For the seasoned Direct Mailer, running a merge purge is a no-brainer. It keeps your data clean, it removes duplicate records, and it saves you money.
With clients NEW to Direct Mail, the concept of a ‘merge purge’ can be a bit foreign with a jumble of terms (self-duplicates, recency matches, frequency, mps suppress) that often leads to more questions than answers.
In an effort to demystify the merge purge process, here is a simple (and true) example illustrating the value of the merge purge process:
Take the below sample merge details
91,863 Rented Records 1,082 Bad Addresses (removed) 611 Self-Duplicates (removed) 824 MPS/Do Not Mail Suppress (customers wishing NOT to receive direct mail solicitations – removed) 12,882 Customer Matches (customers that already existed on the mailer’s file – removed) 14,642 Recency Matches (records that appeared in multiple rented files – removed) 61,822 Quantity left to mail
In this scenario, our client rented 91,863 records from multiple sources. For simplicity, let’s assume it costs our mailer $1 per record to mail (all costs in EXCEPT merge purge).
If the client mailed these records as received then, without doing the merge purge, their cost would simply be $91,863. Not a cheap mailing.
You can see from the above results though that the merge output only 61,822. Had the merge not been performed that would mean overspending by $30,000!
So what does it all mean?
Bad Addresses represent invalid data that would make those 1,082 records unmailable…clearly worth dropping.
Self-Duplicates are duplicate records appearing within the files rented. This often happens due to data entry errors (for instance inputting J. Charles and Jimmy Charles).
MPS/Do Not Mail Suppress are individuals that have officially requested to be removed from direct mailings, generally through the governing body (for instance the DMA in the US). These are clearly customers you do not want to solicit.
Customer Matches represent existing customers within this mailer’s database already. These are often omitted from the acquisition merge in favour of other approaches or strategies as these customers have an existing relationship with the company.
Recency Matches these customers appeared in recent merges (including the current one) already thus the mailer has chosen to remove.
Now bear in mind the above represents the simplest form of merge purge that a mailer should run, but clearly illustrates the perils of just accepting all the data received at face value without processing.
Most data processors can offer several higher levels of data processing to further refine the data, but even through just this basic process alone the mailer saved $30,041 in mail costs AND preserved their reputation by removing duplicate records and those who would rather not be contacted.
And the cost to perform this? At the going rate of $4 per thousand (input) it cost this mailer LESS THAN $400 to save $30,041…. Clearly worth it!
Merge Purge is not only a smart, cost saving measure, but also allows you to target your mailings more effectively, keeps your mailing clean, and will improve your results. Talk to your data processor to fully understand the processes and options they offer.
