How to Implement Batch Transactions for UX

In traditional Web3 interactions, each user action—like approving a token, swapping, and then staking—requires a separate transaction. This results in a poor user experience characterized by multiple wallet pop-ups, repeated gas fee payments, and network confirmation delays. Batch transactions solve this by allowing a user to sign a single transaction that executes a sequence of operations atomically. This pattern is fundamental for creating applications that feel as seamless as their Web2 counterparts, reducing friction and cost for end-users.

The core mechanism enabling batch transactions is the multicall function. Popularized by projects like Uniswap and MakerDAO, multicall (or aggregate) allows multiple contract function calls to be bundled and executed in a single transaction. The calls are executed in order, and the entire batch reverts if any individual call fails, ensuring atomicity. Developers implement this by encoding the calldata for each desired action and passing an array of these calls to a helper contract that delegates the execution.

For developers, implementing batching starts with smart contract architecture. Your protocol's core functions should be designed to be composed. Avoid state changes that would prevent subsequent calls in a batch. Use established libraries like OpenZeppelin's Multicall.sol for security and gas efficiency. On the frontend, libraries such as Ethers.js or Viem provide utilities for encoding calls. A typical flow involves: 1) Building an array of transaction data objects, 2) Encoding them into calldata, and 3) Sending the batch via a single sendTransaction call to the multicall contract.

Consider a DeFi use case: a user wants to provide liquidity. Without batching, this requires approving two tokens and then calling addLiquidity. With batching, you can create a single transaction with three encoded calls: approve(router, amountA), approve(router, amountB), and addLiquidity(amountA, amountB). This reduces three transactions to one, cutting gas costs by up to 40% and requiring only one wallet signature. This pattern applies universally to complex DeFi strategies, NFT minting with allowlists, and multi-step governance actions.

When implementing batch transactions, critical considerations include gas limits, error handling, and security. The total gas for the batch must not exceed the block limit. Robust frontends should simulate the batch via eth_call before broadcasting to catch potential reverts. Security is paramount; never allow user-provided calldata to execute arbitrary calls unless in a strictly permissionless context like a generic aggregator. Always audit the multicall contract's delegatecall logic to prevent vulnerabilities like the one exploited in the August 2022 Nomad bridge incident.

The future of batch transactions is moving towards native wallet and protocol support. ERC-4337 (Account Abstraction) allows smart contract wallets to natively validate and execute batches. Protocols like Uniswap v4 will feature hooks that can bundle lifecycle actions. For developers today, adopting batching is a direct competitive advantage. It significantly improves user retention and conversion by removing the biggest pain point in Web3 interaction. Start by integrating a multicall utility into your frontend for read calls, then progress to writing batched transactions for common user journeys.

To follow this guide, you will need a working development environment with Node.js (v18 or later) and npm or yarn installed. Familiarity with a modern frontend framework like React or Next.js is assumed, as we will integrate wallet interactions into a web application. You should also have a basic understanding of Ethereum concepts, including wallets, transactions, and gas fees. For testing, we recommend using a wallet with testnet funds, such as MetaMask connected to the Sepolia or Goerli testnets.

A solid grasp of Ethereum's transaction lifecycle is crucial. Understand the difference between a standard eth_sendTransaction call and a User Operation in the context of ERC-4337 (Account Abstraction). Batch transactions fundamentally change this flow by bundling multiple actions. You should also be comfortable with Ethers.js v6 or viem, as these libraries will be used to construct and send transaction objects. Knowledge of TypeScript is beneficial but not strictly required for the core examples.

Finally, you need to understand the problem batch transactions solve. Typical dApp interactions—like approving a token and then swapping it—require two separate transactions, leading to poor user experience (UX) with multiple wallet confirmations and double the gas costs. Batch transactions allow these actions to be executed atomically as a single unit. This guide will show you how to implement this using Smart Accounts via Account Abstraction providers like Stackup, Biconomy, or Alchemy, and through multicall patterns for simpler contract interactions.

A batch transaction is a single blockchain transaction that executes multiple independent function calls. Instead of signing and paying for each action separately—like approving a token and then swapping it—a user bundles them. This is a core UX improvement, reducing the number of wallet pop-ups, signature requests, and network confirmations from many to one. Protocols like Uniswap (via the Router), 1inch, and Safe (Gnosis Safe) wallets have popularized this pattern to streamline complex DeFi interactions.

From a technical perspective, batching is often implemented using a multicall pattern. A smart contract, such as the one deployed by Uniswap Labs at 0xcA11bde05977b3631167028862bE2a173976CA11, aggregates an array of call data. The user signs one transaction containing this array, and the contract executes each call in sequence. This is more gas-efficient than separate transactions, as it pays the base transaction fee only once. Key considerations include ensuring calls are non-reverting or implementing a try/catch pattern to prevent one failed call from blocking the entire batch.

For developers, implementing batching starts with the user interface. Your frontend should construct the calldata for each step (e.g., approve, swap, deposit). Libraries like ethers.js or viem provide utilities for encoding calls. Here's a conceptual snippet using viem:

javascriptCopy
import { encodeFunctionData } from 'viem';
const approveCall = encodeFunctionData({
  abi: erc20Abi,
  functionName: 'approve',
  args: [routerAddress, amount]
});
const swapCall = encodeFunctionData({
  abi: routerAbi,
  functionName: 'swapExactTokensForTokens',
  args: [amount, minOut, path, userAddress, deadline]
});
// Submit batch transaction to multicall contract
const txHash = await walletClient.writeContract({
  address: multicallAddress,
  abi: multicallAbi,
  functionName: 'aggregate',
  args: [[approveCall, swapCall]]
});

The primary UX benefits are clear: reduced friction and lower cost. A user performing a multi-step yield farming strategy might need to interact with 4-5 contracts. Without batching, this requires 4-5 approvals, waits for confirmations, and pays 4-5 base gas fees. With batching, it's one click, one fee. However, design trade-offs exist. Batch transactions are atomic—all calls succeed or fail together. This requires robust error handling and potentially simulating the batch via eth_call before submission to avoid wasting gas on a reverted transaction.

Advanced implementations use meta-transactions or account abstraction (ERC-4337) to further enhance batching. With ERC-4337 UserOperations, a smart contract wallet can natively batch arbitrary actions, and even sponsor gas fees, making the experience feel completely gasless. The future of batch transactions lies in this abstraction, moving the complexity off-chain to bundlers and paymasters, while presenting the user with a single, simple intent to sign.

Multicall is a smart contract pattern that allows multiple function calls to be bundled and executed as a single transaction or query. For read operations, it reduces the number of RPC calls, which speeds up data fetching for dApp frontends. For write operations, it enables batch transactions, allowing users to approve and execute multiple actions—like swapping tokens and adding liquidity—in one go, saving time and gas fees. The core concept is a contract with an aggregate or multicall function that takes an array of call data, executes them sequentially, and returns the results.

For reading on-chain state, libraries like ethers.js and viem have built-in multicall support. Instead of making individual calls for token balances or pool reserves, you encode the calls and send them to a deployed Multicall3 contract (address: 0xcA11bde05977b3631167028862bE2a173976CA11). The contract returns all results in a single response. This is critical for building responsive interfaces that need data from multiple sources, such as a dashboard showing a user's positions across various DeFi protocols.

Implementing write multicall is more complex as it involves user signatures and gas. A common approach is to use a permit2-style approval aggregator or a custom router contract. The user signs a single message approving a batch of actions, which are then executed atomically. If any call in the batch fails, the entire transaction can be designed to revert, protecting users from partial execution. This pattern is used by leading DEX aggregators like 1inch and Uniswap for complex swap routes.

When building a multicall, key considerations include gas estimation for the entire batch, nonce management to prevent replay attacks, and error handling for individual call failures. For EVM chains, the Multicall3 contract by Vectorized is the standard, deployed on over 40 networks. For Solana, the concept is implemented via instruction introspection within a single transaction. Always verify the multicall contract's source code and audit status before integration.

Here's a basic read multicall example using viem: import { createPublicClient, http, multicall3Abi } from 'viem' then define calls and use client.multicall({ contracts: calls }). For writes, you would typically interact with a router contract that has a multicall function, passing an array of bytes calldata. This reduces modal pop-ups and transaction confirmations, leading to a smoother user journey from intent to execution.

The main trade-off is increased complexity in transaction simulation and gas estimation. However, the UX benefits are substantial: reduced loading times, lower perceived costs, and the ability to craft complex, atomic DeFi strategies. As blockchain adoption grows, batching operations via multicall is becoming a fundamental tool for scalable and user-friendly dApp development.

Batch execution is a design pattern that allows a smart contract to perform multiple actions in a single transaction. Instead of requiring users to sign and pay gas for each individual operation—like approving a token, swapping on a DEX, and depositing into a vault—they can bundle these steps. The core contract receives a list of encoded function calls (calldata) and a target address for each, then executes them sequentially using a low-level call. This approach is fundamental to account abstraction wallets and gas sponsorship mechanisms, as it centralizes complexity and cost.

The primary smart contract is often called a BatchExecutor or Multicall contract. Its key function is simple: it loops through an array of Call structs and executes them. A basic implementation in Solidity looks like this:

solidityCopy
struct Call {
    address target;
    bytes data;
}

function execute(Call[] calldata calls) external payable {
    for (uint256 i = 0; i < calls.length; i++) {
        (bool success, ) = calls[i].target.call{value: 0}(calls[i].data);
        require(success, "Call failed");
    }
}

This contract is stateless and generic; its power comes from the pre-signed, pre-encoded calldata passed to it by the user or a relayer.

For robust production use, the basic executor must be extended with critical security and utility features. Access control is essential—you may want to restrict the execute function to a user's own ERC-4337 EntryPoint or a trusted relayer. You must also handle native token (ETH) transfers by checking the value field in the call and ensuring the contract has sufficient balance. Furthermore, implementing a executeWithDeadline or executeWithNonce function can prevent replay attacks and stale transactions. Always validate that target addresses are not blacklisted (e.g., the contract itself to prevent reentrancy).

The user experience workflow begins off-chain. A dApp's frontend or a wallet SDK constructs the series of transactions the user intends to perform. Each action is encoded into calldata using the respective contract's ABI. These encoded calls are bundled into the Call[] array. The user then signs a single message authorizing the batch execution, often using EIP-712 for structured data signing. This signed payload can be sent directly by the user or, more commonly, to a relayer network that pays the gas fee and submits it to the BatchExecutor contract, completing the operation in one on-chain transaction.

Real-world protocols like Uniswap's Universal Router, Gnosis Safe's MultiSend, and the ERC-4337 EntryPoint contract utilize advanced batch execution. The Universal Router, for instance, combines swaps, NFT purchases, and permit signatures in one tx. When designing your own, audit common pitfalls: ensure atomicity (all calls succeed or none do), carefully manage gas limits for each sub-call to avoid out-of-gas errors mid-batch, and be wary of dependencies between calls where the state change from call #1 affects call #2. Properly implemented, batch execution reduces friction and cost, making complex DeFi strategies accessible in a single click.

Batch transactions allow users to approve a token and swap it in a single transaction, or stake across multiple pools without repeated confirmations. This pattern is critical for DeFi and NFT applications where multi-step interactions are common. By reducing the number of wallet pop-ups and network confirmations from N to 1, you significantly lower user friction and gas costs. Popular protocols like Uniswap and Aave leverage batching through their routers and smart contracts. The core technical challenge is designing a frontend that can construct, simulate, and submit a bundled payload to a compatible smart contract or relayer.

To implement batching, you need a smart contract that can execute multiple function calls atomically. For EVM chains, you can use a custom contract with a multicall function or integrate with established libraries. The Ethers.js and Viem libraries provide utilities for this. First, encode each individual transaction call data. Then, bundle them into an array and pass them to your batch processor. Always simulate the batch using eth_call or estimateGas before submission to catch reverts and estimate total cost. This prevents partial execution, which can leave users in a bad state.

Here's a basic implementation pattern using Viem: import { encodeFunctionData } from 'viem'; const approveCallData = encodeFunctionData({ abi: erc20Abi, functionName: 'approve', args: [routerAddress, amount] }); const swapCallData = encodeFunctionData({ abi: routerAbi, functionName: 'swapExactTokensForTokens', args: [amount, minOut, path, userAddress, deadline] }); const hash = await walletClient.sendTransaction({ to: batchProcessorAddress, data: encodeFunctionData({ abi: batchAbi, functionName: 'multicall', args: [[approveCallData, swapCallData]] }) });. This bundles an approval and a swap. The batchProcessorAddress is a contract you deploy or a trusted protocol's multicall contract.

For a superior UX, implement gas sponsorship or meta-transactions to let users pay fees in the token they're swapping, or allow sponsored transactions via a paymaster. Use transaction simulation to show users a preview of all actions, expected outcomes, and total gas cost before they sign. Provide clear error handling: if one call in the batch fails, the entire transaction should revert. Inform users of this atomic guarantee. Tools like OpenZeppelin Defender and Gelato Network offer relay services that can manage gas and retry logic for batched transactions.

Consider user state management during the batch lifecycle. Display a single, clear pending state instead of multiple spinners. After submission, track the single transaction hash and parse the receipt logs to determine the success of each internal call. For complex batches, consider using a transaction builder UI that lets users add, remove, and reorder actions before submission. Always audit and limit the batch scope to prevent gas limit issues; very large batches may exceed block gas limits. Test extensively on testnets with tools like Tenderly to simulate edge cases and gas estimations.

Batch transactions, or multicalls, allow users to execute multiple smart contract calls in a single transaction. This pattern is essential for improving user experience (UX) by reducing the number of wallet confirmations and lowering overall gas fees. Popular implementations include the Multicall3 contract and protocols like Uniswap's Router, which bundle swaps, approvals, and transfers. For developers, the primary benefit is atomicity: either all actions succeed, or the entire batch reverts, preventing partial state changes that could leave a user's funds in an undesirable position.

Implementing batching requires careful design to manage dependencies between calls. The simplest approach uses a helper contract that executes an array of (target, data) tuples. Security is paramount: the batch executor must validate all inputs and ensure it cannot be tricked into making arbitrary calls. A common best practice is to use a whitelist of approved target addresses or function selectors. Always implement a replay protection mechanism, such as a nonce, to prevent the same batch from being executed multiple times.

For Ethereum and EVM chains, the Multicall3 contract by michaelhilton is a widely-audited standard. Its aggregate3 function allows each call to specify if it should revert on failure. Here's a basic Solidity example:

solidityCopy
function executeBatch(address[] calldata targets, bytes[] calldata data) external payable {
    require(targets.length == data.length, "Length mismatch");
    for (uint i = 0; i < targets.length; i++) {
        (bool success, ) = targets[i].call(data[i]);
        require(success, "Call failed");
    }
}

Note that this simple version lacks gas stipends for complex calls, which Multicall3 handles.

When designing the frontend, use libraries like viem or ethers.js to encode the batch. Estimate gas for the entire batch before submission, as it can be significantly higher than a single call. Provide clear user feedback: show a summary of all actions (e.g., "Swap 1 ETH for USDC, approve 100 USDC, deposit into pool") before requesting the signature. This transparency is critical for security and trust. Tools like Tenderly can simulate the batch to preview state changes and catch errors.

Consider the gas optimization trade-offs. While batching saves costs by combining base transaction fees, the total execution gas can be high, potentially hitting block gas limits. Structure batches to put likely-to-fail operations first to save gas. For protocols, offering a batched entry point (like a "zap") can abstract complexity from users. Always audit the batch logic separately from the core contracts, focusing on reentrancy, gas griefing, and the order of operations, which can introduce subtle vulnerabilities if not sequenced correctly.

Implementing batch transactions effectively requires a strategic approach. Start by identifying high-friction user flows in your dApp, such as onboarding, staking, or multi-step DeFi operations. Use a library like Ethers.js or Viem to bundle calls into a single transaction. For example, a user onboarding flow could batch an ERC-20 approval and a deposit into a single transaction, saving gas and requiring only one wallet signature. Always test your batched transactions on a testnet first to verify gas estimates and execution order.

The security and reliability of your batch implementation are critical. Use multicall contracts like those from MakerDAO (Multicall3) or Uniswap to ensure atomic execution—either all calls succeed or the entire transaction reverts. This prevents users from being left in a partial state. Be mindful of gas limits; complex batches can exceed block limits. Implement client-side gas estimation and consider breaking very large operations into multiple batches. For protocol developers, designing functions with batching in mind, such as avoiding strict msg.sender checks, can make integration smoother.

To take your implementation further, explore advanced patterns. Account Abstraction (ERC-4337) enables sponsored transactions and session keys, allowing for gasless batched interactions. Layer 2 solutions like Optimism and Arbitrum offer significantly lower gas fees, making complex batches economically viable. For inspiration, study how leading protocols use batching: Uniswap for multi-hop swaps, or Compound for collateralized debt position management. The next step is to integrate these patterns to create seamless, professional-grade user experiences that rival traditional web applications.