How Monad Uses Adjacent Market Success as Social Proof

How Monad Uses Adjacent Market Success as Social Proof

When you’re selling infrastructure in a new domain, the hardest question isn’t “does this work?” It’s “why should we believe this approach will work here?” Christian Almenar, CEO and Founder of Monad, found his answer by pointing to what security teams already knew was possible—just in different parts of their own companies.

In a recent episode of Category Visionaries, Christian explained how Monad’s most powerful positioning argument comes from drawing parallels to adjacent markets that have already solved similar data problems. Instead of asking security teams to believe in an unproven approach, he shows them what’s already working everywhere else in their organization.

The Comparison That Changed Everything

Christian’s core thesis for Monad emerged from observing a stark contrast between how different business functions handle data. The framing he uses is both simple and devastating in its implications.

“As a tech industry, we’ve done amazing work at understanding who’s on the other side of the screen in order to show them ads, really targeted ads, we really understand who’s on the other side and able to sell them a lot of really awesome things,” Christian explains.

Marketing teams can attribute every dollar. Product teams understand user behavior at granular levels. Sales teams have comprehensive analytics on pipeline and conversion. HR has sophisticated people analytics. All of this sophistication exists because these functions built on modern data infrastructure—warehouses, analytics platforms, machine learning capabilities.

Then Christian pivots to security: “What we kept running into is that customers really what they really struggle is like they have too many security products. They can’t really handle all the data these tools generate, yet they can’t really act on the data they generate easily the same way they act on when they get a lot of sales data or product data.”

This comparison does several things simultaneously. It makes the problem tangible by referencing capabilities everyone recognizes. It creates urgency by highlighting the gap. And it provides a roadmap by showing that the solution isn’t theoretical—it’s already proven in adjacent domains.

Why Adjacent Market Analogies Work

The power of Christian’s approach is that he’s not asking security teams to take a leap of faith. He’s asking them to acknowledge a gap they can see in their own organizations.

“It was almost striking that cybersecurity being so critical and so important for the world that it’s not Alipar with other industries,” Christian says. The word choice matters here—”striking” suggests something almost offensive about the disparity. How can the function responsible for protecting the entire business lag so far behind marketing in data sophistication?

This framing transforms the sales conversation. Instead of convincing skeptical buyers that data infrastructure could work for security, Christian is highlighting an obvious gap between what security has and what every other function already uses. The question shifts from “will this work?” to “why haven’t we done this already?”

The adjacent market success provides multiple layers of social proof. First, it proves the underlying technology works—data warehouses, analytics tools, and machine learning aren’t experimental. Second, it proves the organizational capability exists—if marketing can do sophisticated data operations, security teams can learn too. Third, it proves the ROI—these other functions invested in data infrastructure because it generated measurable value.

The Investor Pitch Version

Christian uses the same adjacent market framing to explain why investors backed Monad. “We started really incubating this company with Sequoia. In the beginning, we saw the success of the warehousing movement, south lakes of the world.”

This is pattern-matching at work. Sequoia didn’t need to believe that data infrastructure for cybersecurity was a novel invention. They needed to believe that the same transformation that happened in analytics, marketing, and sales could happen in security.

The data warehousing revolution provided a proven template. Snowflake didn’t succeed by inventing new data concepts—they succeeded by making modern data infrastructure accessible to more use cases and users. Monad’s thesis is similar: bring proven data infrastructure approaches to a domain that hasn’t adopted them yet.

When Christian explains investor excitement, he points to customer behavior: “They see the signs that customers kind of like reaching a tipping point of needing to do things differently when it comes to handling all the data these tools generate.”

The tipping point isn’t about inventing new technology. It’s about cybersecurity finally catching up to where other functions have been for years. Investors can evaluate that thesis against observable market patterns rather than speculative predictions.

How This Shapes Product Positioning

The adjacent market framing directly influences how Christian positions Monad’s product. The goal isn’t to build something entirely new—it’s to bring existing best practices to a new domain.

“Our goal basically is like, how can we uplift the industry to at least be Alipar with what people do for sales data or marketing data?” Christian explains. The target isn’t cutting-edge innovation. It’s parity with what already works elsewhere.

This positioning makes the product easier to understand and the value proposition easier to articulate. Christian isn’t asking security teams to reimagine how they work. He’s asking them to adopt approaches their marketing colleagues have used successfully for years.

The product description reflects this: “We want to empower customers to really take the most value out of the tools they currently have, be able to act on the data that those tools generate, and load it in whatever data warehouse they have, and then allow them to do more data driven workflows with them.”

Notice the references to existing infrastructure—”whatever data warehouse they have.” Monad isn’t inventing data warehousing for security. They’re enabling security teams to use the same data infrastructure the rest of the business already relies on.

The Customer Education Angle

Using adjacent market success as social proof also solves a customer education problem. When you’re introducing infrastructure to a new domain, buyers need to understand both what it does and why it matters. Those are two different educational challenges.

Christian’s approach collapses them into one. By pointing to marketing’s data sophistication, he simultaneously demonstrates what’s possible (the “what”) and why security teams should care (the “why”). Security leaders can look at their marketing colleagues’ capabilities and immediately understand both the gap and the opportunity.

This is especially powerful in Fortune 500 organizations where Christian is selling: “In the beginning, our customers are in the Fortune 500 kind of greater larger companies.” These are organizations where security teams sit in the same building as marketing teams with sophisticated attribution models and product teams with comprehensive analytics.

The adjacent market success isn’t abstract—it’s down the hall. Security leaders can walk over to their CMO and ask about their data infrastructure. They can see the ROI firsthand. They can understand the organizational capability required. The social proof is immediate and verifiable.

The Category Definition Advantage

Christian’s adjacent market framing also helps navigate the challenge of category definition. When asked about market categories, he’s refreshingly uncertain: “I will lie if I say items exactly. I know exactly where it’s still early in the physical companies also early in the industry.”

But he doesn’t need precise category definitions because he can describe the transformation by analogy: “It’s kind of like an architectural shift and a little bit of consolidation that I think is happening.”

This framing works because the audience has seen architectural shifts before. They’ve seen what happened when companies adopted data warehouses for analytics. They’ve seen how infrastructure plays enable new capabilities. The category doesn’t need a clean name—it needs a recognizable pattern.

The Underlying Principle

For founders building in emerging categories or bringing proven approaches to new domains, Christian’s strategy offers a template. Instead of asking buyers to believe in something entirely new, show them it already works somewhere they can verify.

The most powerful social proof isn’t a case study from a similar company. It’s capabilities the buyer can observe in their own organization. When Christian tells security teams they’re behind marketing in data sophistication, he’s not making an abstract argument—he’s pointing to evidence they can validate themselves.

This approach requires finding the right adjacent market. The parallel needs to be close enough that the comparison feels valid but different enough that the gap is obvious. For Monad, marketing and product analytics provided perfect reference points—similar enough data challenges, proven infrastructure solutions, but clear gaps in security adoption.

The deeper lesson is about changing the nature of the sales conversation. When you’re selling infrastructure, you’re not just selling a product—you’re selling a vision for how work should be done. Adjacent market success transforms that vision from speculative to achievable. You’re not asking buyers to imagine a better future. You’re asking them to achieve parity with what already exists.