Case Study: Clicker Game Economy with Revenue-Share via Smart Contract

GameFi clickers are among the most mass-market crypto formats. But most of them hit the same wall: the economy collapses within 3–6 months after launch, with critical decline typically by month 3–4. This case study examines how a project targeting 15M players designed tokenomics where the token is backed by real revenue — not inflationary rewards.

Context: The Project’s Challenge

The project is a clicker game with layer-mining mechanics: players uncover cells of a virtual object layer by layer, collecting prizes. The one who reaches the center claims the grand prize. Available on iOS, Android, and as a Telegram mini-app.

The fundamental difference from most GameFi: the project is split into two phases.

Phase 1 — Game without a token. Goal: acquire up to 15M users and generate cash flow in stablecoins. At this stage, the entire economy runs on fiat payments and in-game currency.

Phase 2 — Ecosystem with a token. Launches only if Phase 1 succeeds: token, DAO, airdrop to players and developers. The token is tied to revenue via smart contract.

The tokenomist’s objectives:

1. Design revenue-share — investors receive a share of revenue through the token, without traditional unlock schedules
2. Don’t kill the game economy — the token must not create inflation that destroys game balance
3. Scalability — the model must work at 1M and at 15M players

The Solution: Tokenized Revenue

Core Idea

Instead of the classic “investors receive tokens → sell on market” scheme, the project used revenue-share through a smart contract:

1. A portion of revenue from in-game equipment sales is automatically used to buy the token via a liquidity pool
2. Investors hold tokens that appreciate due to buyback from real revenue
3. Investor exit is through market sale, not through vesting unlocks

Token Parameters

• Total supply: 100,000,000 tokens
• Base currency: USDT

Allocation and Vesting

Three investment rounds with increasing price: $0.10 → $0.20 → $0.40 per token. Target raise: $14,000,000 total.

Market Model: Uniswap v2

Liquidity pool on Uniswap v2 with the constant product formula:

Starting price: $0.175 (1.75x multiple over Round 1 price). The key mechanism: 70% of the project’s operating income (which is 50% of net revenue from primary + secondary markets = 20.75% of total net spending) flows into the pool as buy-side inflow, creating continuous buying pressure on the token.

The Model: In-Game Economy

Game Mechanics

The game simulates a mining-like process: all players start with identical base equipment. Advanced equipment (semi-automatic, automatic) improves chances but doesn’t guarantee victory.

• 100 layers — players progress sequentially
• Average speed: ~2.7 days per layer
• Viral coefficient: 0.7–0.8 (41–44% of new players come through referrals; ~66% of total organic acquisition comes through squads and viral loops combined)

In-Game Currency and Equipment

In-game currency (called “coins”) is distributed across layers — 5B units per layer. Equipment is divided into 11 classes (0–10) with increasing productivity:

Selected classes shown; full table has 11 tiers (0–10) with near-geometric growth in both production and energy capacity.

Equipment upgrades use a fusing system: 2 items of the same class produce 1 item of the next class. Cost grows geometrically, creating a natural sink for in-game currency.

Starting from class 4, equipment gains additional attributes: durability and repair cost reduction — adding strategic depth for hardcore players.

Player Types and Unit Economics

The simulation identifies 6 cohorts with distinct behavior patterns:

Revenue Distribution

Revenue from both markets is split 50/50 between the project’s operating income and the prize pool.

Prize Pool

• Initial fund: $2,000,000 USDT
• Distribution: 65% — layer prizes, 35% — grand prize (center of the object)
• Pool is replenished from 50% of primary and secondary market revenue

Scenario Analysis

The model was tested across three scenarios:

Maximum scenario (9-month simulation): 18.2M cumulative new players, $4.7B cumulative net spending (including repeat purchases), $979M operating income, $981M prize pool. The $750M figure in the table is a point-in-time snapshot (15M × $50 GMV), while $4.7B is the total over the simulation period accounting for churn and acquisition.

Value Allocation in the Maximum Scenario

Lessons Learned

Key design decisions

The main lesson: in GameFi, the token should not be the players’ income source — it should be an instrument for investors and the ecosystem. Players earn in stablecoins; the token is backed by revenue. This breaks the vicious cycle of “emission → sell → devaluation.”