In merging addresses and eliminating duplicates, the following goals can be differentiated:

File Cleansing
In this application, the duplicates are tracked down in their own files and eliminated.
In some applications it is recommended to consolidate the data connected with the duplicates with each address remaining in the file.

Cleansing of Foreign Lists
This is for comparing one or more "foreign" data files (potential addresses) against a reference file, frequently against own address files, in order to rent only those addresses for a mailing that do not belong to one's own customer list or to load only those sets of data in the databases of prospects that are not yet contained there.

List Mixing
Several files that are managed independently of each other (lists) are purged of duplicates internally and are checked against each other. The lists then no longer overlap and can be used i.e. to construct a data warehouse or are available for a mailing campaign.

View or Cluster Check
In this duplicate comparison, no elimination of the found duplicates occurs. Instead, different "cluster views" are automatically created in the database and in many cases, the thus formed "cluster identifications" are put into the database.

Negative Comparison
Particularly in the mailing sector, negative comparison plays a significant role. All addresses are eliminated that are in the negative file. (Examples for this are risk files or also the Robinson list, which is a list consisting of people who do not wish to receive advertising.)

Positive Comparison (Data Enhancing)
Positive comparison pursues the goal of an "agreement". In a stock of addresses the ones to be "confirmed" are those that are found there in one or more files. As a rule, the goal of data enhancing is pursued here to integrate information from other files into one's own customer or propect base such as telephone numbers, interests, etc.

To enable the user to attain the various goals as easily as possible, mailBatch differentiates between different "types" of address lists. It recognizes own, foreign, negative and enhancing lists.

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