tools with 8 direct overlaps
What the diagnostic found
  • No unified data model — €35M combined revenue visible only through manual reconciliation between two finance teams
  • 340 customer accounts appearing in both CRMs with conflicting ownership and relationship history
  • Two incompatible sales methodologies creating friction for any rep working across both product lines
  • €7.2M in cross-sell opportunity identified across the overlapping customer base — zero systematic motion to capture it
  • Combined tech stack spending 40% above industry benchmark for equivalent functionality
Strategic interventions
  • Designed full RevOps integration roadmap — sequenced by impact and organizational risk
  • Built unified revenue data architecture — single CRM, single customer record, single reporting layer
  • Designed unified sales methodology harmonizing the strongest elements of both pre-merger approaches
  • Built cross-sell GTM motion with ICP alignment, territory design, and enablement framework
  • Rationalized combined tech stack from 14 tools to 6 — eliminating all redundancies without capability loss
Diagnose
4-week RevOps due diligence assessment across both organizations. Mapped all revenue systems, processes, customer records and tech infrastructure. Identified 8 areas of critical misalignment, quantified €7.2M cross-sell opportunity, and modeled full tech stack rationalization savings. Delivered integration sequencing roadmap prioritized by revenue impact and organizational disruption risk.
Optimize
Led full GTM integration in three phases — data architecture first, process harmonization second, go-to-market alignment third. Migrated and reconciled all customer data into a unified CRM. Designed and rolled out the combined sales methodology with structured enablement program. Built the cross-sell GTM motion from ICP through territory design, qualification criteria, and playbook. Managed full tech stack rationalization including vendor negotiations and migration planning.
Scale
Continued as strategic RevOps advisor through the first full fiscal year post-integration. Supported two additional bolt-on acquisitions using the integration framework built in this engagement. Advised on organizational design as the combined company scaled past €40M.

Nine months after the acquisition we were still running two separate companies. The integration felt impossible from the inside — too many systems, too many conflicting processes, too much organizational friction. What RevOpsBI did was give us a clear sequenced plan and then execute it. Twelve months later we had one commercial organization and a cross-sell motion that was already generating meaningful revenue.

— Group CEO · B2B Technology Company · €35M Combined Revenue · Identity confidential

Client identity withheld by mutual agreement. Metrics reflect actual measured outcomes against pre-engagement baselines established in the Revenue Diagnostic.

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