Postal Address Matching & Deduplication of Address Lists & Databases

With this desktop app, duplicate addresses are deleted, ensuring that when you run a marketing campaign, each recipient receives only one copy of your mailing. What’s more, you can have it take opt-out lists into account. And it lowers the cost of compiling and maintaining address lists. Not only can you do the data clean-up yourself, it will cost you very little time and money. So why wait to benefit from our software for postal address deduplication?

Try it now for free! Download now!

( Release date: 4/1/2018 )

Detects duplicate postal addresses despite ...

  • Typos
  • Spelling variations
  • Omissions and additions
  • Misplaced words
  • Abbreviations

Fast, flexible and user-friendly:

  • No technical knowledge required.
  • Local processing of data, no need to transfer data to an external service provider.
  • Data source (address lists and databases): Excel, Access, MS SQL Server, ORACLE, MySQL, MariaDB, IBM DB2, PostgreSQL, OpenOffice Calc, LibreOffice, dBase, VistaDB, CSV files and text files.
  • Can also be used for large databases.

Everything you need for data clean-up:

  • Postal address deduplication inside a table.
  • Postal address deduplication between two tables, for example, to consider blacklists or to synchronise address lists.
  • Search for duplicates by postal address (fuzzy matching), phone number, email address or any other criteria.
  • Fuzzy / error-tolerant matching can deal with company names as well as addresses of private persons.

Numerous opportunities of using the result:

  • The duplicates can be deleted in the source table. Alternatively, the cleansed data can also be written in a new file.
  • The found duplicates can be marked in the original table.
  • The result can be used to enrich data. For example, a telephone number from a second table could be transferred to the first table using the matching result.
  • The result can be processed using the functionality of any stored procedure from the database.
  • Various protocols and lists can be created.

Other functions for quality improvement:

  • Detect gender based on first name.
  • Determine the salutation of a letter.
  • Delete selected data records.
  • Correct the postal code format.


Example: Score  
Albert Einstein    
= Einstein Albert 97%  
= A. Einstein 95%  
= Albert Einssein 94%  
= Abert Meinstein 86%  

Our software products:


DataQualityTools 4.2

Compared to DeduplicationWizard, DataQualityTools offer more options to find duplicates and also a whole series of additional functions to process address data / address lists / mailing lists, such as a function to merge data fields and a function to determine the gender based on the first name from the address. In addition to Excel files, the program can also process dBase, ACCESS, OpenOffice / LibreOffice Calc,  VistaDB, CSV and text files as well as database servers such as MS SQL Server, PostgreSQL, ORACLE, IBM DB2, MariaDB and MySQL. further information ...


DeduplicationWizard 4.2

A simple software that can be used without any special technical knowledge to clean / dedupe Excel files. Duplicates, especially duplicate addresses can be found using the postal address, the telephone / telefax number and/or the email address, either within a single address list or between two address lists, such as is required for the consideration of e.g. Robinson lists, MPS lists or opt-out lists. When the deduplication is based on the postal address – i.e. name, street, postal code and city – the program then also considers typos, inverted words and additions. It is then a fuzzy / error-tolerant matching. further information ...


BatchDeduplicator 4.2

BatchDeduplicator contains essentially the same functions as DataQualityTools to dedupe lists. Like with DataQualityTools, large databases (data sources: EXCEL, ACCESS, dBase, OpenOffice / LibreOffice Calc, CSV files and text files, VistaDB  and database servers such as MS SQL Server, MySQL, MariaDB, ORACLE, IBM DB2 and PostgreSQL) can be processed, several million records generally do not represent a problem. The projects can be scheduled and provided with a time of execution, to thus be carried out e.g. every Tuesday at 5 pm. further information ...

Better data doesn’t have to be expensive.