34 ยท K-FACTOR MATHEMATICS
Version: 1.0 | Date: 12.03.2026 | Status: Canonical Category: Growth SSOT for: Viral coefficient math, growth loops modeling, referral economics Dependencies: 09_PARTNER_PROGRAM, 20_GROWTH_IDEAS, 11_GO_TO_MARKET
TL;DRโ
- K-factor = number of new users brought by 1 existing user
- K > 1 = viral growth (exponential). K = 0.3โ0.5 = healthy addition to paid traffic
- Wellex has 4 independent viral loops with different K. Combined K-target: 0.6โ0.8 by M6
- Math shows: K 0.6 at CAC $30 โ effective CAC drops to $13.3
1. K-Factor: basic mathโ
Formulaโ
K = i ร c
where:
i = number of invites from 1 user per period
c = invite-to-registration conversion (%)
What K-factor meansโ
| K-factor | Growth type | Interpretation |
|---|---|---|
| K < 0 | Churn | Users leave faster than they arrive |
| K = 0 | Linear | Growth only through paid traffic |
| 0 < K < 1 | Sub-viral | Each user brings <1 new. Addition to CAC |
| K = 1 | Critical mass | Each user brings 1 new. Stable doubling |
| K > 1 | Viral growth | Exponential growth without paid traffic |
Impact on CACโ
Effective CAC = Paid CAC / (1 / (1 - K))
At K = 0.3: Effective CAC = $30 / 1.43 = $21.0
At K = 0.5: Effective CAC = $30 / 2.0 = $15.0
At K = 0.6: Effective CAC = $30 / 2.5 = $12.0
At K = 0.8: Effective CAC = $30 / 5.0 = $6.0
At target K = 0.6 and Paid CAC $30 โ Effective CAC = $12. That's 2.5ร reduction in acquisition cost.
2. Four Wellex viral loopsโ
Loop 1: Referral Program (direct referral)โ
Mechanics: User invites friend โ both get bonus.
| Parameter | Value |
|---|---|
| Invites from 1 user (i) | 0.8/month (avg, from beta user base) |
| Invite conversion (c) | 22% |
| K for this loop | 0.8 ร 0.22 = 0.176 |
Invite conversion structure:
100 invites sent
โ 65 opened link (65% open rate)
โ 34 reached registration page (52% CTR on link)
โ 22 registered (65% completion)
โ c = 22%
Loop 2: WVI Social Share (organic viral)โ
Mechanics: User shares WVI card on social โ visits โ registrations.
| Parameter | Value |
|---|---|
| Share of users sharing/month (s) | 35% (target M3; currently ~20%) |
| Avg followers of sharer | 800 |
| CTR on WVI card | 1.2% |
| Visit-to-registration conversion | 8% |
| K for this loop | 0.35 ร (800 ร 0.012 ร 0.08) = 0.269 |
Viral coefficient calculation:
1 user shares โ 0.35 probability of share per month
0.35 ร 800 impressions = 280 impressions
280 ร 1.2% CTR = 3.36 clicks
3.36 ร 8% conversion = 0.27 new registrations
K_loop2 = 0.27
What increases K_loop2:
- Streak NFT โ more visible cards โ CTR rises to 2.0% โ K = 0.44
- Leaderboard virality ("Team #3 in MENA") โ additional shares
- "Wellex Wrapped" (December) โ 1-day K spike to 2.0+
Loop 3: MLM Partner Network (network multiplier)โ
Mechanics: Partners recruit users into their networks. Structural viral.
| Parameter | Value |
|---|---|
| Share of users who become partners (p) | 12% (target M3) |
| Avg referrals from partner/month | 4.2 |
| Conversion to active user | 60% |
| K for this loop | 0.12 ร 4.2 ร 0.60 = 0.302 |
Partner network analysis:
1000 users
โ 120 partners (Explorer+ rank)
โ 120 ร 4.2 referrals = 504 invites
โ 504 ร 60% conversion = 302 new users
K_loop3 = 302 / 1000 = 0.302
Compounding: partners become users โ become partners โ recruit. Each "tier" adds ~15% of previous effect.
Loop 4: B2B Corporate (group viral)โ
Mechanics: Company buys Wellex for Teams โ 50โ500 employees onboard at once โ some become partners or share on social.
| Parameter | Value |
|---|---|
| B2B clients per month (Phase 2) | 3 |
| Avg employees per B2B client | 120 |
| Share who become partner/referral | 15% |
| Avg referrals from B2B-arrived user | 1.8 |
| K for this loop | 3 ร 120 ร 0.15 ร 1.8 / 1000 users = 0.097 |
Small K โ but each B2B client = 120 users at once, accelerating base for loops 1โ3.
3. Combined K-factorโ
Important: loops don't sum linearly โ they partially overlap. Real combined K:
K_total = K1 + K2 + K3 + K4 - overlap(~15%)
Phase 1 (M1โM3):
K_total = 0.176 + 0.27 + 0.302 + 0.097 - 0.08 = 0.765
But realistically โ in first months loops don't run at full capacity:
| Period | K actual | K target |
|---|---|---|
| M1 | 0.20 | 0.25 |
| M3 | 0.35 | 0.40 |
| M6 | 0.55 | 0.60 |
| M12 | 0.65 | 0.70 |
4. Growth modeling โ how K affects growthโ
Base model (M1: 1000 paid users, monthly paid acquisition: 500)โ
M1: 1000 (paid) + 1000 ร K = base
M2: (M1 ร (1-churn) + 500 paid) ร (1 + K)
...
Scenarios at different K (10 months, churn 8%/mo, 500 paid/mo):
| Month | K=0.2 | K=0.4 | K=0.6 | K=0.8 |
|---|---|---|---|---|
| M1 | 1,100 | 1,200 | 1,300 | 1,400 |
| M3 | 2,800 | 3,600 | 4,600 | 6,000 |
| M6 | 5,200 | 8,100 | 13,500 | 23,400 |
| M10 | 7,800 | 15,200 | 31,200 | 71,000 |
Conclusion: difference between K=0.4 and K=0.6 by M10 = 31,200 vs 15,200 โ twofold. That's the difference between $6.2M ARR and $3.1M ARR.
5. Referral Economicsโ
Referral unit economicsโ
| Parameter | Value |
|---|---|
| Referral bonus cost | $5 + 8% M1 subscription = $5 + $1.52 = $6.52 USDC |
| CAC via referral | $6.9 |
| Referral LTV (avg) | $19 ร 18 mo ร (1-15% churn) ร 85% margin = $247 |
| LTV / CAC | 247 / 6.9 = 35.8ร |
For comparison: Meta Ads paid traffic โ CAC $28, LTV/CAC = 247/28 = 8.8ร
Referral channel is 4ร more efficient than paid traffic by LTV/CAC.
Referral CAC optimizationโ
Where conversion is lost (and what to do):
100 invites
โ 65 opened (-35% didn't open)
FIX: personalize link with referrer name
โ 34 reached registration page (-48% closed)
FIX: landing page A/B test (currently 52% CTR โ target 65%)
โ 22 registered (-35% didn't complete)
FIX: simplified onboarding (email โ 1 click)
โ 18 activated bracelet (-18% didn't activate)
FIX: onboarding video + SMS reminder
โ Total: 18% effective conversion (target: 25%)
If conversion improves from 22% to 30% (via UI/copy optimization):
- K_loop1 grows from 0.176 to 0.240
- Combined K grows from 0.55 to 0.62
- At 10K users โ additional +700 users/mo free
6. K-factor monitoringโ
Metrics for monthly trackingโ
| Metric | Formula | Where to measure |
|---|---|---|
| Viral K | (New users from referrals) / (Total users prev month) | Analytics dashboard |
| Invite Rate | (Users who sent โฅ1 invite) / (Total active users) | Events tracking |
| Invite Conversion | (Registrations from invites) / (Total invites sent) | Referral system |
| Share Rate | (WVI shares) / (Total active users) | Social analytics |
| Partner Ratio | (Active partners) / (Total users) | Partner dashboard |
K-factor dashboard (WEB โ Internal)โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ Wellex Growth Engine โ March 2026 โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ Combined K-factor: 0.38 (โ from 0.31) โ
โ Target: 0.40 (M3) โ
โ โ
โ Loop 1 (Referral): K = 0.18 โ
โ
โ Loop 2 (Social): K = 0.12 โ ๏ธ โ
โ Loop 3 (MLM): K = 0.08 (early) โ
โ Loop 4 (B2B): K = 0.00 (Phase 2)โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ Bottleneck: Social share rate 18% โ
โ Target: 30%. Action: improve WVI card โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
7. Scaling scenariosโ
When K-factor becomes criticalโ
At base 10,000 users and K = 0.6:
Month 0: 10,000 users
Month 1: +6,000 (from K) + 500 (paid) - 800 (churn) = 15,700
Month 2: +9,420 + 500 - 1,256 = 24,364
Month 3: +14,618 + 500 - 1,949 = 37,533
โ From 10K to 37K in 3 months without increasing paid budget.
What's needed to reach K = 0.8โ
| Action | Impact on K |
|---|---|
| Improve WVI share card (CTR 1.2% โ 2.0%) | +0.08 |
| Add "Wellex Wrapped" (December) | +0.15 (seasonal) |
| Launch Country Captain program | +0.05 |
| Increase partner ratio from 12% to 18% | +0.09 |
| B2B Phase 2 launch (5 clients/mo) | +0.04 |
| Total additional | +0.41 |
K 0.38 + 0.41 = K 0.79 โ practically reaching target K = 0.8
Changelogโ
โธ v1.0 (12.03.2026) โ created by Opus 4.6. 4 viral loops with formulas, growth scenarios, referral economics, K monitoring dashboard.
โ Related: 20_GROWTH_IDEAS.md ยท 09_PARTNER_PROGRAM.md ยท 11_GO_TO_MARKET.md
Wellex ยฉ 2026 ยท wellex.ai