Valuing Unicorns: The Challenges of Pricing Startups with No Profits
- Editor
- Oct 2
- 4 min read
by KarNivesh | 02 October, 2025
The startup ecosystem has created one of the biggest puzzles in modern finance: how can companies worth thousands of crores still run at heavy losses year after year? Traditional financial wisdom tells us that value should come from profits, yet the world’s most famous startups—called unicorns—often show the opposite.
Take OpenAI, for example. The company is valued at an astonishing ₹25,11,000 crores (₹300 billion), even though it expects losses of nearly ₹6,700 crores in 2025. This paradox shows how modern investors look beyond immediate profits and place bets on future potential.
In this blog, we will explore the challenges of valuing unicorns, the methods used, real-world examples, and what this means for investors and entrepreneurs.
What Exactly Is a Unicorn Startup?
A unicorn is a privately held startup valued at over ₹835 crores (₹1 billion). The term, first used in 2013, highlighted the rarity of such companies. Today, unicorns are far more common—over 1,200 exist globally, with nearly 90% still unprofitable.
The typical unicorn raises around ₹2,300 crores before crossing the billion-dollar mark. They usually operate in technology-driven, scalable markets such as fintech, AI, e-commerce, or clean energy. India alone has 71 unicorns, worth more than ₹15,50,000 crores combined.
Why Valuing Unicorns Is So Difficult
Valuing traditional companies is easier because we have historical data—profits, revenues, cash flows—that help in financial modeling. Unicorns, however, pose unique challenges:
Lack of Historical Data – Startups don’t have long records of performance. Valuers rely on business plans and projections that are often overly optimistic.
Dependence on Key People – Many startups are built around a few individuals (like founders or engineers). If they leave, company value may fall drastically.
Unproven Business Models – Subscription apps, platform companies, or network-based startups look attractive early on, but their long-term profitability remains uncertain.
Traditional Valuation Methods and Their Limits
The most popular valuation tool, Discounted Cash Flow (DCF), doesn’t work well for unprofitable startups. DCF needs predictable future cash flows, but most unicorns reinvest heavily in growth, delaying profits for years.
Instead, investors rely on market-based approaches:
Comparable Company Analysis (CCA): Looks at listed peers using revenue multiples (like EV/Sales).
Precedent Transactions: Studies prices paid in similar startup acquisitions.
These methods reflect investor sentiment more than company fundamentals.
Alternative Valuation Approaches
Since traditional models fall short, investors use startup-specific methods:
The Berkus Method – Assigns values to five factors like idea quality, prototype, team, relationships, and readiness. Useful for very early-stage startups.
Venture Capital Method – Focuses on expected exit value (IPO or acquisition) and discounts it at high rates (30–70%).
Risk Factor Summation – Adjusts valuations by adding or subtracting value for risks like competition, regulation, or management weaknesses.
Learning from Famous Unicorns
Amazon: Took nine years to show profits. Even after turning profitable in 2003, it kept reinvesting heavily, eventually building AWS—its most profitable arm.
Tesla: Struggled for 17 years before consistent profitability in 2013. It overcame multiple near-bankruptcies and skepticism, yet became one of the most valuable carmakers.
OpenAI: Currently the best example of “valuation without profit.” With revenues of ₹1,00,400 crores (₹12 billion) in 2025 but massive costs, its worth depends on future dominance in AI.
These stories prove that losses don’t always mean failure—sometimes patience pays off big.
Is There a Startup Bubble in 2025?
The current wave of unicorn valuations has worrying signs:
Over-concentration in AI: More than 50% of venture capital in early 2025 flowed into AI startups.
Rising Costs: Salaries for AI engineers and computing costs are skyrocketing, hurting sustainability.
Dot-com Parallels: Just like the 2000s internet bubble, companies are valued on hype and growth metrics rather than profitability.
For instance, big tech players like Microsoft, Google, and Meta have invested nearly ₹46,85,000 crores ($560 billion) in AI infrastructure in just two years but generated only ₹2,92,950 crores ($35 billion) in AI revenues.
How Investors Manage the Risks
To navigate these uncertainties, investors focus on:
User engagement metrics like churn rate and customer lifetime value.
Market size and scalability, which decide long-term potential.
Alternative financing like venture debt and revenue-based financing to reduce dilution.
Smaller funds like micro-VCs and impact funds also play growing roles, especially outside mainstream AI hype.
The Road Ahead for Startup Valuation
The future of startup valuation will likely see:
Market corrections that filter out weaker players.
Regulatory interventions in areas like privacy, safety, and job impact.
Longer timelines for adoption, meaning patient capital will be rewarded.
Ultimately, while valuations may seem inflated, technology continues to create real value. Just as Amazon and Tesla proved doubters wrong, today’s unicorns may shape tomorrow’s economy.
Key Takeaways
Unicorns are startups valued over ₹835 crores, even if unprofitable.
Traditional valuation tools like DCF fail because startups prioritize growth, not profits.
Alternative methods such as the Berkus and VC methods are used to capture startup potential.
Real-world examples show that early losses don’t prevent long-term success.
There are risks of a valuation bubble, especially in AI, but patient and careful investing can still yield big rewards.
For entrepreneurs, the lesson is clear: losses don’t mean failure, but financial discipline and a clear strategy are essential. For investors, the challenge is balancing hype with fundamentals, identifying companies with both potential and a realistic path to profitability.
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