Grab Red Packet Amounts, Transfer Notes & Addresses from a WeChat Chat Screenshot
Manually copying a red packet amount, a transfer note, or a Chinese delivery address from a WeChat chat takes 2-3 minutes per customer — this pulls both card data and chat metadata in 5 seconds per image.
5-10s per screenshot · Up to 99% accuracy on printed text
Every WeChat Chat Has Two Layers of Extractable Data
WeChat chat screenshots mix styled in-chat cards (红包 red packets, 转账 transfers) and unbroken Chinese address strings with chat-native UI elements — sender names, timestamps, and message type indicators. With Custom Column Extraction, you name the fields you want, and the AI reads each by visual role and semantic context, not by guessing at a layout that doesn't exist.
Content Fields (消息内容字段)
The opened amount from a red packet card — large centered text on a styled red background, extracted as a currency value.
The ¥ figure from a transfer confirmation card — the AI reads it as a styled UI component, not plain text.
The memo line below the transfer amount — commonly used as an order reference, item description, or purchase note.
Chinese hierarchical address — province, city, district, street, building — extracted from a single unbroken line.
The 11-digit mobile number identified even when fused into an address string without delimiters.
Native Metadata (App原生属性)
Read from the chat header — consistent across all messages in the same conversation, includes emoji names.
Date or time from the message header — absolute or relative — captured as shown for each message.
Classifies each visible element as a red packet card, transfer card, text message, or system notice.
Why a WeChat Chat Screenshot Is Harder to Parse Than Any Other App
WeChat's chat interface embeds styled transaction cards, system messages, and unbroken Chinese address strings into the same visual stream — three data formats that traditional OCR treats as one undifferentiated text block.
Red Packets (红包) and Transfers (转账) Are Styled Cards, Not Text
A red packet confirmation is a large red rectangular card with centered white text. A transfer confirmation is a grey card with the amount in bold and a note line below. Traditional OCR treats both as irregular text regions mixed with the surrounding chat — it cannot isolate the card amount from the bubble text beside it.
Chinese Addresses Are One Unbroken String
"广东省深圳市南山区科技南路18号 李明 13800138000" — province, city, district, street, building, recipient name, and phone number in a single line with no delimiters. A position-based OCR engine cannot tell where the address ends and the phone number begins.
Message Types Share the Same Visual Space
A single screenshot can contain a red packet card, a transfer confirmation, and a plain text message with an address — three distinct visual objects. A small business owner on Xiaohongshu (小红书) described the manual alternative: "Every order, I read the address, copy the phone number, write it on the package, and pray I didn't mix up the district name. I process thirty orders a week and I still check each package twice."
Reads Styled Cards as Visual Components
The AI recognizes the red packet card by its distinct red background and centered text layout, the transfer card by its bordered card frame and bold amount. The amount on a red packet goes into your Red Packet Amount column; the transfer amount and note go into their respective columns — not into a single text dump.
Segments Chinese Addresses by Pattern
The AI reads the hierarchical address structure — province (省), city (市), district (区), street (路/街/道), building number — as a pattern, not a fixed set of positions. It identifies the 11-digit phone number by its numeric structure and the recipient name by character position, then routes each segment to your Address, Recipient, and Phone Number columns separately.
Classifies Each Object by Visual Role
A red packet card is one visual role, a transfer card is another, a text message is a third. The AI classifies each by its visual structure before extracting data — so the red background with centered white text signals "red packet amount," the bordered card with a note line signals "transfer data," and the plain bubble signals "text content." Define one column set and it works across all three in the same screenshot.
From Mixed WeChat Chats to One Order Log
Whether you are logging red packet income for a fundraiser, recording transfer notes from clients, or compiling delivery addresses from a week of orders — the process is three steps, and one set of column names covers every message type.
Upload the WeChat Screenshots
You have a folder with a red packet confirmation, two transfer screenshots from different clients, and an address message — all in one batch. PNG, JPG, whatever your phone saved them as. No sorting by message type required before uploading.
Name Your Columns Once
Type Red Packet Amount, Transfer Amount, Transfer Note, Delivery Address, Phone Number, Sender, Timestamp. The AI reads each screenshot individually — the red packet card fills the Red Packet Amount column, the transfer card fills Transfer Amount and Note, the text message fills Address and Phone Number. Sender and Timestamp are populated from chat-native UI across all types.
Export a Unified Spreadsheet
Every screenshot becomes one row. Red packet rows have the amount and sender; transfer rows have amount, note, and counterparty; address rows have the full address, phone, and recipient name. One .xlsx file with all your WeChat orders, sorted and ready to reconcile against your delivery list.
Extracting from WeChat Chat — What Works and What Doesn't
Styled cards and address strings extract reliably when conditions are right. A few scenarios need extra attention.
- ✓ Opened red packet cards and transfer confirmation cards with clear high-contrast text — the AI reliably reads both the styled card UI and the embedded values.
- ✓ Chinese address messages with a complete province-city-district-street structure plus a visible 11-digit phone number — the segmentable pattern gives the AI clear boundaries.
- ✓ Batches mixing red packet, transfer, and address screenshots together — one column set works across all message types.
- ⚠ The AI extracts named fields from visible chat content — it does not reconstruct the full conversation or produce a chat transcript. For complete chat history with message ordering, use WeChat's built-in chat export feature rather than screenshots.
- ⚠ Chinese text in heavily compressed or low-resolution screenshots — common when chat images are forwarded multiple times — can reduce accuracy on individual characters in address district names or phone number digits. Screenshot the original conversation for the best results.
Frequently Asked Questions About WeChat Chat Data Extraction
An unopened red packet card shows the sender name but no amount — can the AI still extract anything?
An unopened red packet card shows only the red packet graphic and the sender's name. The amount is hidden until the recipient taps to open it — the AI cannot extract a number that is not visually rendered. If you define both a Sender Nickname column and a Red Packet Amount column, the Sender is populated from the card header, and the Amount cell stays empty for that row. Always open the red packet before screenshotting if you need the amount.
Can the AI separate the phone number from the delivery address when they appear as one continuous Chinese string?
Yes. A WeChat message like "广东省深圳市南山区科技南路18号 李明 13800138000" is a single unbroken string containing the delivery address, recipient name, and phone number. The AI segments by pattern: the 11-digit mobile number follows China's phone numbering format and is extracted into your Phone Number column; the hierarchical address structure (省province + 市city + 区district + 路street + 号building) goes into the Delivery Address column; the name between them fills the Recipient Name column. Define these as separate columns and the AI assigns each segment to the correct field.
Can I extract the Transfer Note from a WeChat transfer card screenshot?
Yes. When a customer sends a WeChat transfer (转账), the card displays the amount in bold and often includes a note or memo line below it — typically used as a purchase reference like "订单 42" (Order 42) or a brief description. Define a Transfer Note column alongside the Transfer Amount column. The AI reads the memo text from the transfer card's note area, separate from the amount. If the sender did not include a note, the cell remains empty without affecting the other columns.
What WeChat chat metadata can I extract — sender nickname, timestamp, and message type?
All three. Define a Sender Nickname column — the AI reads the display name from the chat header or bubble label, including emoji names. Define a Timestamp column — the date and time from the message header, captured as shown (relative values like "昨天" or absolute dates). Define a Message Type column — the AI classifies each visual element as red packet card, transfer card, text message, or system notice. These native metadata fields populate alongside your content fields in the same row, so a single screenshot of a red packet conversation yields both the ¥88.00 amount and the sender's name and timestamp in one pass.
Can I process WeChat chat screenshots alongside screenshots from Alipay and other payment apps in one batch?
Yes. Define your columns once — Amount, Counterparty, Date — and upload WeChat chat screenshots (red packets, transfers, address messages) alongside Alipay payment screenshots and other app screenshots in the same batch. The AI adapts to each app's visual layout independently because it reads each field by semantic role and visual structure, not by checking a fixed position. The output is one .xlsx file with consistent column headers across all sources.