Negative Gross Margins ⎟ The Canary in the Market Froth Mine

August 25, 2025

We explore why negative gross margins signal market froth, from scooters to AI. How capital allocators enable value-destructive companies during bubbles.

Patric Hellermann

Shub Bhattacharya

Negative Gross Margins ⎟ The Canary in the Market Froth Mine

This Week On Practical Nerds - tl;dr

Negative gross margins as a froth indicator in venture markets

The fundamental economics of gross margin and pricing power

Why AI companies struggle with unit economics despite hockey stick growth

How capital allocators enable value-destructive business models

The difference between temporary pricing strategies and structural problems

Window dressing techniques that hide true gross margin performance

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Negative gross margins as a froth indicator in venture markets

Last week, Shub brought up something that's been nagging at both of us: we keep seeing this pattern in our deal flow that feels like a reliable early warning system.

"You know what I think is a fairly predictive indicator of market froth?" I asked Shub. Without missing a beat, he said "negative gross margins."

We've been tracking this phenomenon across different sectors and time periods - from the scooter craze of 2017-2020 to today's AI companies. The pattern keeps repeating: when businesses consistently sell products for less than it costs to produce them while still attracting massive investment rounds, something fundamental breaks down in market dynamics.

Our thesis connects market froth directly to capital allocation behavior. During frothy periods, institutional investors face pressure to deploy excess capital. This creates an environment where even economically questionable business models attract significant funding. The negative gross margin becomes a symptom of this broader market condition rather than a rational business strategy.

The cyclical nature becomes evident when examining specific examples. The scooter craze of 2017-2020 exemplified this pattern perfectly. Companies like Lime and Bird operated with unit economics that were fundamentally broken from day one. Yet billions flowed into the sector because investors remained optimistic about eventual market consolidation and pricing power that never materialized.

Our framework suggests that when multiple companies in a sector operate with negative gross margins while still attracting significant investment, market participants should pay attention to broader conditions. This doesn't guarantee every such company will fail, but it suggests the market might be pricing in overly optimistic outcomes about future pricing power and efficiency gains.

The construction and AECS sector provides particularly stark examples. When startups in these traditionally margin-sensitive industries propose negative gross margin strategies, it often signals disconnect from industry realities. Construction customers operate on thin margins themselves and resist arbitrary price increases that could dismantle their own economic assumptions.

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The fundamental economics of gross margin and pricing power

Shub's perspective on gross margin centers on pricing power as the fundamental driver. His analysis suggests that gross margin reflects whether customers value what you deliver enough to pay meaningfully above your direct costs. This creates a clear test for any business model.

The definition we find compelling connects gross margin to customer value perception. Gross margin answers whether customers find value in your offering. Contribution margin tests whether you can distribute that value efficiently. EBITDA eventually determines whether you can build scale effects into the entire business model.

Different business models naturally produce different gross margin structures. Marketplace businesses typically see anything from 1% for pure intermediaries to 20-30% for more managed experiences. The variation depends heavily on how much value-add the marketplace provides beyond simple transaction facilitation.

Software as a Service businesses enjoy much higher gross margins, typically 80-90%, because marginal serving costs remain relatively low. Main costs include cloud hosting, allocated engineering resources, and integration work with enterprise clients. The scalability advantage becomes obvious when you compare this to physical product businesses.

Outcome-based service businesses require more complex gross margin calculations. Person-hours, equipment depreciation, materials, and project-specific software all need accurate allocation. The key insight from their analysis is ensuring you understand the true cost of delivering each project or outcome.

The pricing power lens helps explain why negative gross margins signal deeper problems. When customers won't pay enough to cover direct costs, it suggests either the market doesn't value the solution sufficiently, or competitive dynamics have pushed pricing below sustainable levels. Both scenarios indicate potential market structure problems.

Construction technology companies face particular challenges here. The industry operates on established margin expectations. When startups propose models that require ongoing subsidies to maintain customer relationships, it often signals misunderstanding of how construction businesses actually operate and make purchasing decisions.

Why AI companies struggle with unit economics despite hockey stick growth

The AI sector provides perhaps the most striking contemporary example of the negative gross margin phenomenon that we observe. Our research into specific companies reveals concerning patterns despite impressive top-line growth numbers.

Anthropic reportedly generates $4 billion in annualized revenue, with $1.2 billion coming from just two customers: Cursor and GitHub Copilot. The concentration risk aside, the more revealing story emerges when examining Cursor's underlying economics.

According to our analysis, Cursor pays approximately $650 million annually to Anthropic while generating roughly $500 million in annualized revenue. This creates a negative 30% gross margin before considering additional costs like cloud hosting, customer support, or sales expenses. The math becomes stark when you realize every additional dollar of revenue actually destroys $1.30 in value at the gross margin level.

This dynamic illustrates a broader challenge facing AI application companies. Many successful AI applications function essentially as software wrappers around foundational models provided by Anthropic, OpenAI, or Google. These companies excel at building user interfaces and specialized functionality, but their primary cost structure revolves around API calls to underlying AI models.

The scalability challenge becomes apparent. As these companies grow and serve more customers, their costs to foundational model providers grow proportionally. Without the ability to charge customers significantly more than what they pay for underlying AI capabilities, they face structural gross margin pressure that intensifies with growth.

We challenge the common refrain that "models will get more efficient." Our observation suggests that while models do become more efficient over time, customer expectations evolve simultaneously. Users don't accept outdated models just because they consume less power. The industry operates in an arms race where everyone demands access to the most powerful, most current capabilities.

We note that this pattern extends beyond Cursor. Our research indicates negative gross margins appear across multiple AI companies, including Perplexity and others. The industry publications we follow, particularly The Information, have documented this phenomenon across several high-profile companies.

This creates what we describe as "scaling yourself into hell." Every additional customer and every additional dollar of revenue actually makes the business economics worse, not better. The traditional venture playbook of growing into profitability breaks down when the fundamental unit economics work against you.

How capital allocators enable value-destructive business models

From the capital allocation perspective, we frame negative gross margin businesses as representing a fundamental breakdown in the investment process. The basic premise of capital allocation assumes entrepreneurs can generate higher returns than investors could achieve independently.

The absurdity becomes clear when framed properly. An entrepreneur approaches an investor saying essentially: "Give your capital, put it through the business machine, and receive back less than you provided." This value destruction happens before considering any fixed costs or operating expenses. At the gross margin level, the business already destroys capital.

We use the metaphor of a kitchen machine that literally shreds dollar bills, producing fewer dollars than you input. Then you layer all fixed costs on top of this fundamental value destruction. From pure capital allocation logic, this makes sense only if you believe in eventual pricing power that will materialize at scale.

This dynamic emerges during periods when capital allocators face pressure to deploy money quickly while earning management fees on assets under management. When interest rates remain low and traditional fixed income yields look unattractive, money flows toward alternative investments even when fundamental economics don't support the valuations.

The cycle becomes self-reinforcing during frothy periods. Institutional investors accumulate large amounts of capital needing deployment. They allocate to venture funds. Venture funds face pressure to invest their capital within certain timeframes to generate returns and raise subsequent funds. This creates artificial demand for investment opportunities that might not meet traditional return thresholds.

The "land grab" mentality becomes pervasive during these periods. Companies argue they need to capture market share quickly, even at the expense of unit economics. The assumption remains that once they achieve scale and market position, they'll gain the pricing power needed to become profitable.

But our analysis reveals a crucial flaw in this logic. The very fact that you need negative gross margins to compete often suggests the market structure works against sustainable pricing power. If customers can easily switch to competitors offering similar subsidies, the future pricing power never materializes.

Construction technology investors face particular challenges because industry customers understand supplier economics well. When a construction tech startup proposes negative margin pricing to win market share, sophisticated customers often question the supplier's long-term viability rather than celebrating the discount.

The difference between temporary pricing strategies and structural problems

Shub and I make important distinctions between legitimate pricing strategies and structural business model problems. Not all low-margin approaches signal market froth or poor business fundamentals.

The elevator industry provides our go-to example of strategic loss leaders working properly. Major elevator companies often install elevators at minimal margins but require customers to sign multi-year maintenance contracts that generate highly profitable recurring revenue. The installation creates an installed base that produces predictable, high-margin cash flows.

Similar patterns appear in printers and ink cartridges, where hardware gets sold cheaply to drive sales of profitable consumables. The crucial difference remains that these companies maintain positive blended gross margins across their complete product portfolio. They redistribute margin across different offerings rather than destroying value overall.

Our analysis distinguishes this from true negative gross margin businesses where no clear path to profitability exists even when considering the full customer relationship. Quick commerce exemplifies this challenge, where unit economics remained broken even accounting for customer lifetime value and repeat purchase behavior.

Construction and B2B markets present additional complications for negative margin strategies. Unlike consumer purchases where price increases might cause minor inconvenience, B2B price changes can fundamentally alter customer P&Ls and operational assumptions. Industrial customers plan their businesses around stable supplier relationships and predictable cost structures.

This explains why land grab strategies that succeed in consumer markets often fail in industrial contexts. B2B customers typically demonstrate more sophistication about total cost of ownership and more resistance to arbitrary price changes. They also maintain longer planning horizons and face more complex switching costs that work in both directions.

We acknowledge that temporary negative margins during market shocks or transition periods can make strategic sense. Maintaining customer relationships through difficult periods to avoid rebuilding from scratch later might justify temporary margin sacrifices. But this differs fundamentally from building your entire business model around ongoing value destruction.

Our observation suggests that legitimate strategic pricing should have clear timeframes and specific triggers for returning to positive margins. When companies can't articulate these conditions clearly, it often signals they're hoping market conditions will somehow solve their fundamental economics problems.

Window dressing techniques that hide true gross margin performance

We have observed several common techniques companies employ to make their gross margins appear healthier than underlying reality. These patterns emerge repeatedly in our deal flow and due diligence processes.

The most straightforward approach involves redefining what counts as revenue. Instead of reporting true top-line revenue, companies might report "net revenue" after deducting various costs. This mathematical manipulation allows them to show higher gross margin percentages on a smaller revenue base that doesn't reflect actual business scale.

A managed marketplace might call total transaction volume "gross revenue" and their take rate "net revenue," then calculate margins only on the net figure. While this might be technically accurate, it obscures the actual economics of customer acquisition and transaction facilitation that determine business viability.

Companies frequently move legitimate direct costs below the gross margin line. Customer service costs in software businesses represent a common example. Early-stage companies might argue these costs don't scale directly with revenue, but sophisticated investors recognize that customer support requirements typically grow with customer base and usage.

Another technique involves allocating shared resources inappropriately. Engineering talent that directly supports revenue generation might get categorized as general operating expense rather than cost of goods sold. Integration costs with enterprise customers might get buried in sales and marketing rather than properly allocated to the revenue they support.

We have seen companies avoid including payment processing fees, logistics costs, or quality control expenses in their gross margin calculations. These costs directly relate to revenue delivery but get repositioned as operational expenses to improve apparent unit economics.

We note that these techniques might work during seed or Series A fundraising when absolute numbers remain small enough that misallocation doesn't materially impact overall business analysis. But sophisticated Series C investors and beyond typically catch these discrepancies because the absolute dollar amounts become significant enough to matter.

The fundamental problem with window dressing remains that entrepreneurs primarily fool themselves. When you invest your career and life building a business, you need accurate understanding of whether the underlying economics actually work. Raising additional funding based on misleading metrics doesn't solve fundamental business model problems.

Our advice centers on maintaining clean books and honest accounting from the beginning. Even during desperate fundraising periods, accurate gross margin calculation helps entrepreneurs understand whether they're building something sustainable or just buying time with investor capital.

The construction technology sector faces particular scrutiny here because industry customers understand supplier economics well. When a construction tech startup presents financials that don't align with industry cost structures, experienced customers often question the sustainability rather than celebrating temporary discounts.

Conclusion

Our anecdotal evidence suggests that negative gross margins serve as a reliable early warning system for market froth across venture markets. When businesses systematically destroy value at the unit level while still attracting significant investment, it signals that capital allocation has become detached from fundamental economics. The pattern repeats across cycles, from scooters in 2017-2020 to AI companies today, where impressive top-line growth masks unsustainable cost structures. For entrepreneurs, the lesson remains clear: building a business that creates value for customers while maintaining positive unit economics provides the foundation for long-term success. For investors, recognizing these patterns can help identify when market exuberance has pushed valuations beyond rational levels. The companies that survive market corrections typically have strong gross margins from the start, not promises of future efficiency gains that may never materialize. Clean accounting and honest unit economics analysis remain essential tools for navigating both frothy and rational market environments.