Parse, Validate and Standardise Mailing Addresses
A lot of our customers use mailparser.io to automate their e-commerce order fulfilment process. Another popular use-case is to extract contact details from e-mails, for example real-estate buyer leads which our customers receive from platforms like Trulia and Zillow.
Both use-cases have one thing in common: They involve parsing, verification and normalisation of postal addresses.
In other words, our users often want to transform a text block containing a shipping address, a billing address or the location of a property into individual fields like Street, Zipcode, State and Country.
As easy as it sounds, this has always been a very tricky and difficult task. Until today!
Today, we are happy to announce a new feature which allows you to turn an unstructured text block containing a postal address into individual fields. Take advantage of this feature today!
Look at the image below to see our new awesome mailing address normalisation service in action.
So why do you want to standardise and parse postal addresses?
An obvious reason for standardising postal addresses is an integration with your CRM system. Most CRM systems store mailing addresses in individual fields like Street, Zipcode, State, Country. So if you receive postal addresses as one assembled text block and you need to split up the text into individual fields, an address parsing service is what you need. Our address parser is capable of splitting up international mailing addresses so that you can easily store them inside your CRM.
Another reason is address validation. If crucial parts of the address are missing, our address parser will return empty values. You can then use this information to validate an address or mark it as not valid.
Why was address verification and normalisation difficult until now?
If you want to parse shipping or billing addresses from e-mails, chances are high that these addresses are in a unstructured, not normalised form. For example you will sometimes have an abbreviation for the state, sometimes it will be written out. All those little variations make it near to impossible to standardise a postal address with the standard rule based text filters offered by mailparser.io. Until now!
This is why we teamed up our friends at address-parser.net of us which offer an awesome postal address parsing API. By integrating their services into mailparser.io, it is now super simple to standardise any international mailing address and return the individual parts of the address.
How can I use this to parse shipping or billing addresses?
This new intelligent text filter can be used in the same way as our other filters. All you need to do is to isolate the text block containing the address by defining a start and end position. Once you’ve cut out the address text block, click on “Add Text Filter” and choose “Refine Results” and then “Normalize Postal Address”. Et voilà, what you get is your address split up in easy-to-use individual data fields.
We hope you enjoy this new filter which will allow you to easily transfer unstructured postal address into your CRM. And as always, please don’t hesitate to contact us if you have any questions or ideas.