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CPQ Is Becoming the Revenue Engine of Modern B2B

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February 12, 2026

Lessons from ServiceNow on Configuration, AI, and the Future of Self-Service

For years, CPQ (Configure, Price, Quote) has lived in the shadows of B2B commerce conversations.

It’s been labeled “middle office.”

It’s been called operational plumbing.

It’s rarely described as transformative.

But in Episode 157 of The Hard Truth About B2B E-Commerce, Matthew Asher, formerly Senior Program Manager of CPQ at ServiceNow, offered a perspective that stood out:

CPQ isn’t back-office mechanics. It’s the revenue engine.

And it’s evolving fast.

What CPQ Actually Does (And Why It Matters More Than Ever)

At its core, CPQ does exactly what the acronym says:

  • Configure complex products
  • Price them correctly
  • Generate quotes that move deals forward

On the surface, it sounds simple. In practice, it’s far more complex.

In B2B environments, configuration can mean anything from conveyor systems to sheds with dozens of structural options. It can involve sizing power generators to square footage, designing playground systems with spatial rules, or configuring CNC machines with thousands of possible combinations.

CPQ sits between the front office (CRM, sales) and the back office (ERP, billing, fulfillment). It ensures that what’s sold is valid, priced correctly, and executable downstream.

But historically, CPQ has had a problem. It was built for sales reps — not buyers. That’s changing today.

The Shift: From SKU Thinking to Guided Selling

One of the biggest mindset shifts Matthew highlighted is this:

Most manufacturers think in SKUs and models. Buyers think in outcomes.

Sales reps might know the model “XYZ-123.” Customers don’t.

Modern CPQ platforms are moving toward guided configuration. They ask characteristic-based questions instead of requiring technical knowledge.

Think about configuring a bike:

  • How tall is the rider?
  • What terrain will they ride on?
  • What surfaces?
  • What weight range?

From those answers, the system determines the correct product type.

This shift from model-first to outcome-first is foundational. It’s what makes true self-service possible.

The Self-Service Gap in B2B

We talk a lot about self-service in B2B, but adoption is far from universal. Many manufacturers hesitate to embrace digital configuration, convinced their products are too complex, their sales processes too ingrained, their ERP systems too central, or that the disruption required would be too great.

But as Matthew pointed out, that resistance creates opportunity. If a procurement manager can configure and estimate a CNC machine independently at one manufacturer but not another, guess where they’ll start the buying process?

Self-service doesn’t eliminate sales. It accelerates qualification.

Buyers increasingly want to:

  • Explore configurations independently
  • Estimate pricing before talking to sales
  • Validate requirements internally
  • Reduce friction in early research stages

The companies enabling it win earlier in the buying cycle.

AI in CPQ: Beyond the Hype

AI in B2B commerce is everywhere. But in CPQ, it’s becoming practical.

Here are three applications:

1. Learning From Prior Configurations

Historical configuration data can be loaded into models to recommend:

  • Likely add-ons
  • Common combinations
  • Suggested configurations
  • Prior selections by similar buyers

For large enterprise buyers — like cruise lines ordering equipment for 57 kitchens — this matters. They want to search past configurations and replicate or modify them conversationally.

The beautiful part is that it’s not science fiction. It’s already available today.

2. Conversational Quoting

Imagine a sales rep saying:

“Quote XYZ Company the same configuration we did for ABC Company last week, but add feature CDF.”

That conversational layer is emerging quickly.

AI agents will increasingly handle:

  • Quote replication
  • Minor modifications
  • Rule interpretation
  • Guided adjustments

The time to generate complex quotes will compress dramatically.

3. AI-Assisted Rule Management

Behind every CPQ implementation are thousands of rules.

AI can assist administrators by:

  • Writing rule logic
  • Identifying conflicts
  • Suggesting improvements
  • Analyzing performance patterns

This is critical. Configuration complexity doesn’t disappear, but maintaining it becomes smarter.

The 3D and Visual Configuration Layer

Another area gaining traction today is visual configuration.

We discussed examples ranging from golf cars with rotating 3D views and sheds with multiple structural options to playgrounds governed by spatial design logic and even full data center layouts.

There’s a spectrum here:

  • “Pretty” visual overlays (retail-style experiences)
  • Engineering-grade CAD integrations
  • Spatial rule enforcement

Not every manufacturer needs high-fidelity visuals in phase one. But visual validation, especially in complex or spatial products, reduces error and increases confidence.

The key lesson:

Don’t over-engineer v1. Visuals can evolve in iteration two.

The Implementation Trap: Stop Trying to Eat the Elephant in One Bite

One of the strongest themes in our conversation was implementation discipline.

Too many B2B organizations attempt massive, multi-year, multi-million dollar programs. That approach is increasingly hard to justify, especially in uncertain economic environments.

Matthew reframed MVP in a way I really like:

“Why the hell would I want a minimal viable product? … It’s a maximum value product.”

Instead of launching everything at once, start with:

  • One product line
  • One high-volume configuration
  • One external channel
  • Guided selling first

A focused 3–6 month implementation that drives measurable revenue is far easier to justify internally than a 16-month transformation roadmap.

Especially when you’re asking a CFO to fund it.

As Matthew put it bluntly:

“You can't eat an elephant in one bite.”

The Hard Part: Cultural Change

Perhaps the most important takeaway wasn’t technical — it was cultural. CPQ directly impacts revenue, and that naturally makes executives cautious. When you’re operating that close to the company’s financial engine, requirements discipline, scope clarity, consistent communication, and visible progress are essential. 

As Matthew put it, “If Santa Claus isn't gonna show up on Christmas Eve, I better not find out about it a week before.” In other words, transparency and sprint-based visibility aren’t just project management best practices; they’re how you reduce risk and maintain trust at the leadership level.

ServiceNow + Logik.ai: The Front Office Expansion

With ServiceNow acquiring Logik.ai, CPQ becomes part of a broader front-office strategy.

ServiceNow built its dominance around IT workflows, field service, and back-office automation. That foundation gave the company deep credibility in operational execution. The expansion into CRM, sales, and order management — now powered by a high-speed configuration engine — extends that strength into the revenue side of the business.

By connecting CRM, CPQ, workflow automation, AI capabilities, and external commerce platforms like Shopify, BigCommerce, and Adobe, the opportunity becomes much larger than a standalone quoting tool. It becomes a unified system that connects the front office to fulfillment. That end-to-end model is where the broader platform strategy is heading next.

Final Thought: CPQ Isn’t “Sexy.” But It’s Strategic.

CPQ might not grab headlines the way AI agents or immersive commerce do.

But if B2B organizations want:

  • Scalable self-service
  • Faster quoting cycles
  • Reduced sales friction
  • Accurate pricing
  • Channel consistency
  • AI-powered configuration

They can’t treat CPQ as back-office tooling. It’s the connective tissue of modern revenue systems.

And as this episode makes clear, the companies that rethink configuration as a guided, intelligent, experience-first layer — not just a quoting utility — will win the market, unlike those who are still anchored in SKU-first thinking.

If you're exploring how CPQ, guided selling, and AI-powered configuration fit into your broader commerce roadmap, Zaelab works with B2B organizations navigating exactly these shifts — from phased rollout strategies to unified front-office architectures. Let’s talk.

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