The world of data processing can be confusing and full of unfamiliar terminology. To give you a helping hand we have compiled a list of commonly used phrases and their meanings:
The process of removing duplicated records from a set of data. Duplicate data can be identified by any one of a number of methods depending upon the quality of your data.
A list of records that you would like to have removed from your data prior to sending a mailing. These are most likely people who have unsubscribed to your mailings previously, but could also be people from segments of your customer base that you don’t want to market to right now.
If you have a large data set it is an unfortunate fact that some people will pass away. Obviously, you don’t want to send out items to these people. It costs money and you are likely to upset relatives. This process removes such people from your mailing list.
Every year 10% of the population moves house, in theory that means that up to 10% of your data is out of date within 12 months of collecting it. This process tracks those movers and flags them so you can remove them as required.
So, you’ve suppressed the people who have gone away, but that also means that you’ve removed a customer from your list. This process enables you to track those people who have moved and continue to target them.
Maybe there’s a specific demographic that you don’t want to mail to, that could be housing associations or people who rent. This suppression will identify and remove these people from your lists.
People can register their address against the MPS. This means that they should no long receive unsolicited mail in the post, it is therefore prudent to check this register prior to undertaking a mailing.
A check that is carried out on your data to assess its suitability for the task you want to use if for. As an example:
If you are undertaking a mailing, are all of the postcodes correct and valid? Or, if you are emailing to businesses, do you have the contact emails and how many are simply Gmail accounts?
The process of checking the addresses you have in your data against the PAF database. This database is held by the Royal Mail and contains every registered address in the UK.
The process of analysing your data and creating a profile that fits either your typical customer or the customer you would like to target in this campaign. It could be based on age, sex, marital status, home ownership, etc. Basically, all the data that you have (or can append) to your current databases.
As ‘big data’ evolves and the use of data driven marketing campaigns expands I’m sure that there will be more and more terms that come along, but for now we hope that you find this list useful.
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