What's a healthy K-factor for SaaS?

K=0.1-0.2 is most B2B SaaS (referral helps but doesn't drive growth). K=0.3-0.5 is good (meaningfully reduces CAC). K=0.5-1.0 is excellent. K>1.0 = exponential growth. For consumer products K targets are higher (0.5+ to be considered viral). Tycoon Agent benchmarks you against your category.

What if my product has no built-in sharing?

Then K is being driven by word-of-mouth alone, which is hard to measure precisely. She'll estimate it via 'how did you hear about us' signup field + organic search referral patterns. The recommendation is usually to ship a viral feature (see /ship-a-viral-feature) since adding share surfaces typically lifts K by 0.1-0.3.

How is K different from referral program ROI?

K-factor is product-driven virality (anyone who uses the product creates new signups). Referral program ROI is incentive-driven (give $20, get $20). They're complementary metrics. K measures product strength; referral ROI measures program strength. Both can be improved independently.

Why segment K by cohort?

Blended K hides the signal. Power users almost always have K=0.5-1.0 (they love it, they share). Free users almost always have K<0.1 (they're not invested). The real lever isn't always 'improve sharing' — it's often 'get more users to power-user behavior so the high-K cohort grows.'

Ask Tycoon Agent: What is my referral coefficient?

You'd think K-factor needs a growth analyst — Tycoon Agent computes it weekly from PostHog signups and tells you exactly which mechanic is driving (or not).

The short answer

Tycoon Agent calculates your referral coefficient (K-factor) weekly by mining PostHog signup events for referral source attribution. K = (invitations sent per user) × (conversion rate per invitation). She pulls the last 90 days of signups, classifies each by source (direct referral link, shared content, viral feature, paid acquisition), computes invitations-sent per active user, and tracks each invitation through to signup. Segmented K-factor matters more than blended — she shows K per cohort: net-new users, paid users, power users. Most B2B SaaS sit at K=0.1-0.3 (referral helps but doesn't drive growth). K=0.5+ is meaningful CAC reduction. K>1.0 = exponential growth without paid acquisition. The weekly Lark report shows current K, 4-week trend, K by source, and the top 2 levers to push it (typically: better share UX, stronger sender incentive, or removing friction in the recipient signup flow).

How Tycoon Agent actually does it

Map referral attribution in PostHog
Set up properly: signup_source (direct/referral/viral/paid), referrer_user_id on signup. Backfill last 90 days from URL params + email links.
PostHog
Compute invitations sent per user
Per active user (logged in last 30d): how many shares, invites, public links sent. Average across cohort. This is the i in K = i × c.
Compute conversion rate per invitation
Of all invitations/shares sent, what % resulted in a signup within 30 days. This is the c in K = i × c.
Segment K by cohort and source
K for paid users vs free users, power users vs casual, new cohorts vs old. Different segments have very different K — averaging them hides the signal.
Deliver report + 2 levers
Weekly Lark: current K (overall + segmented), 4-week trend, K by referral source, top 2 levers to push it (share UX, sender incentive, recipient friction).
Lark

What it looks like in chat

YouWhat's my referral coefficient?

Tycoon AgentLast 90 days, blended K = **0.18**. Below the 0.3 useful threshold but not zero. **Math:** - Active users (last 30d): 1,247 - Invitations sent: 412 (i = 0.33) - Invitations → signup conversion: 54% (c = 0.54) - K = 0.33 × 0.54 = 0.18 **Segmented K:** - Paid users: K = 0.41 ✅ (your fans share) - Free users: K = 0.09 ❌ (they don't) - Power users (5+ logins/wk): K = 0.62 ✅✅ **The story:** your power users actually go viral on you. Free users don't share at all. The fix isn't 'add referral feature' — it's 'get free users to power user behavior faster.' **Top 2 levers:** 1. **Improve onboarding to power-user behavior.** Right now 8% of free users hit power-user threshold. Push that to 15% via /raise-onboarding-completion-to-80 → blended K to ~0.28. 2. **Add share moment to the cost analysis report** (most-used feature). Each report = one natural share opportunity. Projected K lift: +0.1. Do both = K = 0.38 in 90 days. Worth it given your $180 CAC. Want to start on lever #1?

What you get back

Weekly Lark report: K-factor (overall + segmented), 4-week trend, K by source, top 2 levers to push it.

Cadence: Weekly Friday 4pm. Quarterly deep-dive on K trends.

What is my referral coefficient?