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Refining Product-Market Fit and Scaling B2B SaaS Products

Blog Author: Rina Alexin

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Most startups don’t stall because of bad ideas—they stall because they stop refining their product-market fit and what works.

Everyone’s chasing the next AI feature or untapped market. Rachel Owens offers a rare voice of clarity in this space. She’s a seasoned product executive with a track record of scaling AI and workflow automation platforms from $1M to $10M in under a year. And in her recent interview on Productside Stories, she broke down what it really takes to scale a B2B SaaS product without losing focus.

 

Here’s what we learned about the difference between finding and refining product-market fit—and how to align your teams, avoid hype-driven strategy, and unlock real growth.

From Public Sports Complexes to SaaS: A PM Origin Story Like No Other

Before leading go-to-market strategy at B2B SaaS startups, Rachel helped launch Aviator, a $50M sports complex built on a decommissioned New York City airport. From understanding community needs across the five boroughs to designing the physical space, choosing technologies, and planning operations, her job was to build and deliver a complex system that worked for real people.

 

“That was my first real product role—even if I didn’t have the title,” she told us. “It was all about understanding customer needs and delivering something that solved a real problem.”

Rachel eventually launched her own IoT startup, worked in health tech and long-term care, and made the leap to AI-powered B2B SaaS. Her throughline? Every step has been about diagnosing real pain points—and solving them in scalable, repeatable ways.

 

Takeaway: Great product managers aren’t just builders. They’re problem-solvers. And those skills are transferable across industries.

Why Product-Market Fit Isn’t a One-and-Done

Too many teams celebrate early revenue like it’s the final boss of product strategy. But Rachel sees things differently.

 

“Companies assume that revenue equals product-market fit. But if you plateau at $1M ARR and can’t scale beyond early adopters—you don’t have product-market fit. You have early traction.”

You might need to refine PMF if:

  • Sales stall or rely too heavily on a few early evangelists
  • Customers don’t understand the core value without handholding
  • The product only fits a narrow, unscalable use case
  • Churn creeps up due to weak engagement or activation

 

Takeaway: Product-market fit isn’t just something you find. It’s something you sharpen. Especially if you want to scale.

The Real Work: How to Refine Product-Market Fit for Growth

1. Zoom Out from the Use Case. Zero In on the Problem.

Rachel’s team once built an onboarding automation tool for HR teams—great for enterprises hiring hundreds at a time. But the market turned out to be smaller than they thought.

 

That’s when they asked: What else could this product solve?

Turns out, the same automation flows applied to:

  • Employee transitions and promotions
  • Tech stack migrations
  • Compliance tracking and training

 

“Scaling isn’t always about finding new customers. Sometimes, it’s about solving more problems for the ones you already have.”

Takeaway: Don’t fixate on one persona or use case. Obsess over the pain—and where else it shows up

 

2. Align Product, Sales, and Marketing (or Stay Stuck)

When product teams operate in silos, even great features can fall flat. That’s why Rachel insists on cross-functional collaboration—early and often.

 

“Your job isn’t just to build the product. It’s to help sales and marketing tell the story.”

Her playbook for alignment:

  • Sit in on sales calls to hear objections firsthand
  • Co-create messaging that speaks in the customer’s voice, not just industry buzzwords
  • Collaborate on case studies and sales collateral that highlight real pain, not just features

 

Takeaway: If your go-to-market team doesn’t understand your product’s value, your customer won’t either.

 

3. Expand Adjacent, Not Everywhere

New markets are exciting—but they’re also expensive. Instead of chasing shiny objects, Rachel recommends expanding adjacently, where you already have traction and insight.

 

Her 3-step framework:

  1. Identify overlaps. Ask your users where else they need help. Listen for “hacks” or unexpected use cases.
  2. Test before you scale. Landing pages, concierge MVPs, or just conversations can validate direction before code.
  3. Tweak instead of overbuilding. Sometimes changing field names or workflows is all it takes to unlock a new segment.

 

Takeaway: Real growth often comes from lateral moves, not moonshots.

AI Is Not a Strategy—It’s a Tool

Rachel has seen the AI hype cycle before—and warns against letting tech lead the way.

 

“AI is powerful. But adding it for the sake of it leads to cost bloat, complexity, and poor product fit.”

Her advice for using AI wisely:

  • Start with the pain. AI should solve a clear bottleneck—not just boost your demo.
  • Focus on augmentation. Enhance user capabilities, don’t try to replace them.
  • Audit what you already use. Many teams are already using AI and ML—chatbots, analytics, automation—but failing to talk about it.

 

Takeaway: Use AI to do more of what’s already working. Not as a gimmick to chase a market that doesn’t exist.

Scaling Is a Team Sport—But Product Leads the Playbook

Rachel prioritizes building systems. And that includes tight alignment with sales, marketing, customer success, and leadership.

 

“At some companies, I went on every major sales call. Because product isn’t just about what you ship. It’s about how that product succeeds in the world.”

Whether it’s writing fake press releases, testing new markets through conversation, or refining workflows to serve new use cases, Rachel’s approach is all about making product strategy actionable.

 

Handling Data Challenges & the AI Revolution

AI is at the forefront of nearly every product discussion today—but as Anne points out, many companies misunderstand its role.

 

“Often, when clients say they want AI, they actually need better data,” she says. “We hear, ‘We want AI to do X,’ but when we investigate, they don’t actually need AI for that.”

 

She highlights two major data challenges companies face:

  1. Messy Data – Data isn’t clean or structured, making AI adoption difficult.
  2. Zero Data – Companies entering new markets don’t have historical data to analyze.

 

For messy data, Anne’s team helps clients clean and structure their datasets to improve decision-making. For companies lacking data, agencies like Razorfish leverage third-party datasets (e.g., through partners like Epsilon) to bridge the gap.

 

Advice for PMs Considering an Agency Career

For product managers considering a shift to agency work, Anne offers a few key insights:

  • Expect variety: You’ll work on different industries, challenges, and business models.
  • Be adaptable: Client priorities shift fast—you have to pivot quickly.
  • Develop strong communication skills: You’ll need to convey product ideas clearly to stakeholders who might not speak “product.”
  • Think fast, but think smart: Agencies don’t have the luxury of long timelines, but good decisions still require rigorous thinking.

 

“Product at an agency is exciting because you’re constantly being challenged,” Anne says. “But it’s important to know that product work isn’t always glamorous. The day-to-day can be messy and complex—but that’s where the magic happens.”

Scaling Smarter with Product-Market Fit

Rachel’s playbook for scaling B2B SaaS products is a blueprint for today’s product leaders—clarify your value, align your teams, and refine relentlessly. Whether you’re navigating early traction, expanding into adjacent markets, or integrating AI with purpose, the path to sustainable growth starts with better product strategy.

 

What’s been your biggest challenge in refining product-market fit? Share your thoughts in the comments or connect with us on LinkedIn.