Started reading some S1’s recently where I really look forward to understand the business more thorughly, not just from an investor perspective but if the company has a clear startegy at play.

There are a few areas which I focus on:

  • Problem: Getting a clear articulation of the problem that a company is solving.
  • Product Bet vs competition: What is the product bet that translates to a business opportunity and why is this company better placed than others?
  • Product bet translates to business Outcome: What product outcomes directly impact the topline? Eg. what leads to improved topline - more transactions, more time spent etc.
  • Risks current and future: eg. why are customers churning currently or will do so in the future in this market?
  • How’s the business doing? What’s the revenue growth, gross margin?

The above is a general framework, and since this is a B2B product, let’s go into some more nuances. For a B2C businesses, it will look a little different, and I’ll cover it in a future post.

Lens Specific to B2B SaaS
Problem What type of problem - workflow, coordination, or data? Each predicts a different kind of switching cost and lock-in durability
Product Bet vs competition Does the product architecture structurally enable the intended GTM motion? What are the switching costs (moat) — integration depth, workflow embeddedness, ecosystem, data accumulated?
Product bet translates to business Outcome What’s the GTM motion (PLG, top-down, hybrid) and is pricing aligned to it?
• Expansion engine: What drives NRR — seats, tiers, usage, or cross-sell? Is there evidence of SMB → mid-market → enterprise conversion?  
Risks current and future Retention structure:
• Decompose churn by segment — SMB churn is structural, mid-market and enterprise GRR is what matters  
• Gross retention (logo churn) vs. net retention (spend churn) — what’s causing each?  
Business Health 1. GRR (>90% = efficient), NRR (>110% = efficient) - read together
2. ACV distribution across segments and concentration risk  
3. CAC payback period  
4. Rule of 40 (growth rate + FCF margin, >40 is healthy)  

So let’s get into Figma’s S1.

Problem

The first question I ask when reading any B2B SaaS S-1 is simple: what product outcome is the company trying to own? Great software doesn’t win because it has more features. It wins because it becomes the default way customers complete an important workflow. Once a product owns the workflow, pricing power, retention and expansion tend to follow naturally.

Design tools were single-player, while product development is inherently multiplayer. Figma primarily solves a coordination problem, and solving for multiplayer was the bet.

Workflow problems (tools people use daily) create habit lock-in. Coordination problems (tools that connect teams) create network-effect lock-in. Data problems (tools that accumulate institutional knowledge) create the deepest lock-in of all.

Product bet

Figma made design feel like Google Docs and made a multiplayer collaborative canvas for design. Instead of the clunky back-and-forth of sending files, getting feedback, and managing versions (like with Sketch), everything happens in one shared file where designers and developers collaborate in real time, and developers can directly grab code without exports. Under the hood, this was powered by some pretty novel bets: using WebGL (2D/3D graphic rendering) and WebAssembly to make the browser perform like a native editor, introducing vector networks for more flexible design workflows, and enabling true multiplayer editing at scale using CRDTs (Conflict-free Replicated Data Types). The browser native bet also aligns with it’s PLG motion because a desktop app would have required an install and an IT approval. A designer could share a Figma link with a developer or a stakeholder, and they could open it instantly. Every share was a product-led acquisition.

The real-time multiplayer nature of the product - when a designer, developer and a PM could see each other’s cursor made the value very clear - no sales team required to pitch that value. The dev mode made it easy for devs to extract CSS measurements and assets, which then became an additional persona who depended on the tool (network effect increasing the switching cost).

Now in 2025, Figma has gone deep and evolved into a full-fledged product development platform, having launched 7 new products in the last 4 years.

Product Bet Translates to Business Outcome

A great product doesn’t automatically become a great business. The bridge between the two is the go-to-market motion and pricing model. Figma operates a hybrid model where product-led growth (PLG) seeds adoption and enterprise sales scale it. Individuals and small teams start on the free Starter or Professional plans, while larger organisations move to Organisation and Enterprise plans that introduce governance, security and administrative controls. The pricing isn’t simply tiered by features; it’s designed to support how customers naturally mature from individual users into enterprise accounts.

The next question is what actually drives expansion. Net Revenue Retention (NRR), which measures how much revenue existing customers generate after accounting for upgrades, downgrades and churn, is one of the best indicators of a SaaS company’s long-term health because it reveals whether growth is coming from customers the company has already acquired. NRR can be driven by seat expansion, tier upgrades, usage or cross-sell, and each has a different level of durability. Figma’s expansion engine is primarily powered by seat growth into new personas and product expansion across the platform. Dev Mode transformed developers into a paid user persona, who now account for roughly 30% of monthly active users, while products like FigJam, Slides, Sites and Buzz have resulted in more than three-quarters of customers using multiple products. One important nuance is that part of today’s 132% NRR also reflects the March 2025 pricing changes, something management already expects to normalise over time. That makes seat expansion and cross-product adoption the metrics worth watching going forward.

Finally, I look for evidence that PLG actually converts into enterprise revenue. Around 70% of new Organisation and Enterprise customers already had someone using the Professional plan before upgrading. That’s one of the clearest indicators that the PLG motion is working. The SMB base isn’t simply generating revenue in its own right, it’s continuously feeding the enterprise pipeline. There is, however, an interesting trade-off. The recent pricing changes introduced administrator approval before additional seats are provisioned, replacing the previous user-led upgrade flow. While this improves governance for larger organisations, it also introduces friction into the very expansion engine that made the bottoms-up strategy so effective.

Risks: Current and Future

When evaluating risks, I separate them into three categories: structural churn, expansion risk and technology disruption. Starting with churn, Figma’s reported 96% Gross Revenue Retention (GRR), which measures how much recurring revenue is retained from existing customers before expansion. That suggests enterprise customers remain exceptionally sticky, while the inevitable churn within the SMB base is largely hidden from the headline metric. For a company built on PLG, that’s not necessarily concerning, but it does mean retention should always be interpreted in the context of customer segments rather than as a single blended number.

The more interesting risk is expansion drag. A SaaS business can retain customers while still slowing materially if existing accounts stop growing. Figma’s shift to administrator approval for seat upgrades is the clearest example of this. Previously, users could add seats immediately, with administrators reviewing them after the fact. Now, every additional seat requires approval before it’s provisioned. It’s a subtle operational change, but strategically it places procurement in front of what was previously a product-led expansion motion. If approval rates slow or organisations become more disciplined on licensing, seat-based expansion could naturally moderate over time.

AI creates a different category of risk altogether. Rather than asking whether AI is a threat, it’s more useful to ask how it changes the workflow Figma owns. AI-generated interfaces could automate parts of the design process, reducing the amount of traditional design work required. At the same time, Figma’s own AI capabilities can make designers more productive and strengthen the platform. A third possibility is that entirely new workflows emerge through tools like Cursor or v0, allowing software teams to move from idea to implementation with less dependence on traditional design tools. These are fundamentally different risks, and Figma will likely need a different strategy to address each of them.

How’s the Business Doing?

The first metrics I look at are Gross Revenue Retention (GRR), which measures how much recurring revenue a company retains from existing customers before expansion, and Net Revenue Retention (NRR), which includes expansion revenue from those same customers. Together, they tell you whether customers are staying and whether they’re growing. Figma’s 96% GRR shows that enterprise customers rarely leave, while its 132% NRR demonstrates that existing customers continue increasing their spend.

The customer distribution provides another useful lens. Figma has roughly 450,000 paying customers, over 11,000 spending more than $10,000 annually, and just over 1,000 spending more than $100,000 annually. At the same time, 95% of the Fortune 500 already uses the platform. That gap between widespread adoption and relatively modest enterprise monetisation represents one of the company’s biggest opportunities. Much of the future growth story is likely to come from converting existing usage into larger enterprise relationships rather than acquiring entirely new customers.

Revenue grew 48% in 2024 and continued growing 46% year over year in Q1 2025, while non-GAAP operating margins improved from 5% in 2023 to 17% in 2024. Combined with gross margins above 90%, efficient customer acquisition and strong expansion, this suggests the business is moving beyond pure growth mode into a phase where scale is beginning to generate operating leverage. Although Figma doesn’t disclose its CAC payback period directly, its combination of 90%+ gross margins, 132% NRR and a product-led sales motion suggests a very efficient payback profile.

All of this culminates in one of the simplest but most powerful SaaS metrics: the Rule of 40, calculated as revenue growth rate + profitability margin (typically operating margin or free cash flow margin). A score above 40 is generally considered the benchmark for a healthy public SaaS company. Using Figma’s 2024 results, the calculation is straightforward: 48% revenue growth + 17% non-GAAP operating margin = 65, comfortably above the threshold. More importantly, Figma achieves this without sacrificing growth.