Crypto markets never sleep.
A single wallet moving millions in Ethereum can trigger massive price swings within minutes. By the time Twitter posts about it, the opportunity is usually gone.
Serious traders monitor whale wallets constantly. However, most tools require advanced Python scripts or Node.js bots, which makes them inaccessible for marketers, analysts, or Web3 founders without coding experience.
The good news is that you can automate crypto wallet tracking with Make.com without writing a single line of code.
Using a blockchain API, Make.com’s HTTP module, and a Telegram bot, you can build a real-time whale alert system that instantly notifies you whenever a large transaction occurs. In this guide, you will learn exactly how to build a visual Web3 automation pipeline that monitors crypto wallets and sends instant alerts to Telegram or Discord.
By the end, you’ll have a professional monitoring system similar to what crypto trading desks use.
The Cost of Being Slow in Crypto Markets
Crypto is a 24/7 battlefield where speed equals profit.
When a whale moves millions of dollars in ETH or stablecoins, the market often reacts instantly. If a smart contract gets drained or a massive sell-off begins, traders who react first have the absolute advantage.
Manually refreshing blockchain explorers is inefficient, and social media alerts arrive far too late. A real-time wallet monitoring system solves this problem by automatically tracking blockchain activity and sending alerts within seconds.
A whale tracker monitors blockchain transactions using APIs, filters them based on value thresholds, and pushes automated alerts whenever a massive movement occurs. For example, if a wallet transfers 500 ETH, your bot instantly sends a Telegram alert before most of the market even notices.
In my experience, this kind of custom automation infrastructure is exactly what crypto funds and Web3 trading teams use internally.
The No-Code Tech Stack Behind the Whale Tracker
Before building the automation, it’s important to understand the tools powering it. This system connects blockchain data sources with real-time messaging platforms.
| Component | Purpose | Example Tool |
| Blockchain Data Source | Fetch wallet transactions | Etherscan API |
| Automation Engine | Process and filter data | Make.com |
| Logic Filter | Detect whale transactions | Make.com Router |
| Alert System | Send real-time notifications | Telegram Bot |
Together, these components create a real-time crypto monitoring pipeline. Instead of coding scripts, you simply connect modules visually inside Make.com.
Step 1: Fetch On-Chain Data Using the Etherscan API 🔗
To automate crypto wallet tracking with Make.com, you must first fetch the blockchain transaction data.
Blockchains store every transaction publicly. APIs like Etherscan allow external applications to retrieve this information instantly. Make.com’s HTTP module will send the request automatically, and the API will return a JSON response containing the latest transaction details.
Follow these steps inside Make.com:
- Create a new Scenario.
- Add the HTTP – Make a Request module.
- Choose
GETrequest as the method. - Set Parse Response to
Yes.
Paste this exact Etherscan API endpoint into the URL field (replace the caps with your specific details):
Plaintext
https://api.etherscan.io/api?module=account&action=txlist&address=WALLET_ADDRESS_HERE&startblock=0&endblock=99999999&sort=desc&apikey=YOUR_API_KEY
When I run this workflow, Make.com pulls the transaction data within seconds. The output appears as structured JSON, which contains all transaction details including sender address, receiver address, and value.
However, raw blockchain data is not easy to read. That is where parsing comes in.
Step 2: Parsing Blockchain JSON Data Inside Make.com
Blockchain APIs return data in raw formats. More importantly, Ethereum transaction values are measured in Wei, the absolute smallest denomination of ETH.
1 ETH equals 1,000,000,000,000,000,000 Wei ($10^{18}$).
For example, a transaction value of 500 ETH will look like this in your Make.com HTTP module output:
Plaintext
500000000000000000000
If you send that massive number to a Telegram chat, it will look like gibberish. You must transform that value into a readable ETH amount. Inside Make.com, you map the value variable and divide it by 1 quintillion.
To make it look highly professional, wrap it in a formatting function like this:
Plaintext
{{ formatNumber(1.value / 1000000000000000000; 2; "."; ",") }}
This formula instantly converts Wei to ETH, rounds it to two decimal places, and adds commas. 500000000000000000000 becomes a clean 500.00.
Step 3: Filtering Whale Transactions with Make Routers 🐳
Not every transaction matters. Most wallets perform small transfers or pay minor gas fees constantly, which will flood your notification channel.
You need to establish a filter rule. A router evaluates the transaction data and continues the automation only if the conditions match predefined rules.
Click the wrench icon between your modules to set a filter:
- Condition: Map your divided ETH value here.
- Operator:
Numeric operator: Greater than or equal to. - Value:
100(or your preferred threshold).
In my experience, using value-based filters dramatically reduces noise while highlighting meaningful activity. Here are common thresholds:
| Whale Level | ETH Amount | Approx. USD Value |
| Small Whale | 10 ETH | ~$30K |
| Medium Whale | 100 ETH | ~$300K |
| Mega Whale | 500+ ETH | $1M+ |
Once the router confirms a whale transaction, the system triggers the alert module.
Step 4: Sending a Real-Time Telegram Alert 📲
Now comes the exciting part. Your automation will send instant alerts whenever a whale moves funds.
A Telegram bot receives the parsed data from Make.com and sends a formatted alert to a private channel. Inside Make.com, add the Telegram Bot – Send a Text Message module, connect your bot token, and map the variables into the message field.
For the best user experience, use Telegram’s HTML or Markdown parsing to create a clean visual layout. Here is a production-ready template:
Plaintext
🚨 **WHALE ALERT: Massive Transfer Detected** 🚨
💰 **Amount:** {{formatNumber(1.value / 1000000000000000000; 2; "."; ",")}} ETH
📤 **From:** `{{1.from}}`
📥 **To:** `{{1.to}}`
🔗 [View Transaction on Etherscan](https://etherscan.io/tx/{{1.hash}})
This message appears instantly in your Telegram channel. By wrapping the wallet addresses in backticks, traders can tap to copy them instantly on mobile. The clickable transaction hash lets them jump straight to the block explorer.
Advanced Upgrade: Send Alerts to Discord or Slack
Telegram works perfectly for personal alerts or small groups. However, enterprise trading teams often prefer Discord or Slack for broader collaboration.
The exact same automation pipeline works with a Discord Webhook. Instead of the Telegram module, simply add an HTTP POST request module that pushes the JSON payload to your Discord server’s webhook URL.
Pro-Level Insight: Turning Whale Tracking into a Data Pipeline 💡
Most beginner tutorials stop at simple alerts. However, real trading desks build data pipelines, not just bots.
In my experience working with automation systems, the true power comes from storing and analyzing transaction history. You can extend this system by:
- Logging confirmed whale transactions into Google Sheets or Airtable for historical modeling.
- Tracking specific smart contract liquidity pool changes.
- Detecting massive centralized exchange (CEX) inflows and outflows.
These upgrades transform a simple bot into a Web3 intelligence platform. And the best part? You built the entire foundation using visual API routing instead of complex code.
Why This Skill Matters for Web3 Careers
Building systems like this proves something incredibly important to employers: you understand real-time financial data payloads.
Recruiters in major tech and crypto hubs like Dubai and Riyadh actively look for professionals who can connect blockchain APIs, automation platforms, and messaging systems. While most digital marketers only know how to automate email forms, someone who can automate crypto wallet tracking with Make.com demonstrates deep, cross-industry technical ability.
You are no longer just automating tasks; you are building Web3 infrastructure.
FAQs
How can I automate crypto wallet tracking without coding?
You can automate crypto wallet tracking without coding by connecting a blockchain API like Etherscan to Make.com. The automation fetches wallet transactions, filters large transfers, and sends instant alerts to messaging platforms such as Telegram or Discord. This visual workflow replaces traditional Python scripts with drag-and-drop automation modules.
What is a crypto whale tracker?
A crypto whale tracker is a monitoring system that detects large blockchain transactions. It analyzes wallet activity and sends alerts when significant amounts of cryptocurrency move between addresses. Traders use whale trackers to anticipate market shifts caused by large investors or institutional activity.
How does the Etherscan API work for wallet monitoring?
The Etherscan API retrieves blockchain transaction data from Ethereum wallets. Applications send HTTP requests containing wallet addresses and API keys. The API responds with structured JSON data that includes transaction value, sender address, receiver address, and timestamps, which automation tools can process.
What is the minimum transaction value for whale alerts?
Most whale trackers set thresholds between 10 ETH and 100 ETH depending on trading strategies. Smaller thresholds generate more alerts but also more noise. Professional trading desks often monitor transfers above $100,000 because those movements tend to influence market liquidity.
Can Make.com monitor smart contracts and token transfers?
Yes, Make.com can monitor smart contracts and token transfers using blockchain APIs such as Etherscan or Alchemy. By querying token transfer endpoints instead of wallet transactions, the automation can detect large ERC-20 token movements, liquidity pool changes, or NFT mint activity in real time.
See Also: Revoke Smart Contract Permissions Rabby Wallet: Complete Safety Guide
