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Welcome to another Data Driven VC “Insights” episode where we cover the most interesting startup research & reports from the past two weeks.
How SaaS Outliers Scale from $1M to $20M ARR
Kyle Poyar analyzed data from 6,525 software companies in ChartMogul’s SaaS benchmark report to uncover what separates the 3.5% of startups that grow to $20M ARR from the rest. The surprising finding: success is less about how companies start and more about how they improve over time.
Starting Points Are Similar: At $1M ARR, metrics looked alike between winners and laggards. The only difference was MoM growth (16.7% for outliers versus 8.7% for others), but even that wasn’t a clear predictor of long-term success.
Improvement Is the Real Differentiator: Top performers systematically improved key metrics. 72% raised average revenue per account, 71% increased annual plan share, and over half boosted gross and net retention by more than 10%.
Pricing and Expansion Drive Scale: Outliers raised prices aggressively, increasing ARPA by 82%, and improved NRR by roughly 10 percentage points, often by shifting to multi-product offerings.
✈️ KEY TAKEAWAYS
The SaaS startups that reach $20M ARR don’t just grow faster, they evolve better. Continuous improvements in pricing, retention, and product expansion separate enduring winners from those that stall out early.
The 2025 GTM Scorecard: What’s Working and What’s Next
Maja Voje and Kyle Poyar investigated data from 195 B2B companies to understand which go-to-market (GTM) channels drive results today, and where teams are placing bets for 2026. With most companies running around 10 channels and experiments in parallel, efficiency and focus are more critical than ever.
Top Channels by Company Size: Larger SaaS firms ($10M+ ARR) rely on conferences, SEO, and paid ads. Mid-sized teams ($1-10M ARR) lean on warm and intent-based outbound, while smaller startups (<$1M ARR) thrive through LinkedIn and strong founder brands.
Deal Size Shapes GTM Strategy: High-ticket deals ($25K+) are won through conferences and personalized events. Mid-range deals ($5-25K) mix outbound and SEO, while low-ticket deals (<$5K) depend on digital reach through paid and organic channels.
Where Budgets Are Headed Next: AI-driven GTM is on the rise. 51% plan to boost investment in AI search (AEO), and 45% in intent-based outbound. LinkedIn (31%) and founder branding (30%) remain strong for smaller teams, while AI SDRs (28%) are still early-stage.
✈️ KEY TAKEAWAYS
GTM success in 2025 blends proven fundamentals with emerging AI-driven tactics. The data shows no single winning channel, teams that adapt quickly, balance reliable performers with smart experiments, and lean into AEO and intent-based outbound are best positioned for the next wave.
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VC Valuation Gap: Europe vs. U.S.
Yoram Wijngaarde highlights a persistent valuation discount for European VC rounds compared to U.S. deals, and shows that the difference shrinks only as deals scale.
12 % Discount in Early Rounds: The analysis points out that average pre-money valuations for European Series A rounds are ~12 % lower than U.S. counterparts, suggesting geographic cost arbitrage in early stages.
Discount Narrows at >$100M Valuations: It notes the disparity shrinks significantly for unicorn or near-unicorn deals, where Europe closes the valuation gap and sometimes matches U.S. levels, highlighting scale and maturity as levellers.
Capital Remains U.S. Concentrated: Despite narrowing valuation differences, the post underscores that the number and size of U.S. deals remain substantially greater than Europe’s, implying a continued head-start advantage for U.S. founders.
✈️ KEY TAKEAWAYS
European startups still face a valuation gap versus U.S. peers, especially in early stages, but the gap shrinks at scale, making geography a fluid rather than fixed advantage for founders and VCs.
Is the Forward Deployed Engineer (FDE) on the Rise?
Pave’s latest analysis investigates whether the “Forward Deployed Engineer” role (popularized by Palantir) is becoming more common across startups. Using compensation and job title data from nearly 9,000 customers, the report tracks the emergence and growth of this hybrid technical-customer-facing position.
Rising Trend, but Still Rare: The share of companies employing Forward Deployed Engineers has increased sharply over the past two years. Yet, as of September 2025, only 1.24% of firms in Pave’s dataset list this role, showing that while interest is growing, it remains niche.
Follow-the-Leader Dynamics: The pattern suggests a “follow the leader” effect. As influential companies like OpenAI and Palantir expand their FDE teams, others are likely to follow suit to stay competitive in customer-centered engineering.
Compensation Benchmarks: Forward Deployed Engineers are compensated about 9.2% below generalist software engineers, but earn 23.7% more than customer support engineers and 16.2% more than technical account managers.
✈️ KEY TAKEAWAYS
The Forward Deployed Engineer is emerging as a distinct role bridging engineering and customer delivery. While adoption is still limited, rising demand from AI-driven and enterprise-focused startups suggests this role could become a fixture in modern product organizations by 2026.
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How Big is the AI Spend?
Recent analysis places AI infrastructure spending among the largest economic mobilizations in U.S. history. Although still far from the scale of the world wars or the New Deal, the pace of investment is accelerating rapidly as major tech companies build massive data center and GPU networks.
AI vs. History: World War II topped the list at 37.8% of GDP, followed by World War I (12.3%), the New Deal (7.7%), and the railroad boom (6.0%). AI spending currently accounts for 1.6% of U.S. GDP, already surpassing the telecom bubble’s 1.2%.
Corporate Investment Surge: Microsoft, Google, and Meta are leading with respective infrastructure outlays of $140B, $92B, and $71B. OpenAI is reportedly planning a $295B spend by 2030, signaling an unprecedented arms race in compute capacity.
The Road to 2030: If OpenAI represents roughly 30% of total market spending, annual AI infrastructure investment could hit $983B by 2030, around 2.8% of projected GDP. Matching the railroad era’s 6% benchmark would require $2.1T in yearly AI outlays, meaning each major firm would need to increase spending 5-7x.
✈️ KEY TAKEAWAYS
AI infrastructure spending has become a top-tier U.S. investment category, rivaling historical industrial booms. While far from the peaks of wartime mobilization, the compounding pace of tech capital expenditure could reshape economic priorities over the next decade.
AI Startups Double the Rate of Equity Grants for Non-Execs at Seed
New data summarized by Dylan Hughes reveals that 100% of AI startups now offer new hire equity grants to non-executive employees, compared to just 50% of traditional software startups. This shift highlights how equity has become a primary weapon in the battle for scarce AI and machine learning talent.
AI Talent Scarcity: Competition for senior AI/ML engineers is driving early-stage founders to offer equity packages typically reserved for VP-level hires, turning equity into a frontline recruiting tool rather than a long-term retention mechanism.
Capital-Driven Aggression: Massive funding rounds and investor pressure are encouraging AI startups to issue equity earlier in the company lifecycle, using ownership as the key differentiator to attract world-class technical talent.
Valuation-Backed Tradeoffs: Sky-high valuations make each equity point more valuable, prompting founders to accept greater dilution upfront to secure critical hires who can accelerate product development and differentiation.
✈️ KEY TAKEAWAYS
AI startups are redefining equity strategy at the seed stage, front-loading ownership to attract scarce technical talent. Non-AI startups entering hybrid AI product spaces will need to adapt by introducing earlier and more dynamic equity models to stay competitive.
Thanks to Lea Winkler for her help with this post.
Stay driven,
Andre
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