Global B2B software company · USA, Europe, and India
Predictive Acquisition Infrastructure for Global B2B Software
An account-level propensity and next-best-action blueprint coordinating marketing and sales around first-party buying signals.
Anonymized architecture blueprint. No client or personal identity is disclosed. Figures are success targets—not published claims of achieved client performance—and require engagement-level validation before external attribution.
01 · Problem
The operating constraint
Marketing and sales use different scoring models, producing conflicting priorities and slow handoffs. Reporting emphasizes activity rather than account progression or incremental pipeline.
02 · Solution
The control-plane design
The system joins product, content, CRM, and commercial events into an account graph. Calibrated models estimate buying-stage movement while policy controls territory, consent, and frequency.
03 · Architecture
Signal-to-action flow
- Resolve account and buying-committee identities
- Create time-aware intent and engagement features
- Calibrate propensity and progression models
- Select next-best action under channel constraints
- Measure incremental account-stage movement
Mermaid.js source
graph LR
A[Product + Web Events] --> C[Account Graph]
B[CRM + Commercial Data] --> C
C --> D[Propensity Models]
D --> E[Next-Best-Action Engine]
E --> F[Marketing + Sales]
F --> G[Incrementality Measurement]04 · Impact
Measure the decision, not the demo.
Baseline operational cost, decision latency, reliability, override behavior, business lift, and risk events before deployment. Report exceptions and uncertainty alongside headline outcomes.
Related Silvrix AI capability ↗Executive working session
Define the AI system worth building.
Map the decision, economics, data, controls, and implementation path in a focused strategy conversation.