After two decades of working with large, global organizations across geographies, cultures, and industries, one pattern kept repeating itself:

The customer lifecycle is everywhere. But lifecycle intelligence is rare.

I've seen teams optimize demand generation while others struggle with onboarding. Product teams chase engagement metrics while finance retools pricing. Support teams firefight churn while sales plans the next quarter.

Everyone is solving pieces. No one is solving the system.

This fragmentation creates what we call the Lifecycle Intelligence Gap.

Data exists. Tools exist. But insight doesn't flow. Context is lost between functions. Decisions lag behind reality. And the system as a whole becomes reactive, not adaptive.

According to McKinsey, companies that integrate lifecycle data across functions see up to 20% improvement in retention and cross-sell. Yet fewer than 12% of firms report being able to act on that data in real time.
(Source: McKinsey & Company, 2023 – link).

At SigmaArc, we built SPECTRA to close that gap.

SPECTRA is our architecture for customer lifecycle intelligence. It connects how organizations perceive, decide, and operate across the entire customer journey — from first signal to final renewal.

What does SPECTRA do?

SPECTRA is not a product. It’s an intelligence layer that activates real business flows:

• Lead optimization through connected demand signals

• Onboarding intelligence for activation and value realization

• Revenue precision through pricing, margin, and forecasting feedback

• Behavioral insight for churn prediction and customer success

• Operational adaptability across CX, support, and finance

It’s built on four core dimensions: Technology, Governance, Experience, and Enablement. Together, they power intelligent action where it matters most.

We didn’t set out to build a framework. We set out to answer a problem:

Why do so many well-instrumented companies still struggle to act intelligently across the customer lifecycle?

And the answer wasn’t more tooling. It was architecture.

Where this is going

We’re working with early adopters who want to:

• Improve CLTV by reducing leakage across lifecycle stages

• Align GTM, product, and ops teams with shared intelligence

• Build systems that don’t just see the customer — they respond to them

We’ll share what we learn as we build. This is the first step.

Because customer lifetime value isn’t just a financial outcome.

It’s a systems problem. And systems can be designed.

– SigmaArc