~ by Christoph Scholze, International Sales Manager, at Deutsche Post Adress GmbH & Co. KG.

Importance of Data Quality

In many companies, data quality management is considered as a possibly necessary but rather annoying and expensive entity. Although many believe this to be true address data quality does not end in itself. A return is not only considered a waste of postage, but that a customer can not be reached and thus will not consider a vendor for the next purchasing decision. Hence, not reaching the customer will ultimately lead to a loss in sales, which again results in lower revenues.

Holistic Address Management

This is not new. In the last couple of years, more companies have started to care about their data. Data has been cleaned and sometimes also updated in advance to mailings. Therefore, a mailing list or customer database has been sent to a bureau service provider who processes and sends a cleaned file back. But how does a company know what processes are necessary? How to decide which data to clean in which way? How to extract the data from the database and how to reintegrate them again? Furthermore, what is the reason for the bad data quality? Is the customer regarding purely symptoms or the cause as well.

All these questions lead to the fact that, in the past, bureau service providers were mainly producing ‘data tons’. They sold their product, cleaned the database, but left their customer alone with that raw data and without any advice on how to improve the overall process or what to do with the data.

This brings us to the conclusion that address data management should be seen from a more holistic perspective: to deliver a solution for the challenges of address management to the customer. The solution provider should solve the problem and implement the solution into the customer’s systems.

One way to do this is to consider the customer lifecycle and to think about where to deal with an address and how it may change over time. Therefore, six stages on the customer lifecycle were developed:

  1. First and foremost, a prospect needs to be approached. This can be done by mail, telephone or email – but in any way one needs updated contact information.
  2. After a prospect has been successfully approached and reacts with a requirement for further information or a purchase, the new customer’s contact data – name, address, telephone number – need to be captured correctly and efficiently. If mistakes occur at this stage it may be extremely difficult or even impossible to correct this later.
  3. The contact details – captured correctly and stored in the database – now have to be managed and the right systems to host a database need to be chosen. The data need to be extracted and reintegrated into the database. For all of these processes business rules need to be defined.
  4. Customers move or marry, streets get renamed or telephone numbers become obsolete – data can change over time. Thus, a database needs to be updated regularly to capture those changes and to be able to still reach a customer. Therefore, updating routines and frequency need to be applied – another business rule.
  5. If an address can’t be updated because there is no new known address or a person has died, it is necessary to stop mailing to that address.
  6. Some ‘undeliverable’ addresses might be so valuable it could be worth actively researching them, to find a good customer or maybe a debtor. Those records need to be chosen – again something to be defined in the business rules.

Not all companies see their challenges for data quality management in those same stages. Thus, they need to be adjusted to suit individual needs.

A solution process consisting of four phases helps to approach each stage. First, the customer’s requirements need to be identified. Then a workshop should be held where information can be gathered to develop recommendations and a solution for those identified requirements. Thirdly, the solution for each stage should be implemented and the fourth step will ensure a trouble-free operation with regular monitoring in the future.


An holistic approach to address data quality management ensures high data quality and, hence, availability of customers. This increases not only the customer value but also leverages the total value of a company since sales volumes and revenues can be increased too.

Deutsche Post Adress, with its international Business Unit POSTADRESS GLOBAL, is a pioneer in this new field of address quality management on an international basis. This year, POSTADRESS GLOBAL has released ‘International Data Quality Solutions’  – an holistic approach to address data quality management, as outlined above.


Light has indeed been shining on Greece in the news a significant amount in recent months. Not all of the news has been favorable; from rolling labor union strikes to the International Monetary Fund and Eurozone governments providing Greece emergency short- and medium-term loans worth $147 billion so that the country could make debt repayments to creditors (source: World Factbook).

Not all the news out of Greece is cast in this negative light. A number of Global-Z clients have been seeing significant growth and opportunity in this important Southern European market so they came to us for help. As client demand calls for research and development into markets for which Global-Z was previously providing formatting only (i.e., not address validation) we listen. The result? We now have a Greece module thanks to our hard-working R&D team. That is, not only can we format postal data to the standards of the Greek postal authority-Hellenic Post-but much more.

Here are the main features of the new Global-Z Greece module:

  • The new module supports address validation and correction on both Roman-text (English) and Greek-text names and addresses (ονόματα και τις διευθύνσεις).
  • Global-Z’s proprietary software utilizes up-to-date data containing 1,200 postcodes, 11,000 towns, cities and districts, and over 13,000 streets and building number ranges in the largest towns and cities in the country.
  • New capabilities also include name parsing, genderization, phone and email standardization.

While results vary from data set to data set, validation rates can be expected to be in the 75% plus range. Currently street-level data are available for the largest towns and cities.

Contact Us to test Greece today!