Retrieve Sender Name, Timestamp & Order Details from Any WhatsApp Chat Screenshot
Manually copying a customer's order number, address, or bank details from a WhatsApp chat screenshot takes about a minute of switching between apps — this extracts content fields plus chat metadata (sender, timestamp, message type, read status) into your spreadsheet in 5 seconds.
5-10s per screenshot · Up to 99% accuracy on printed text
What You Can Pull from a WhatsApp Chat
There is no receipt screen in WhatsApp — data sits inside chat bubbles. With Custom Column Extraction, the AI finds each field by meaning, not by a layout that doesn't exist.
Identified by labels like "Account:" or "Phone:" and digit patterns in the message.
Read from the chat header or bubble label — stable across all conversations.
Found by labels like "Order #" or "Ref:" — works regardless of sender formatting.
Read from phrase context like "deliver to" — separates deliveries from casual mentions.
Read from the grey text below each bubble. Resolves "Yesterday" or "2:30 PM" into consistent date-time values.
Identified by the bubble layout — text, image, document, or voice — as shown in the chat UI.
Why a Chat Bubble Is Harder to Parse Than a Receipt
Payment apps and e-commerce sites show transaction data on a structured screen — a card with labelled fields, a confirmation page, a receipt PDF. WhatsApp gives you a chat bubble. The data is there, but it's mixed with conversation, emojis, timestamps, and metadata indicators.
No Confirmation Screen Exists
There is no "Order Received" card with fields in boxes. A WhatsApp order looks like "Hi, I want 2 t-shirts size L — deliver to 45 MG Road, Bangalore. Order #42." The phone number, address, and order reference are all in one sentence, not in separate form fields.
Every Sender Formats Differently
"Pls deliver to 123 MG Road, Order #42", "Address: 45, 3rd Cross, Indiranagar — reference order 42", "Account: 123456789, Amount: 500." There is no standard template. A tool that matches fixed positions fails immediately; a tool that reads by meaning adapts to each sender's wording.
Read Status Is a Visual Icon, Not a Text Label
WhatsApp shows delivery status as check mark patterns — single grey (sent), double grey (delivered), double blue (read) — with no text description. A tool that only reads text characters cannot tell delivered from read. The AI reads the check mark pattern from the chat interface and records the read or delivery status as a structured field.
Semantic Extraction Reads by Meaning
You define a column called "Address" and the AI reads the sentence structure — "deliver to 45 MG Road" — to identify the address. It knows the phone number is a separate thing because "phone: 9876543210" is used differently in the sentence than the physical location.
Format-Independent Matching
"Order 42", "Ref: 42", "PO-42", or just "42" in a conversational context — the AI identifies the order reference by its relationship to other text and labels, not by checking a fixed position in a document. No template, no training, no per-sender configuration.
One Column Set for All Chats
Define your columns once — Phone Number, Sender, Order Reference, Address — and process unlimited WhatsApp screenshots from different conversations. Business orders and personal bank details go into the same batch, the same column mapping, and one unified spreadsheet.
From a WhatsApp Chat Screenshot to One Structured Row
Three steps is all it takes to turn a screenshot of any WhatsApp message into structured spreadsheet data, with no manual copying between apps.
Upload the Screenshot
Drag a WhatsApp chat screenshot — JPG or PNG — into the upload area. The screenshot can be from WhatsApp Messenger or WhatsApp Business, showing any part of a conversation that contains the data you need.
Name Your Columns
Type the column names you want — "Phone Number", "Order Reference", "Address", "Sender Name", "Timestamp", "Message Type". The AI reads the message content and the chat interface — sender name from the header, timestamp from the bubble label, each content field from the message text — and fills the right cell.
Export to Excel
Every screenshot becomes one row in your spreadsheet. Upload a batch of WhatsApp screenshots from different customers and get a single .xlsx file with all the phone numbers, order references, addresses, and sender names ready to use.
When It Works Best — and When to Be Cautious
- ✓ Messages where data has clear labels like "deliver to", "Account:", or "Order #" — giving the AI semantic cues to classify each value.
- ✓ Screenshots with one or two relevant messages, not multi-page scrolls. The AI can isolate and extract fields from a focused conversation segment with high accuracy.
- ✓ English or Latin-script text with clear fonts produces the highest accuracy.
- ⚠ The AI extracts specific named fields — not a full transcript. For complete chat history with timestamps and ordering, use WhatsApp's built-in export feature.
- ⚠ Heavily compressed or resized screenshots (common when images are forwarded through WhatsApp multiple times) can reduce OCR accuracy on small text like 10-digit phone numbers or reference codes.
- ⚠ Non-Latin scripts (Arabic, Devanagari, CJK) are supported but accuracy depends on font clarity — test a sample before large batches.
- ⚠ Screenshots only capture the visible chat UI. Read receipts and timestamps that scrolled off screen are not present and cannot be extracted. Only metadata visually rendered in the screenshot is extracted.
Frequently Asked Questions
Real questions about extracting data from WhatsApp chat screenshots.
Can the AI tell the difference between a delivery address and an address mentioned in casual conversation?
Yes. The AI reads the semantic context around the address — phrases like "deliver to", "send it to", "ship to", "my address is" — to determine whether the location is a requested delivery point or just a casual mention. If the message says "I live near the park on MG Road" without delivery intent, the address is not extracted into the Address column.
A customer sent their bank account number and sort code on WhatsApp — will the AI extract both correctly?
Yes. Define "Account Number" and "Sort Code" as two separate columns. The AI reads the labels in the message — "Account: 12345678" and "Sort Code: 12-34-56" — and maps each number to its correct column. Traditional OCR would see two numeric strings with no way to tell which is which; semantic extraction reads the label context.
What if the WhatsApp screenshot contains multiple messages from different customers in one image?
The AI processes the screenshot as one upload and extracts one set of fields per image. If a single screenshot shows multiple conversations or messages from different customers, we recommend cropping or capturing focused screenshots — one order or one set of bank details per image — for clean per-row results in your spreadsheet.
I have 20 sales promoters sending WhatsApp orders — can I automate this without manually uploading each screenshot?
You can batch upload multiple WhatsApp screenshots in one go — the tool processes them all with the same column definitions and outputs a single Excel file. For a fully automated pipeline, use the v1 API to upload screenshots programmatically, or set up a Collection Link (a shareable upload URL) that sales promoters can use to submit their screenshots directly into your processing queue without you handling each file.
Can the AI extract timestamps, message types, and read status from a WhatsApp chat screenshot?
Yes. The AI reads the chat UI elements — the timestamp text below each message bubble (resolving relative times like "Yesterday" or "2:30 PM" into consistent date-time values), the message type indicator from the bubble layout (text, image, document, or voice), and the read status from the check mark icon pattern (single grey for sent, double grey for delivered, double blue for read). Define a column called "Timestamp", "Message Type", or "Read Status" and the AI extracts that metadata from the visible chat interface alongside your content fields.