What should a new Global-Z client understand or know about international mailing?
One of the most difficult aspects of ensuring good data quality practices is developing effective measurement techniques for evaluating the quality of your data and the impact of data quality improvement efforts. Just as an example, mailers often assume that if they aren’t receiving any returned mail, their data quality is probably ok. However this can be misleading, since depending on how mail is sent the mail delivery service provider may or may not route undeliverable mail back to the mailer, unless specific steps are taken to ensure that this occurs. A highly effective and strongly recommended practice is to include “seed” names and addresses in any international mailing, in order to evaluate the rate of delivery, total time of delivery, condition of the delivered mailpiece, and similar factors. As another example of the difficulty in measuring results, developing quantitative metrics for evaluating data quality can be very challenging, since comprehensive addressing standards gene
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