Many organisation are working with poor customer data on a daily basis and are unaware of the impact of their customer data not being in standardised name and address field.
For instance, data8 has been approached on many occasions to cleanse a customer database prior to a mailing.
The client will want to suppress goneaway and deceased records and take advantage of any forwarding addresses that can be provided to ensure valuable relationships are not lost. However, is the way the data is structured important?
Absolutely yes.
The actual format the data is provided in doesn't usually provide us with a problem due to the wide range of data formats we can accept. We are also able to accept separate data fields or one field containing all address elements. However, if the data structure changes throughout the file it can create a whole host of problems.
If you can imagine the data is provided as the following:-
Title, Forename, Surname, Address 1 , Address 2, Address 3, Address 4, Post Code
part way through the file the data changes to:-
Surname, Title, Forename, Address 1 -4, Postcode
In order for us to process the data against our suppression services, it is important for us to understand where name and data fields occur and map the data accordingly. If we import the name field as a Surname and it changes to a Forename part way through the file, our automated processes will think the Forename is the Surname and make limited or inappropriate matches.
Even more significant if you send your data to print in this format, the mail merge will also make the same errors and print the mailing inappropriately.
However, all is not lost. Using our experienced bureau services team, we can run filters and programs on your data to ensure not only is it structured correctly for mailing purposes, but you will get the best possible match rates for data cleansing and improve your overall campaign effectiveness.
Call our sales team now to talk through all your data challenges and find a solution for data standardisation.