Skip to content
Brandon Olander
← All case studies

Portfolio system artifact · 60-second read

Designing revenue orchestration for multi-product B2B

A working model for keeping product usage, buying-group evidence, sales ownership, customer context, and governance from collapsing into one lead score or lifecycle field.

Customer lifecycle architecturePLG + enterpriseRevenue systemsAI governance

The problem

Most GTM systems collapse too many different facts into one account score or lifecycle stage. Product usage, marketing engagement, buying-group evidence, opportunity status, customer health, and sales ownership start contaminating one another. The result is bad routing, irrelevant outreach, false qualification, and constant friction between Marketing and Sales.

What I designed

I designed a deterministic revenue-orchestration model that keeps observed evidence separate from inference, commercial readiness separate from permission to act, account context separate from product-specific purchase motions, and hard blocks separate from owner precedence and warnings.

The model runs twelve synthetic B2B scenarios across PLG, expansion, active opportunities, consent restrictions, support escalations, identity problems, SLA failures, and third-party intent. Every scenario produces an inspectable path from signal to coordinated action.

What this demonstrates

Lifecycle architecture

Models people, accounts, products, buying groups, opportunities, and customer context as separate states instead of forcing them into one funnel field.

Revenue orchestration

Turns fragmented GTM signals into an explicit next action, owner, participating teams, and reason for the decision.

Cross-functional governance

Separates commercial readiness from permission to act so Sales, Marketing, Product, Customer Success, and RevOps can share one system without breaking rules of engagement.

AI authority design

Defines where probabilistic systems could assist interpretation while keeping consent, ownership, hard blocks, and other high-consequence authority boundaries deterministic and auditable.

The decision architecture

The point is not a prettier lead score. The point is making the reason for an action inspectable.

Event → Evidence → Customer state → Assessment → Governance → Permission → Action → Owner

That separation lets multiple revenue motions coexist on the same account without a PLG signal inflating an unrelated enterprise deal, or an active opportunity suppressing every other valid product motion. Truly account-wide constraints can still apply where they belong.

My role

I defined the lifecycle architecture, business rules, authority boundaries, failure modes, and cross-functional operating model, then used AI-assisted engineering to turn that system design into a testable interactive artifact. The artifact is synthetic by design and makes no claim of live customer data, live AI, or production revenue impact.

See the idea in 60 seconds

Follow one account from evidence to action.

The expansion-ready scenario shows the core idea quickly: strong evidence can create commercial readiness, while governance still remains a separate decision about whether and how the organization should act.

Open the interactive lab
  1. 01Open the interactive Revenue Orchestration Lab.
  2. 02The Expansion-ready customer scenario is preselected.
  3. 03Choose Jump to outcome.
  4. 04Read Orchestration, then Decision trace, to see the path from evidence to action and owner.

Recruiter takeaway

This artifact shows how I think beyond campaigns and into the operating architecture that connects Demand Gen, Lifecycle, PLG, Sales, RevOps, Product, Customer Success, data, and AI.

Contact

Working on a similar GTM problem?

If your team is trying to coordinate lifecycle, PLG, sales ownership, and revenue operations without creating another black-box score, get in touch.