Scattered commercial data is decision-making in the dark.
We consolidate commercial data on a single platform with applied intelligence, so prioritization, forecast and executive decisions run on context instead of intuition.
Commercial intelligence by the numbers
177%
more profit from replacing generic cross-sell with data-driven targeting
of CRM projects deliver no significant improvement; but when processes are structured (initiating, maintaining and ending relationships), the association with performance is positive
177% more profit with data-driven targeting vs. generic cross-sell. Does your commercial operation know where the money is, or does it chase everything?
When commercial data lives scattered across CRM, ERP and personal spreadsheets, every salesperson builds their own version of the portfolio. Prioritization becomes opinion, forecast becomes a bet and the commercial team spends its energy on the wrong accounts. The result is revenue that could exist and never materializes: quarter after quarter.
The real scenario
Four structural failures that blind commercial intelligence every day
Each of these four failures runs in silence. Together, they separate a team that prioritizes with context from a team that chases everything.
01
Commercial data scattered with no consolidation
Part of the commercial data in the CRM, another part in the ERP, a third in the salesperson's spreadsheet. With no single base, nobody has the full picture of the portfolio, and every report tells a different story. The operation decides on partial data and finds the error only in the consolidated view.
02
Prioritization by intuition, not by criteria
Which accounts to go after? Where to invest time? With no portfolio scoring on potential, risk and recency, the salesperson prioritizes what they already know, and the best opportunities stay hidden in the customer base nobody visited.
03
Forecast with no traceable assumptions
Revenue projection built on optimistic feeling, with no analytical criteria and no documented scenarios. When the forecast misses, nobody knows which assumption failed, and the next cycle repeats the same pattern of surprise.
04
CRM as a cost, not as intelligence
~70% of CRM projects deliver no significant improvement. But when processes are structured: initiating, maintaining and ending relationships: the association with performance is positive. What CRM projects lack is architecture.
We have seen this scenario before. And we know where commercial intelligence gets lost.
Commercial intelligence platforms fail because consolidation, prioritization, forecast and action run as disconnected dimensions. The Bunker Protocol connects those layers into a single architecture: with analytical criteria, governance and institutional visibility.
We design the platform that makes every piece of commercial data produce a decision with context.
40+ B2B operations with structured commercial intelligence
300+ CRM projects with prioritization architecture
8 countries with an active commercial intelligence platform
Documented increase in forecast accuracy in 45%+ of cases
The Bunker Protocol applied to Commercial Intelligence
Four phases. One intelligence platform. Auditable governance.
Phase 01
Data Diagnosis
We map the commercial data landscape end to end: active sources, record quality, information gaps and duplication across systems. We identify where the data exists but never reaches the decision-maker, where quality compromises the forecast and where the lack of governance produces conflicting versions of the same portfolio.
Outcomes
Map of commercial sources with quality and gaps by system
Real cost of decisions made on partial or outdated data
Fronts ranked by impact on prioritization and forecast
01
Phase 02
Consolidation Architecture
With the diagnosis in hand, we design the consolidation architecture: a single base with quality governance, integration across sources on a priority criterion and a data model that reflects the real operation. Every source gets a defined role: no duplication and no version conflict.
Outcomes
A single commercial base with governance of quality and updates
Integration across CRM, ERP and complementary sources
Data model with a consolidated view of portfolio and opportunity
02
Consolidation
One base. One version of the portfolio. One source of truth for the commercial team.
Phase 03
Prioritization Engine
We install the intelligence engine inside the real routine of the operation. Portfolio scoring on potential, risk and recency. Forecast with traceable assumptions and documented scenarios. Opportunity and risk alerts on a defined cadence. The commercial team sets its priorities on data.
Outcomes
Portfolio and opportunity scoring on analytical criteria
Forecast with documented assumptions and comparable scenarios
Opportunity and risk alerts on an operational cadence
03
Phase 04
Governance and Hand-off
We install a traceability dashboard with visibility of forecast accuracy, portfolio coverage and performance by segment. The operation advances in waves, with progressive autonomy. The goal is for your team to govern commercial intelligence without depending on us.
Outcomes
Governance dashboard with accuracy, coverage and performance
Data quality and model adherence indicators
Operational autonomy handed over to the internal team
04
Transformation
From scattered data to governed commercial intelligence
Without Bunker
Commercial decisions in the dark
Data in CRM, ERP and personal spreadsheets with no consolidation
Prioritization by intuition and salesperson familiarity
Forecast built on optimistic feeling with no stated assumption
CRM as an operational cost with no visible return
Opportunities hidden in the customer base nobody visited
With Bunker
Intelligence with criteria and action
A single commercial base with quality governance
Portfolio scoring on potential, risk and recency
Forecast with traceable assumptions and documented scenarios
CRM as an intelligence platform with measurable return
Commercial team focused on the accounts that generate results
Every month of scattered data is opportunity lost and a forecast that misses again.
The first step is a commercial data diagnosis. No commitment, no generic slide deck. Assess whether your commercial intelligence scenario justifies a different architecture.