How to Extract Data from Email to Excel
Wrestling with data stuck inside your emails is a common headache. Invoices, order confirmations, contact form submissions, and automated reports all arrive in your inbox, but getting that information into an Excel spreadsheet where it's actually useful often involves hours of mindless copy-pasting. We'll show you several methods to automate this process, freeing you from a tedious task and eliminating costly human errors. This guide will walk you through everything from simple built-in tools to more advanced, hands-off automation techniques.
Why Automate Data Extraction from Email?
Manually transferring information from an email to an Excel file is not just slow, it's a recipe for mistakes. A moment of distraction can lead to a skipped line, a misplaced decimal, or incorrect data entry, which can throw off your entire analysis. Most businesses need to pull data from recurring emails for a few common reasons:
Lead Management: Your website's contact form likely sends every new lead to your email. Manually moving these leads into a spreadsheet for a sales team is inefficient and can cause delays in follow-up.
Sales and Order Tracking: E-commerce platforms like Shopify or payment processors like Stripe send individual emails for every new order. Extracting this data allows you to create consolidated sales reports without having to log into different admin panels.
Financial Reporting: Logging invoices, receipts, and expense reports that arrive via email is essential for bookkeeping. Automation ensures nothing gets missed.
Monitoring Performance: System alerts, analytics summaries, and other automated reports often come via email. Pulling specific metrics from these emails into a dashboard gives you a centralized view of performance over time.
By automating, you create a reliable system that populates your spreadsheets consistently and accurately, giving you back time to focus on analyzing the data rather than gathering it.
Method 1: Using Outlook Rules and the Export Feature
If you use Microsoft Outlook, you can use its built-in features to gather emails together and export them as a CSV file. While this method isn't fully automated and requires some manual cleanup, it's a huge step up from copy-pasting one email at a time.
Step 1: Organize Your Emails with a Rule
First, you need to isolate the specific emails you want to extract data from. Creating a rule will automatically move these incoming emails into a dedicated folder, creating a clean data source.
Find an example email you want to track (e.g., an order confirmation from your website). Right-click it and choose Rules > Create Rule.
Outlook will suggest conditions based on that email. You can create a rule for emails from a specific sender, with a specific subject line containing certain words (like "New Order"), or sent to a particular address.
Check the conditions that apply. Then, check the box for "Move the item to folder".
Click "Select Folder" and create a new folder (e.g., "Website Orders") to store these emails.
Click OK to save the rule. You can also run this rule immediately on all messages already in your inbox to gather historical data.
Step 2: Export the Folder to a CSV File
Once your rule is set up and emails are collected in the designated folder, you can export the contents of that folder.
In Outlook, go to File > Open & Export > Import/Export.
In the wizard, select "Export to a file" and click Next.
Choose "Comma Separated Values" and click Next.
Select the folder you created in Step 1 (e.g., "Website Orders") from the list and click Next.
Choose where to save your file and give it a name. Click Next, then Finish.
Step 3: Clean the Data in Excel
The exported CSV file will contain your email data, but it will also have dozens of unnecessary columns for email-specific metadata like "Bcc," "Follow-up Flag," and "Importance." When you open the file, the crucial information is almost always in the "Body" or "Message" column, but it's still unstructured. You will have to manually clean this text or use tools within Excel, like Text to Columns, to parse the data from the body text into separate columns.
This method is great for bulk-processing hundreds of emails at once, but you will need to re-export the file periodically to get fresh data.
Method 2: Advanced Extraction with Excel Power Query
If you're comfortable inside Excel and want a much more powerful and refreshable solution, Power Query is the tool for you. Power Query (called Get & Transform Data on the Data tab) is Excel's built-in tool for connecting to, cleaning, and shaping data. You can use it to parse the unstructured email bodies from the CSV file you created in the first method.
Following this approach means you only have to build the query once. Afterward, you can simply re-export an updated CSV from Outlook and hit "Refresh" in Excel to automatically process all the new data.
Let’s say your email body looks something like this for every order:
Customer Name: John Smith
Order ID: FVT-12345
Product: Red T-Shirt - Large
Amount: $25.00
Here’s how you can use Power Query to pull out each piece of information into its own column.
Step 1: Connect Excel to Your CSV File
Open a blank Excel workbook.
Go to the Data tab >, From Text/CSV.
Find and select the CSV file you exported from Outlook. Click Import.
A preview window will appear. Click "Transform Data" to open the Power Query Editor.
Step 2: Isolate and Clean the Body Column
Inside the Power Query Editor, you'll see all the columns from your export. It’s noisy, so first, we'll declutter.
Scroll over until you find the "Body" column. This contains the content of your emails.
Right-click the "Body" column header and select "Remove Other Columns" to get rid of everything else. You might want to keep the "Received" date column as well, for chronological tracking.
Step 3: Extract Data Using "Column from Examples"
This is where Power Query feels like magic. "Column from Examples" lets you extract data by simply showing Power Query what you want, and it writes the formula for you.
With the "Body" column selected, go to the Add Column tab and click "Column From Examples". A new, blank column will appear.
We'll start with "Customer Name." In the first row of the new column, type what you see in the email body for the customer's name: John Smith.
Press Enter. Power Query will try to guess the pattern and automatically fill in the names for all other rows. If it's correct, you'll see names like "Jane Doe" and "Peter Jones" appear instantly.
Rename the new column to "Customer Name." Click OK.
Repeat the process for the Order ID, Product, and Amount. Just add a new "Column From Examples" for each piece of data, give it one or two examples, and let Power Query do the work.
Once you’re finished, click "Close & Load" on the Home tab. Your beautifully structured data will load into a new sheet in Excel. The next time you want to update it with new orders, just save the latest email export over your old CSV file and then go to Data > Refresh All in Excel.
Method 3: Fully Automated Extraction with No-Code Tools
If you want a truly hands-off solution that sends data from your inbox to Excel in real-time, no-code automation platforms like Zapier or Make.com are the answer. These tools connect your email account to thousands of other apps, including Excel Online and Google Sheets.
The general concept relies on a built-in email parser, which you train to recognize and extract data from a specific email layout.
How it Works: A Typical Automation Workflow
Choose a Trigger: New Email. You start by connecting your Gmail or Outlook account. Your trigger event will be a "New Email" that matches certain criteria (e.g., from a specific sender or has a particular label/subject).
Add a Parser Step: Extract the Data. You'll forward a sample email to a special email address provided by the automation tool. Inside their mail parser, you highlight the text you want to extract - for example, highlight "John Smith" and label it customer_name. You do this for every data point: order ID, amount, etc. This creates a template.
Set the Action: Create a Spreadsheet Row. Finally, you connect your Excel Online or Google Sheets account. You tell the tool to "Add a Row" in a specific worksheet. Then, you map the data extracted by the parser to the columns in your spreadsheet. For example, the customer_name from the parser goes into the "Customer" column, order_id goes into the "Order Number" column, and so on.
Once you turn this automation on, it runs silently in the background. Every time a new email meets your trigger criteria, the parser will extract the data and add it to your Excel sheet as a new row within seconds. This is the most scalable solution for businesses handling a high volume of structured emails.
Final Thoughts
Freeing data from your inbox empowers you to use it for meaningful analysis, from tracking sales trends to managing customer relationships. Moving from manual copying to using tools like Outlook rules, Power Query, or Zapier saves countless hours, reduces errors, and ensures your reports are always up to date.
This is where we built Graphed to help with the next step. After setting up a clean data pipeline - for instance, using an automation tool to send email data to a Google Sheet - you can connect it directly to our platform. Instead of wrestling with pivot tables or complex Excel formulas, you simply ask questions in plain English, like, 'Show me our top 10 products sold this month' or 'Create a chart of daily sales from our email orders,' and get live dashboards instantly. It automates the analysis and visualization, closing the loop from raw email text to actionable business insights.