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It is rare to see a career trajectory that moves from Venture Capital to product management, yet this unique path offers a distinct advantage in understanding how successful companies are built. Julia Schottenstein, now a product leader at DBT Labs, made this transition after identifying DBT not just as a tool, but as a movement that was fundamentally changing the data landscape. Her experience spans both sides of the table—evaluating startups as an investor at NEA and building one of the most significant data platforms of the last decade.
The journey of DBT Labs—from a consulting firm solving manual data problems to the industry standard for analytics engineering—offers critical lessons in community building, strategic acquisitions, and product philosophy. Whether you are a founder navigating the complexities of M&A or a product manager looking to refine your pricing strategy, the insights derived from DBT’s growth provide a blueprint for building enduring value in technical markets.
Key Takeaways
- M&A Strategy: The most effective way to attract an acquirer is to "inflict pain" on them strategically while maintaining a friendly, open relationship.
- The "Worse is Better" Mindset: Shipping imperfect products allows for faster learning; technical debt is often a sign of success and usage ("a champagne problem").
- Value Creation over Capture: Successful platforms often charge a fraction of the value they create, prioritizing long-term ecosystem health over short-term revenue.
- The Consulting Advantage: DBT spent two years manually solving customer problems as a consultancy before scaling their software, ensuring deep product-market fit.
- Investor Frameworks for Product: Evaluating product decisions through the lens of People, Market, Product, and Distribution can clarify strategic direction.
Mastering the Art of M&A
Mergers and acquisitions are often viewed as exit strategies, but successful founders view them as a component of strategic optionality—creating "Plan Bs." While the primary goal of any founder should be to build an enduring, independent company, the reality of market dynamics often requires alternative paths. The most leverage in an M&A negotiation comes from having a viable path to independence.
The "Inflict Pain" Strategy
For startups looking to get noticed by incumbents, passivity is not an option. For any given startup, there are typically only two or three strategic buyers who will view the technology as essential. To capture their attention, a startup must demonstrate that they are indispensable—or a threat.
m&a is always about creating plan BS... I would figure out the area that you bring a competitive advantage and I would inflict pain on that potential buyer make it impossible for them to not notice you because that's when they're going to have their ears perk up.
However, this aggression must be balanced with diplomacy. A common mistake founders make is taking too competitive a stance, shutting down conversations with potential acquirers prematurely. The goal is to inflict pain via product superiority and market presence while simultaneously keeping the relationship open and friendly. This approach was exemplified by DBT’s acquisition of Transform. Transform competed aggressively with DBT’s semantic layer ambitions, proving their technical superiority, yet positioned themselves as partners within the ecosystem. This duality made the eventual acquisition natural rather than hostile.
Navigating Strategic Alternatives
In challenging economic climates, the stigma around seeking a buyer has lessened. If a company is running low on runway, transparency is often the best policy. Rather than obfuscating the situation to create artificial demand, founders in "Hail Mary" situations should be direct with corporate development teams. The focus should be on the team and the technology assets, as acquirers are often looking to solve specific resource or technical gaps.
Decoding the Success of DBT Labs
DBT Labs stands as a rare example of a tool that became a default standard in the modern data stack. Their rise was not accidental but the result of specific structural choices and market timing.
Power Through Simplicity
When DBT launched, it faced skepticism for being "just a SQL templating tool." However, this simplicity was its core innovation. By allowing anyone who knew SQL to perform data transformation workflows—tasks previously reserved for specialized data engineers—DBT democratized data engineering. They empowered analysts to own the full data lifecycle, creating a new role now known as the "Analytics Engineer."
The Consulting Roots
Before becoming a software giant, the team operated as Fishtown Analytics, a consultancy. For nearly two years, they solved data problems manually for clients. This period was crucial for product-market fit. Every time the consultants encountered friction or repetitive tasks, they built software to solve it. This meant the product was matured by heavy, practical daily usage before it ever needed to scale as a standalone SaaS offering.
The Open Source Flywheel
A commitment to open source was the engine of DBT's distribution. The low barrier to entry allowed the tool to spread horizontally across organizations without sales intervention. This created a network effect: as more companies adopted the standard, more partners built integrations for it, which in turn attracted more companies.
Product Philosophy: Worse is Better
Perfectionism is often the enemy of effective product management. In the early stages of a feature or product, shipping a "worse" version—one that is simple, naive, but functional—is often superior to delaying launch for a sophisticated architecture.
Tech debt is a champagne problem... we would be so lucky to have tech debt because that means people are using the product.
A prime example of this philosophy was the initial DBT Cloud scheduler. It was built as a simple loop over a jobs table—an unsophisticated engineering solution. However, it worked well enough to support the product while it gained its first customers. It was only after scaling to thousands of companies and millions of runs that the team rebuilt it into a distributed system. Had they over-engineered the scheduler at launch, they would have wasted resources on a problem they did not yet have.
Pricing and Value Dynamics
One of the most complex challenges for open-core companies is determining what to give away and what to monetize. The philosophy at DBT Labs centers on valuing creation over capture.
Open Source vs. Proprietary
The distinction between the open-source and commercial offering is drawn around the concept of "state." The open-source core handles the transformation logic—the "guts" of the business logic. The commercial cloud offering handles stateful interactions, collaboration, and enterprise-grade workflows. This ensures that the ecosystem remains open and standardized while the company monetizes the efficiency and collaboration layers.
Willingness to Pay
Discussions regarding willingness to pay should ideally happen before a product is built, not during the sales cycle. In a zero-interest rate environment, many startups ignored this, optimizing for user growth over revenue. Today, understanding price elasticity is critical. A healthy pricing model often captures only a small fraction of the total value created for the customer. For instance, while DBT might generate 20-35% of the value of a cloud data warehouse, it deliberately charges a fraction of that cost, ensuring the product remains an obvious high-value investment for the customer.
Applying Investor Frameworks to Product
Transitioning from venture capital to product management requires a shift in focus, but the evaluation frameworks remain relevant. When assessing new product opportunities or career moves, the same four pillars used to evaluate startups can be applied:
- People: Do you trust the leadership? Is there a unique combination of vision and attention to detail?
- Market: Is the market growing or chaotic? Chaos creates opportunities for new entrants to establish order.
- Product: Is there a genuine "spark" or emotional reaction from users? Great products generate chatter and evangelism.
- Distribution: Does the product have a competitive advantage in how it gets to market (e.g., an open-source ecosystem or a unique sales channel)?
Additionally, product leaders can benefit from the "portfolio approach" used by VCs. While not every feature or initiative will succeed, product teams should take calculated risks on bets that have uncapped upside potential, effectively looking for power-law returns within their own roadmap.
Conclusion
The trajectory of DBT Labs illustrates that category-defining companies are rarely built on technology alone. They are built on a deep understanding of user pain points, often discovered through manual service work, and amplified by a distribution model that aligns with how users want to work. Whether through "inflicting pain" to catalyze M&A conversations or embracing technical debt to accelerate learning, the common thread is a bias toward action and a focus on long-term value creation. For founders and product leaders alike, the goal remains the same: build something that users cannot help but talk about, and ensure the business model captures a fair share of that immense value.
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