T14

During the 2020-2021 PLG bull market, companies like Slack, Figma, and Notion were presented as examples of viral coefficient k ≥ 1 — implying self-sustaining, acquisition-cost-free growth. This framing drove massive PLG investment premiums and a generation of SaaS companies over-indexing on PLG without the product foundations to sustain it. The claim that k < 1 always binds in B2B is contested by pointing to these examples — but the counter-argument is that even Slack and Figma required continuous top-of-funnel investment to maintain growth; their viral coefficient compounded acquisition efficiency but never eliminated the need for it.

A PLG loop is a graph: User Activation -> Viral Invite (k invites per user, each converting at rate p) -> New User -> Activation. The viral coefficient K = k * p. If K ≥ 1, the loop is self-sustaining (epidemic growth). If K < 1, the loop amplifies but does not sustain — it decays toward equilibrium. In B2B, structural forces prevent K ≥ 1: (a) invite networks are finite (a company has a fixed number of employees); (b) B2B products have slower adoption cycles than consumer products; (c) same-company virality saturates quickly, and cross-company virality requires an external use case (shared documents, collaborative design). Empirically, even the strongest B2B viral products have K ≈ 0.3-0.7 — meaning they amplify acquisition efficiency 1.4-3.3x relative to no virality, but still require new-user injections from marketing. The PLG loop equation: steady-state users = Injections / (1-K), meaning the loop is valuable (it multiplies injection effect by 1/(1-K)) but the injection is always required.

• Slack S-1 filing: despite reputation as a viral product, Slack spent >$200M on sales and marketing in its last private year — the viral coefficient amplified, but marketing and outbound were still required
• Figma acquisition by Adobe at $20B: Figma had a substantial outbound and events motion alongside PLG — the two co-existed, confirming PLG as an efficient channel, not a standalone motion
• OpenView PLG Benchmarks 2022: top-quartile PLG companies had 60-70% of new users from organic/viral channels and 30-40% from paid/outbound — even best-in-class PLG required external injection
• Andrew Chen (Andreessen Horowitz) network effects analysis: B2B viral coefficients typically range 0.2-0.6 in practice, never reaching the K≥1 threshold seen in consumer social networks

• Some bottom-up-expansion PLG models (individual user converts team converts department converts company) effectively achieve K≥1 within an enterprise, even if cross-company K<1
• The K threshold varies by category — developer tools and collaboration tools have structurally higher viral coefficients than vertical SaaS, making the K<1 claim less universal
• Measuring K accurately requires distinguishing viral invites from organic discovery, which attribution systems rarely do correctly

Do not plan your growth model assuming PLG is self-sustaining. Model PLG as a multiplier on your injection (paid acquisition + outbound + brand). Calculate your effective K from product analytics: track invite-sent rate per activated user and invite-to-activation conversion rate. Use K to size how much top-of-funnel injection you need to hit your growth target: injection_required = target_new_users * (1-K). If K = 0.5, you need half the injection you would without PLG — that is significant efficiency, but still requires injection. Set a minimum viable PLG test threshold: if K < 0.2 after 90 days of product optimization, PLG is not a material channel for your product.