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Data cleansing and International address standards

What is UPU S42 and why should you care?

We are proud to say our data cleansing solutions (On-Demand Data Cleansing API and Batch Data Cleansing Service) are UPU S42 compliant. But as I type that, I can feel your smile glazing over. So let’s break it down and see why this is so important and what it means for your data.

First of all what does UPU stand for? The Universal Postal Union is the second oldest international organisation in the world, founded in 1874. (Out of interest, the oldest is the International Telecommunications Union, founded in 1865). With 192 member countries, the UPU’s mission is to bring standardised and efficient postal systems to countries around the world. The organisation helps member countries to develop and implement addressing standards and grow their mail, parcel delivery and financial services. The UPU acts as a forum for international discussion and collaboration in the postal sector.

UPU S42 is the international addressing standard developed by the UPU’s Postal Operations Council and experts from its Addressing Group. It comprises two sections, first breaking down postal addresses into the generic component parts commonly used by all UPU member countries.


The second section on UPU S42 provides templates of precisely how these component parts are arranged according to the standards of each country. With over 200 different addressing systems in the world, this database is vital, providing a framework by which international shipments can be efficiently processed.
The UPU S42 templates are embedded into our data cleansing solutions, on top of the gold-standard global data sources we use for all of our validation services. This means that the addresses in your customer database are not only validated but also reformatted, where necessary, to the precise standards of their country. This is particularly important if you are dealing with customers from multiple different countries.

A very simple example of this will be addresses in Germany where the street number generally comes after the street name in local addresses. If somebody in the UK types in a German address they may use their own local form and place the street number first. After data cleansing, the address will be formatted in the standard format for Germany.

Locally formatted address

Hienz Wolff
167A Königstraße

Standardised address for Germany

Hienz Wolff
Königstraße 167A

Why is this important?

Your forms will collect data in your chosen format, likely the standard format of your country’s address system. While the content of the data captured is technically valid, it may be in the wrong order for the destination country which could cause delays in delivery. 

Installing an on-demand data cleansing API will verify the format of every address as an automatic step in your data processing system. This is a particularly vital process for logistics and fulfilment companies who do not capture address data directly from the customer but receive orders via retailers.

Validating the address data provided and ensuring the correct format for the destination country will streamline shipments and reduce lost or delayed deliveries.

For more information on our On-Demand Data Cleansing API and out Batch Data Cleansing, head over to our product pages. If you have any questions don’t hesitate to get in touch, our team of experts are always happy to help.

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About Fetchify

We are a pioneer in SaaS address lookup and data validation solutions. We process millions of data transactions each day for thousands of clients ranging from small e-commerce startups to large household brands such as Heinz and RBS. Our flagship products Address Auto Complete and Postcode Lookup reduce friction on checkouts, leading to increases in conversion rate of up to 40%, and helps reduce failed deliveries by as much as 75%. Since launching in 2008, we have differentiated by our ease of integration and exceptional support. We provide a full suite of data validation solutions including Phone Validation, Email Validation, UK Bank Validation, and Data Cleansing.