Refer-2-Earn
Updated: 8th March 2025
The most effective driver for Web3 DApp adoption is community-led growth, where users bring in fellow content creators and consumers. To foster this organic expansion, the RuBaRu's Refer-to-Earn program offers incentives to both the Referrer and the Referee each time a new user joins.
Consideration & Hypothesis: The initial phase of user adoption is expected to incur high costs, necessitating a higher reward structure for referrals. However, as the user base expands and the platform gains traction, the cost of onboarding new users will decrease. Consequently, the rewards for referrals will also be adjusted downward in alignment with the reduced acquisition costs.
This ensures that RuBaRu’s expansion benefits its community, not just the platform itself. More importantly, early adopters earn the highest rewards, making them key drivers of the SocialFi revolution.
How It Works: Dual Incentives for Growth
RuBaRu’s R-2-E program rewards both the Inviter (referrer) and the New user (referee) in RuBaRu Credits.
This referral model is designed to: ✅ Motivate participation – Higher rewards for early users, ensuring rapid adoption. ✅ Follow a fair distribution model – Rewards halve over time, prioritizing early adopters while maintaining sustainability.
Reward Structure
📌 Current Earning Model:
Referrer earns: 100 RuBaRu Credits per successful referral
Referee earns: 100 RuBaRu Credits upon signing up, in addition to 200 Credits for J-2-E
(Note: Rewards for both the Referrer and Referee will be halved at predefined intervals—every 100K users for referrers and every 80K users for referees, ensuring a gradual decrease in acquisition costs over time.)
Satoshi’s Epoch Halving (SEH) Algorithm
This model follows a Bitcoin-style halving approach, where rewards decrease by half after a certain number of users join the platform. The referee’s reward decreases faster than the referrer’s reward, ensuring an early adoption incentive while stabilising at a minimum reward after multiple halvings.
Variable Definitions:
Rreferrer(U) → Referrer’s reward at registered user count U
Rreferee(U) → Referee’s reward at registered user count U
U → Total number of users who have joined the platform
R0 → Initial reward (e.g., 100 Credits)
Rmin​ → Minimum reward after stabilization (configurable, e.g., 10)
Hreferrer → Halving interval for referrer rewards (e.g., every 100K users)
Hreferee → Halving interval for referee rewards (e.g., every 80K users, meaning faster decay)
⌊x⌋ → Floor function (rounds down to the nearest whole number)
How Halving works?
Inviter Reward Halving: Every 100K users
Invitee Reward Halving: Every 80K users
Final Stabilization: Rewards will not drop below 10 Credits after the last halving.
Referrer(Inviter) Reward Table - Halving every 100k registered users
0 - 99,999
0
100 * pow(2,0) = 100
100
100k - 199,999
1
100 * pow(2,-1) = 50
50
200k - 299,999
2
100 * pow(2,-2) = 25
25
300k - 499,999
3
100 * pow(2,-3) = 12.5
12
500k+
4
Stablises at 10
10
Referee(New User) Reward Table - Halving every 80k registered users
0 - 79,999
0
100 * pow(2,0) = 100
100
80k - 159,999
1
100 * pow(2,-1) = 50
50
160k - 239,999
2
100 * pow(2,-2) = 25
25
240k - 319,999
3
100 * pow(2,-3) = 12.5
12
320k - 399,999
4
100 * pow(2,-4) = 6.5
10 (Capped)
400k+
Stable
Remains 10
10
Last updated
