Nowadays, as the number of firms grows, competition is at an all-time high, requiring enterprises to develop novel marketing strategies.

Apart from digital marketing trends, SMS marketing and telemarketing have also become crucial marketing channels. But organizations need to have a huge database of phone numbers to leverage these channels.

There are millions of phone numbers dispersed throughout thousands of emails and websites, each with its unique structure and format. So, how can you quickly extract this treasure trove of contact info without any programming knowledge?

This is where phone number extractors can help.

Build a custom phone number extractor workflow with Nanonets. Automatically parse phone numbers from emails, documents, websites etc.

A phone number extractor is a data parser that retrieves phone numbers from emails, attachments and websites regardless of its format.

Once extracted, the phone number data can be imported into your preferred business application.

Once you’ve configured your settings, the phone number extractor can automatically grab data from multiple sources. This does away with all manual effort, freeing up your time for more productive activities.

What is a Data Parser?

Data parsers transform unstructured or unreadable data into well-structured and simple to understand data.

Data parsing is the method of processing strings of letters, special characters, or data formats. And then organizing the data based on some user-defined criteria.

In other terms, it is a way of extracting and filtering data from files.

How to Find and Extract Phone Numbers?

You must first identify the sources from which you would like to extract the phone number data. Are they public databases, or websites or emails you receive routinely?

Next, you can either select an email parser, a web scraper or phone number extractor to set up an extraction workflow.

In an ideal setup the software will monitor all your sources routinely. And it will automatically parse all sources to only extract phone numbers based on certain pre-set criteria. The extracted data can then be filtered, edited, refined or processed and saved in a prescribed format.

This data can then be imported into CRM or ERP software to enrich leads or provide new prospects.

Build a custom phone number extractor workflow with Nanonets. Automatically parse phone numbers from emails, documents, websites etc.

Let’s find out how you can set up an automated workflow with Nanonets to extract phone numbers. Here are the steps:

Create an account

Sign up to get started with Nanonets.

Upload a few sample files and mark the phone number(s) that you want to extract. The AI will learn to identify phone numbers based on the examples you show – the more the better.

Screenshots of emails or web pages will do just fine. Test the custom extractor with new files to see how it works.

Define the source(s)

If emails are your primary source, then set up a Nanonets receiving address and auto-forward all relevant emails to that email id.

If websites are your primary source, Nanonets can be set up as a web scraper to extract data from dynamic web pages.

You can also set up an automatic import of files from cloud storage, databases or connect via API.

Set up the workflow

Create the entire workflow by connecting the source to the custom data extractor you built. You can also define parsing rules to process the extracted data into an appropriate output format.

Finally define the destination that you would like to export the refined data into. You can export the data directly into CRM or ERP software via Nanonets’ API.