How to extract data from emails

By setting up automated processes, you can ensure data constantly flows into your systems in real time or on a set schedule. Here’s how you can implement these techniques effectively. 

Real-time data extraction

Automating real-time data extraction means data is pulled from emails as they arrive, allowing your business to access and act on critical information immediately. So, if you’re handling support tickets, customer inquiries, or order confirmations, you can extract the data as soon as the email hits your inbox. This automation ensures that important information is instantly available in your CRM, database, or relevant application, helping your team respond quickly without manually triggering the process.

Scheduled parsing

For businesses that don’t need data extraction to happen continuously, scheduling periodic extractions offers an efficient alternative. Depending on your needs, you can configure extractions at specific intervals — such as every hour, day, or week. Scheduled parsing works well for less urgent data like marketing responses or routine reports, ensuring your databases and CRMs are regularly updated without the constant resource demand of real-time extraction. This helps balance workloads while maintaining current information.

Error handling and monitoring

When automating data extraction, having systems to ensure accuracy is crucial. Many data extraction tools handle specific types of information and ensure that only relevant, complete data is processed. 

For example, ExtractAI focuses on precise data extraction by scanning emails for e-commerce-related information, such as order details and shipment tracking. It only processes emails that contain all the necessary data, helping to prevent incomplete or irrelevant information from being extracted. By relying on tools like this, businesses can maintain a smooth, automated data extraction process with minimal manual intervention, reducing the risk of handling inaccurate data.

Once you’ve extracted valuable information from emails using ExtractAI, organizing and storing that data is the next step to ensure it’s actionable and accessible for your business operations. Here’s how to export, categorize, and store your extracted data in ways that maximize its utility.

Exporting data to CRM or database

Export data using ExtractAI to your preferred CRM system, spreadsheet, or database. Whether you’re managing customer information in Salesforce, tracking orders in a spreadsheet, or storing communication logs in a custom database, ExtractAI simplifies the integration. You can automate the data transfer through API calls or export the data manually in a format of your choice (e.g., CSV). 

Data categorization and tagging

Organizing your data is key to making it easy to retrieve and act on. ExtractAI allows you to categorize and tag extracted data based on custom rules. For example, you can tag emails based on the type of inquiry — such as ‘support request,’ ‘order confirmation,’ or ‘feedback’ — making it simple to sort through large volumes of data later. Tagging also enables faster filtering and reporting, so if you need to pull all emails related to a specific product or issue, the tags will allow for quick and easy retrieval.

Data formats and compatibility

ExtractAI supports a range of export formats to suit different business needs. You can export your data in:

• CSV: Ideal for use in spreadsheets or uploading into various platforms like CRMs or data analysis tools. It’s a simple format for handling structured data.
• JSON: This format works well for developers and systems that require machine-readable data. JSON is perfect for API-based integrations, allowing you to send data directly to other software applications or workflows.

API calls: If your business uses a more dynamic, real-time integration approach, ExtractAI supports exporting data via API calls. This allows for seamless and automated data transfers between ExtractAI and your backend systems.

Setting up email parsing with ExtractAI can help you get the most value from your email data. Whether you’re looking to automate processes, gain insights, or organize data from various inboxes, ExtractAI simplifies extracting the specific information you need from incoming emails. 

Let’s walk through how to configure ExtractAI, handle different email formats, and customize your extraction rules to suit your business needs.

Initial configuration: Starting with a proper setup ensures you capture the correct data. To configure ExtractAI, connect your email accounts securely through the Nylas platform. Once you make the connection, select which inboxes or folders you want to monitor for incoming data. Then, define the type of information you want ExtractAI to pull — customer details, order numbers, or any other key data points. With your configuration in place, you can begin parsing emails immediately.

Email templates and formats: Emails come in many shapes and sizes, and ExtractAI handles that variety. Whether you’re dealing with plain text emails, HTML layouts, or complex transactional templates, ExtractAI can accurately extract the data you need. For instance, if you’re parsing confirmation emails from different vendors, ExtractAI will seamlessly recognize and extract essential information like totals, shipping details, or tracking numbers, even if each email looks different.

Customizing extraction rules: ExtractAI’s flexibility allows you to set custom rules for precise data extraction based on your specific needs. If you’re tracking customer names, order numbers, or sentiment from email communications, you can easily configure rules to focus on these elements. For example, you might set a filter that flags emails containing specific keywords or captures certain data fields, like a product ID or feedback sentiment. This level of customization ensures you’re not just extracting data but extracting the right data for your business.

Extracting valuable insights from emails requires more than parsing the data. You need advanced techniques to gain deeper insights and drive meaningful actions beyond pulling simple data points. Here are some methods you can use with ExtractAI to get the most out of your email data: 

Keyword and phrase recognition

One of the simplest yet powerful techniques is identifying and extracting specific keywords and phrases from emails. Consider setting up keyword recognition for terms that matter most to your business, such as product names, support inquiries, or high-priority actions. For example, if your customer service team receives inquiries about specific products, flag those emails and pull relevant product names, allowing your team to respond faster. This technique is ideal for categorizing emails and routing them to the correct department.

Structured vs. unstructured data

Emails can contain structured data, such as forms and tables, and unstructured data, like free-text messages. Handling both types efficiently is crucial for extracting valuable information.

• Structured data: Use ExtractAI to parse structured data in a table or form submission, such as order details. This data is straightforward to capture and can be used directly in your workflows — logging orders or processing invoices.
• Unstructured data: Unstructured data, such as customer feedback or open-ended inquiries, presents a larger challenge. ExtractAI uses advanced parsing techniques to extract relevant information from free-text emails. For example, it can recognize a customer’s issue from an unstructured email and categorize it under “support” or “billing” based on the context.

Using natural language processing (NLP)

To dive deeper into email content, ExtractAI employs natural language processing (NLP) to extract more complex insights. NLP allows you to analyze free-text emails to understand:

• Sentiment: Determine whether an email’s tone is positive, negative, or neutral. This can help you prioritize responses to dissatisfied customers or flag positive feedback for marketing.
• Intent: NLP can identify the intent behind an email, such as whether the sender is making a support request, placing an order, or requesting information. For example, an email that says, “I need help with my subscription,” would be tagged as a support inquiry.
• Actionable requests: ExtractAI can also detect actionable requests hidden within emails, such as refund requests, upgrades, or changes to account settings. You can streamline responses and improve customer satisfaction by automatically recognizing these actions.

To illustrate how businesses can leverage ExtractAI to automate email data extraction, let’s explore two practical examples that showcase its capabilities.

Consolidating purchase information for customers

A business could use ExtractAI to automatically retrieve and consolidate purchase information from customers’ email communications. Consider a personal finance app that helps users track their spending across online retailers. By integrating ExtractAI, the app can connect to the user’s email inbox (with their permission) and parse incoming order confirmation emails. 

ExtractAI extracts key details such as order dates, order numbers, itemized purchases, and total costs. This information is organized within the app, giving users a comprehensive view of their online spending habits. By automating this data extraction, the app enhances user experience by saving time and providing valuable insights into purchasing behaviors.

Streamlining shipment tracking for e-commerce platforms

An e-commerce business could use ExtractAI to automate the extraction of shipment tracking information from emails sent by suppliers and shipping carriers. Instead of manually processing each email to retrieve tracking numbers and carrier details, ExtractAI parses incoming emails to extract this information in real time. The extracted data is then automatically fed into the company’s order management system, updating shipment statuses and informing customers about their delivery progress. 

Using ExtractAI, the business reduces manual workload, minimizes the risk of errors, and improves customer satisfaction through timely updates.