Growth & Viral

Help satisfied users invite and share so growth compounds from real value—never from contact spam or coerced invites.

Prerequisite: Customer Discovery (especially Talk, Search, and Buy). Core concept: Social Transmission. Also User Agency, Retention.

What it is

Growth and viral design is about building product moments where satisfied users bringing in other people is a natural consequence of the value they already got—not a marketing campaign bolted onto the product, and not a mechanism for turning every user into an unpaid sales channel. The test for whether a growth loop belongs in the product or belongs in the ad budget is simple: would a person invite someone to this on their own, unprompted, because it genuinely helps both of them? If the honest answer is no, the “growth feature” is extraction wearing a product costume.

This strategy covers two related but distinct behaviours: referral, where someone actively recommends the product to a specific person because they think it will help them, and shareability, where someone shows off an outcome they created because they are proud of it and the artefact happens to carry the product’s name. Both depend on the same precondition—real, felt value that the person wants associated with their own reputation—which is why growth work fails when it is attempted before Activation has actually happened.

Why it works

Word of mouth converts and retains better than almost any paid channel because it arrives pre-qualified: the person doing the inviting already filtered for relevance, and the person receiving the invite trusts the source more than they trust an advertisement. Social Transmission explains the mechanics—shareable artefacts, genuine referrals, and contact bridges that connect people who already know each other—while User Agency is the boundary that keeps those mechanics honest: consent at every hop, never a harvested address book or a pre-value invite wall.

The compounding math (often summarised as a viral coefficient, or K-factor) is real but frequently overrated in isolation: a modest K paired with strong retention outperforms a flashy K paired with weak retention, because a leaky loop just cycles the same churn through a bigger top-of-funnel. This is why growth strategy is inseparable from Retention—a referral loop invites people into a product that then has to actually keep them, or the loop is manufacturing acquisition cost it never recovers.

Core Tools, Techniques, and Practices (TTPs)

• Referral: Help satisfied users invite people who will genuinely benefit, with a clear and respectful path for everyone
• Shareability: Help users share a meaningful outcome when they want to tell its story
• Contact Bridge: Connect users to people they already know—without turning their address book into a growth hack
• Deep-link: Drop users into the exact moment, feature, or context that matters
• Success Moments: Mark meaningful progress with feedback that feels earned, then let users decide what comes next

Supporting Tools, Techniques, and Practices (TTPs)

• Gamified Progress: Make meaningful progress visible, achievable, and fully in the user’s control
• Effort Moat: Honour what people have built, so their progress remains useful and recognisable
• Variable Reward: Add optional novelty around reliable value, without making users chase uncertainty
• System Widget: Put one timely, glanceable piece of user-chosen value where people already look
• Spark Curiosity: Offer a truthful glimpse of a useful outcome, then let users choose whether to explore it

Insights & Metrics

Measure whether sharing and invites compound—and whether the users they bring stick.

1. Viral Coefficient (K-Factor)
   • Formula: Invitations sent per user × Invitation acceptance (conversion) rate
   • What it measures: Average new users each existing user brings through the invite/share loop
   • Why it matters: K > 1 is rare; even modest K with strong retention still lowers acquisition cost. A high K with poor retention is a leaky loop
2. Viral Cycle Time
   • Formula: Median time from a user’s first invite-eligible moment to their first successful referral (invitee activates)
   • What it measures: How fast one generation of the loop completes
   • Why it matters: Shorter cycles compound more at any K; speeding empty prompts without value usually hurts quality
3. Organic Share of New Users
   • Formula: (New organic users in period ÷ Total new users in period) × 100
   • What it measures: How much acquisition comes from word-of-mouth, shares, and unpaid discovery vs paid
   • Why it matters: Rising paid dependence with flat organic share often means the loop is weak or prompts feel extractive
4. Referral Programme return on investment (ROI)
   • Formula: ((Revenue attributable to referred users − Referral costs) ÷ Referral costs) × 100
   • What it measures: Whether incentives and programme ops pay back
   • Why it matters: Profitable only if referred users activate and retain—not if rewards buy one-off signups
5. Network Density (where connections are the product)
   • Formula: (Connected user pairs ÷ Total possible pairs) × 100
   • What it measures: How interconnected the graph is for collaboration and invitation paths
   • Why it matters: Density without mutual value is vanity; useful density predicts when invites feel natural rather than forced

Behind the Data

Diagnose whether people want to invite or share—and what blocks a respectful loop.

Loop quality & timing

• Which Success Moments produce shares or invites that convert—and which prompts get dismissed or reported?
• Does earlier ask raise invite volume but lower acceptance, activation, or trust?
• Where do Deep-links land invitees, and does that context match the story the sharer told?

Network & value

• At what connected-group size does the product feel clearly better for the user?
• Which collaborative or multiplayer features create invites that help both sides?
• Do Contact Bridge suggestions feel useful and optional, or like harvesting an address book?

Channel & incentive health

• Which share/referral channels bring users with the best activation and retention—not just the most clicks?
• How do organic vs incentivised referrals differ on quality, and when do rewards attract mercenary invites?
• What shareable artefacts convert without pressuring the user to broadcast?

Further reading

• Lessons Learned – Viral Marketing (David Skok) — Canonical K-factor and why cycle time often dominates growth math.
• Why the best way to drive viral growth is to increase retention (Andrew Chen) — Retention as the foundation of durable viral loops.
• 16 Ways to Measure Network Effects (a16z) — Practical metrics across acquisition, engagement, and economics—not just vanity K.
• The Network Effects Manual (NFX) — Taxonomy of network-effect types so “viral” is not treated as one lever.
• The Dynamics of Network Effects (a16z) — How network value evolves—and why early loops can weaken without care.

Agent skill

• Primary command / sequence: /productfeeling sequence — jobs → peaks-ends → trust → anti-patterns → review
• Core TTPs to load: Referral, Shareability, Contact Bridge, Deep-link, Success Moments
• Supporting TTPs: Gamified Progress, Effort Moat, Variable Reward, System Widget, Spark Curiosity
• When the agent should use this strategy: “referral programme”, “invite flow”, “share sheet”, “viral loop”, “organic growth”, “network invite”
• Companion handoff: Impeccable — share sheets, invite flows, deep-link landing states, and referral UI; DocSlime — when growth-loop definitions or referral economics belong in docs/strategy/; RedTeam — before contact-import prompts, incentive structures, or pre-value invite walls (/redteam assumptions on who benefits and who bears cost)
• Feeling north star this strategy serves: pride worth sharing through helpful invitation
• Anti-goals: address-book spam, forced invites before value, dark-pattern share walls, incentive bait that harms invitees, manufactured FOMO
• Reference path: skill/reference/sequence.md