In today’s fast-paced world, businesses need data to flow seamlessly across multiple formats and platforms. And since manual data entry is often cumbersome and costly, an entire market of automation tools has arised and grown over the years. Nowadays, a quick search on Google will show you a plethora of websites and applications that can extract data from documents. This is a huge boon for productivity… assuming you have found the right solution for your needs.
The truth is, some document data extraction tools, while very effective at extracting data with great accuracy, can be challenging to use. Configuring the extraction rules (also known as parsing rules) to work exactly how you want them isn’t always simple. You might have to go through a lot of trial and error to get it right. So in this post, we’ll examine how Docparser simplifies document data extraction to make it easy, quick, and reliable.
Why businesses struggle sometimes with data extraction
Undoubtedly, there are many data extraction tools with amazing capabilities. While they are built for the same overall purpose, they don’t necessarily work in the same way. Some of these tools require coding skills while others don’t. Also, some of them rely on logic-based rules set by the users, while others use AI that reads documents and extracts data, then retrains itself to improve accuracy based on human feedback.
Both types of document data extraction tools can deliver amazing results, but there is a chance you will run into an issue or two while using a given tool.
Configuring the parsing rules
Some tools use AI to automatically create parsing rules based on a sample document. So you upload a document, wait for a moment, then check the extraction results and rectify them if needed. Granted, this is convenient and works great in many cases. But depending on the complexity and uniqueness of your document type, the setup process may be fast or slow. Common documents like invoices are fairly easy to parse by AI. However, there are cases where AI will make wrong guesses while trying to extract data fields, so you will have to rectify those mistakes before validating the model.
On the other hand, there are rule-based document parsers that work perfectly for some use cases, but not so well for others. They might be missing some specific functionalities for certain complex scenarios. So, whichever solution you decide to use, you need to make sure that it can extract data from your documents accurately and without extensive post-processing cleanup.
Integrations with existing systems
Extracted data doesn’t have much use if it sits within your data extraction solution. Whether it’s order details, lead data, a table, a customer message, or anything else, you need to move it to your systems to be able to use it.
So it’s important to check the integration options of a document parsing tool before investing in it. An integration with an application or platforms means that you can send extracted data to that app or platform. For instance, you should be able to export data to a Google spreadsheet, a CRM, or an ERP system. Hopefully, the data mapping settings aren’t confusing.
While you may not find an integration for a specific app that you use, that won’t be a problem if your document parser integrates with a third-party platform that can send data to your app. The most popular example is Zapier, an app designed to move data from one to the other. If a document parsing tool includes a Zapier integration, that means you most likely can export data to virtually any cloud application through Zapier.
So if you decide to use a document extraction solution that doesn’t provide an integration for your existing system, this might result in a lot of trial and error trying to build a bridge between your document parser and your system. Instead of trying to fix this on your own, it’s better to choose a solution with integration options that allow data to go where you need it to be.
How does Docparser simplify document data extraction?
The two issues we explained occur sometimes when a company invests in a document extraction tool that is not entirely adequate with its specific needs. So the company must either figure out a workaround or switch to another solution.
If you encountered similar challenges before while using a document parsing tool, you might want to give Docparser a try. Here is how Docparser simplifies document data extraction to make it painless and reliable.
Customize your parsing rules freely
Docparser gives you complete freedom to set up parsing rules so that each data field is extracted with complete accuracy.
Here’s the gist of how it works: you upload a sample document, and then create a parsing rule for each data field. To create a rule, you draw a rectangle around the data you want and it gets extracted. Then, you can add filters that organize and clean up the extracted data as needed. Want to extract a person’s name? Simply outline the name on the document.
After selecting a data field, you can chain up multiple text or table filters to customize the parsing results to perfection. For example, you can do the following:
- Extract email addresses, phone numbers, or specific keywords
- Remove unneeded text or blank spaces
- Search and replacing specific text
- Change the structure of a table
- Merge table rows or columns
- Change the format of dates and numbers
- Change capitalization
- And more
Furthermore, in case a user hits a roadblock while trying to set up their parsing rules, they can always ask for help and even request a dedicated assistant who will create all parsing rules for them.
Streamline document-heavy workflows with integrations
To make data flow seamlessly from your documents to your systems, Docparser has a large number of integration options. In addition to integrating with commonly used cloud apps like Google Sheets and OneDrive, you can export parsed data to virtually any cloud app via third-party platforms, most notably Zapier.
Alternatively, you can download parsed data as a file in multiple formats and import it into your system. You can even connect your Docparser account to a URL endpoint via a webhook integration. It’s all up to you!
Overall, this large variety of integrations ensure a smooth and efficient flow of data between documents and business systems. Docparser will fit easily into your existing workflows to make them easier, faster, and ultimately more profitable.
In conclusion
To make the most out of automation, you should choose tools that not only deliver the results you want but are also easy to use. Otherwise, users will find themselves spending a lot of time trying to get a tool to work as needed, which defeats the purpose of investing in it in the first place.
You may have used some document parsing solutions before. If you weren’t entirely satisfied with them, give Docparser a try.
Docparser simplifies document data extraction by making it easy to learn and accessible to any person in your organization. Users don’t need coding knowledge and won’t have to go through an arduous learning process or spend time fixing unexpected issues. In addition to having an intuitive point-and-click interface and providing plenty of learning materials, you can always request assistance to get your custom document parser set up for you.
