PVML’s Market Education Strategy: Selling Differential Privacy to People Who’ve Never Heard of It

PVML’s Market Education Strategy: Selling Differential Privacy to People Who’ve Never Heard of It

Your co-founder just finished his PhD researching a technology that solves a massive market problem. There’s just one catch: when you mention it to potential customers, they stare blankly and ask you to explain what it is. You’re not selling a better version of something familiar—you’re selling something that requires explaining an entirely new concept before you can even discuss benefits.

In a recent episode of Category Visionaries, Rina Galperin, CTO and Co-Founder of PVML, a data access platform that’s raised $8 million, shared how they approach selling differential privacy—a PhD-level technology that most buyers have never encountered—without losing prospects in technical explanations or oversimplifying to the point of meaninglessness.

The Founding Advantage That Became a Market Challenge

PVML’s origin story handed them a significant technical advantage. While Rina encountered data access limitations at Microsoft, her co-founder Shachar was completing his PhD in computer science, specializing in differential privacy. “A mathematically quantifiable definition of privacy. And yeah, that’s a thing. It actually exists,” Rina notes with the slight wonder of someone discovering an elegant solution to an impossible problem.

Differential privacy was formulated specifically to solve the challenge of unlocking analytics without compromising individual privacy. Unlike anonymization or masking—techniques most security buyers understand—differential privacy provides mathematical guarantees about privacy preservation while maintaining analytical utility.

This technological sophistication created PVML’s core differentiation. “Our unique data protection technology. So the first technology that actually helps unlock more data for analysis without altering it and without risking it,” Rina explains. But it also created a go-to-market problem: how do you sell technology that requires explaining an academic concept most buyers have never heard of?

The Education Burden in Category Creation

Most B2B sales involve some degree of education. You explain why your CRM is better than Salesforce, why your analytics platform beats Tableau, why your security solution outperforms competitors. But you’re operating within an understood category. Buyers know what CRMs, analytics platforms, and security solutions do—you’re just convincing them yours is superior.

PVML faced a different challenge. They needed to educate the market not just about their product, but about the foundational technology enabling it. This creates a multi-layered sales conversation:

First, explain what differential privacy is. Second, explain why it’s superior to existing approaches like anonymization. Third, explain how PVML implements it. Fourth, explain why PVML’s implementation is the right choice.

Each layer risks losing prospects. Explain differential privacy too technically and non-PhD buyers tune out. Oversimplify and sophisticated buyers question whether you actually understand the technology. Rush through the education to get to your product and prospects lack the foundation to understand why your approach matters.

The Strategic Decision: Where to Educate

Recognizing this education burden, PVML made a critical strategic choice about where to invest their market education efforts. They could attempt to educate the entire cybersecurity market about differential privacy, or they could focus on specific verticals where the pain point was acute and the value proposition immediately clear.

They chose the latter. “We do try to look for clients not specifically in, I mean, you mentioned events and not specifically in cyber events, but maybe branch out more to domain specific events that we’re seeing traction specifically in fintech, mobility, healthcare,” Rina shares.

This vertical-first approach solves multiple problems simultaneously. At a cybersecurity conference, PVML is one of hundreds of vendors making bold claims about novel technology. The noise level is overwhelming and buyer skepticism is high. Everyone claims their approach is revolutionary.

At a fintech conference, PVML is the data security solution that actually understands fintech’s specific challenge: needing to analyze sensitive financial data for fraud detection, risk modeling, and regulatory compliance without risking breaches or violations. The education conversation becomes concrete rather than abstract.

Instead of explaining “differential privacy enables analytics on sensitive data,” they can say “differential privacy lets you run fraud detection models on actual transaction data without risking individual customer exposure, even if your database is breached.” The technology becomes a solution to a specific, painful problem rather than an interesting academic concept.

The Positioning That Makes Education Easier

PVML’s broader positioning strategy also reduces the education burden. Rather than leading with “we use differential privacy,” they lead with the outcome: enabling instead of restricting data access.

“I would say it’s data access, but it’s enabling instead of limiting,” Rina explains. This positioning anchors the conversation in a pain point every security buyer understands: the frustrating trade-off between protection and utility.

Every company dealing with sensitive data faces this tension. Security teams want to lock everything down. Analytics teams need access to drive insights. Compliance teams demand protection. Business leaders want data-driven decisions. Traditional security solutions force an either/or choice.

By positioning as “enabling instead of limiting,” PVML frames differential privacy as the solution to this universal tension rather than an academic technology buyers need to understand. The education becomes about “here’s how we eliminate the trade-off” rather than “here’s what differential privacy means.”

This shifts the buyer’s mental model. Instead of thinking “do I understand this technology well enough to bet my career on it?” they think “if this actually eliminates the security-versus-utility trade-off, I need to understand how it works.” The motivation to learn flips from obligation to opportunity.

The Trust Problem in Novel Technology

Beyond understanding, market education faces a deeper challenge: trust. Buyers can understand what differential privacy is and still hesitate to adopt it. Novel technologies carry career risk. If you champion a well-known solution that fails, you made a reasonable bet that didn’t work out. If you champion a technology nobody has heard of and it fails, you look reckless.

This is why PVML’s focus on specific verticals matters beyond just targeted education. By building concentration in fintech, mobility, and healthcare, they create proof points. The first fintech customer takes the biggest risk. The tenth fintech customer can point to nine others who validated the approach.

Vertical concentration also enables reference selling. A healthcare CISO evaluating PVML can speak with other healthcare CISOs who’ve implemented it. They’re not just learning about differential privacy academically—they’re hearing from peers in similar situations who took the risk and succeeded.

The Ongoing Education Investment

Market education isn’t a one-time investment that eventually ends. PVML explicitly recognizes this as an ongoing go-to-market challenge. “We definitely also have some market education to do because we’re using a very unique solution for our product,” Rina notes.

This ongoing education requirement affects resource allocation. Companies selling within established categories can eventually shift marketing budget away from education toward demand generation and conversion optimization. PVML will always need to invest in education because they’re constantly reaching new buyers who haven’t heard of differential privacy.

This has implications for marketing strategy, content creation, sales enablement, and customer success. Every prospect conversation requires some level of education. Every piece of marketing content needs to balance education with value proposition. Every sales rep needs to be capable of explaining complex technology in accessible ways.

The Framework for Novel Technology GTM

PVML’s approach suggests a framework for any company selling genuinely novel technology:

Don’t try to educate everyone. Focus education efforts on verticals or segments where the pain point is acute and the value proposition is immediately concrete. Broad market education is prohibitively expensive and slow.

Lead with outcome, not technology. Position around the problem you solve, not the novel approach you use. Let buyers pull the technological explanation from you rather than pushing it on them.

Build vertical concentration for proof points. The first customer in any vertical takes maximum risk. The tenth customer has validation. Concentrate efforts to build referenceable success stories.

Accept education as ongoing investment. Budget and resource accordingly. Novel technology requires sustained education investment, not just early-stage market development.

Make technical sophistication accessible. You need to be capable of explaining your technology at PhD level and at business buyer level. Most sales will require both depending on stakeholders involved.

The Long Game

Market education is inherently a long game. PVML can’t run a three-month campaign and expect the market to suddenly understand differential privacy. They’re playing a multi-year game of gradually expanding awareness within targeted verticals while building proof points that reduce perceived risk.

For founders building genuinely novel technology, PVML’s approach offers a pragmatic path: focus your education efforts on audiences most likely to care, lead with outcomes over technology, and accept that education is an ongoing investment, not a problem you solve once.

The alternative—trying to educate the entire market at once—is how innovative companies run out of money before achieving product-market fit.