Step 0: model one user for thirty days
Before choosing colors, simulate the most active legitimate user. Record the base production per hour, claim interval, capacity, each upgrade cost, each rate increase, task rewards, referral rewards and any withdrawable allocation. Run the model for thirty days and compare total production with total sinks and the funded reward budget.
Also model a normal user who returns once per day and a referral-heavy user. If one path creates dramatically more liability than the others, introduce caps, diminishing returns or a different kind of reward before anyone sees the promise.
- Base rate
- Offline capacity
- Claim interval
- Upgrade curve
- Task budget
- Referral budget
- Reward reserve
- Season or reset rule
Step 1: create the bot and product identity
- Create the bot with @BotFather
Choose a credible name and unique username.
- Secure the token
Connect it only to the trusted builder that will run the project.
- Write the short promise
Explain that this is a game, simulator or reward experience in one sentence.
- Add recognizable media
Complete the bot profile before sending traffic.
- Choose the primary unit
Give the production resource a name that does not imply guaranteed external value.
Step 2: connect Mini Empire and configure production
Create a Mini App project in Mini Empire, connect the BotFather token and select the mining experience. Configure the base production rate, storage or claim limit and the conditions that start or stop production. The interface should show the current rate, accumulated amount, capacity and next useful action without forcing the user to guess.
Elapsed time must be computed from trusted stored state rather than a client animation. Closing the Mini App, changing the device clock or tapping claim twice should not create extra units. Reopen the app after several intervals during testing and compare the credited amount with the model.
Step 3: build the upgrade curve and sinks
Start with upgrades whose effect is easy to understand: higher rate, more capacity or a temporary boost. Show the cost, current effect and next effect before purchase. Early upgrades can be frequent, but costs should rise faster than raw production if the economy needs to avoid unlimited inflation.
Add sinks that create choices rather than punishment. Collections, cosmetics, team contributions, season access and optional convenience can remove units while giving users a reason to care. A withdrawal fee should not be the only sink, because that makes the economy feel designed to block exits.
| Upgrade | What it changes | Risk to test |
|---|---|---|
| Rate | Units produced per interval | Exponential production liability |
| Capacity | Maximum stored production | Long absences become optimal |
| Boost | Temporary multiplier | Overlapping or repeated activation |
| Automation | Claims or restarts production | Background credits beyond intended limits |
Step 4: add tasks and referrals after the core loop works
Tasks should introduce the community, teach a feature or create measurable campaign value. Verify Telegram membership where required and label external-link tasks honestly. Give each repeatable task a cooldown or reset window, and record completion so reopening the app cannot claim it again.
Referral rewards should wait for a qualified action by the invited user. Rewarding a bot start invites account farms and teaches users to optimize the bounty rather than the product. Show pending and qualified referrals separately and cap expensive rewards according to the campaign budget.
- Task objective
- Verification method
- Cooldown
- Reward asset
- Referral qualifying event
- Self-referral rejection
- Per-period cap
Step 5: choose the revenue and payout model
Use rewarded advertising only at moments where the user chooses a clear exchange. Telegram Stars are the required rail for digital goods sold inside Telegram mobile apps, so useful upgrades or subscriptions should follow the current Stars rules. Sponsorships and partner tasks can work when the audience matches the offer and the completion evidence is honest.
Decide which unit, if any, is withdrawable. Publish the minimum, funding source, queue behavior and limits. Keep the game resource separate from a funded reward balance unless the conversion rule is real, budgeted and visible. Test one tiny transfer end to end before enabling the withdrawal button for the cohort.
Step 6: run the production-readiness matrix
| Test | Expected result |
|---|---|
| Close and reopen after one hour | Production matches the trusted elapsed-time rule |
| Tap claim repeatedly | Only one credit event is created |
| Buy the same upgrade twice quickly | Cost and effect remain consistent |
| Open a referral link twice | Sponsor and reward do not duplicate |
| Complete a repeatable task early | Cooldown blocks the second reward |
| Lose connection during a purchase | The final payment state is recoverable |
| Fail a withdrawal | The balance is not lost or refunded twice |
Step 7: launch small, then change one variable at a time
Start with users who resemble the intended audience and can describe where the loop becomes confusing. Measure first-session activation, first claim, first upgrade, next-day return, task completion and qualified referrals. Do not buy large traffic because the interface looks finished.
Change one major variable per cohort: the opening promise, claim interval, first-upgrade price or referral reward. Use broadcasts to explain material changes and preserve existing earned balances. Scale only when retention, reward cost and support load remain stable together.
Common questions
Do I need to code the mining timer?
Not with a prepared product engine. The builder supplies the state and interface; you configure and test the economic rules.
What should users mine?
Use a clearly named in-app resource tied to progression. Do not imply a guaranteed token or cash value unless a real, funded conversion or allocation rule exists.
Should I add ads before launch?
Test the core loop first. Add one voluntary placement after users understand the product, then measure retention and revenue by cohort.
How many users should test the first version?
A focused group of roughly 10–25 relevant testers is often enough to expose broken state, confusing rules and device issues before broader promotion.
Sources and further reading
Technical and product claims were checked against these primary sources.