Case Study: Magazine Publisher saves over $53,000.00

Mid-Sized hobby magazine publisher.

The Problem:
The client mails approximately 1,000,000 subscription solicitations per year. Some files come from list rentals, but most are attendee lists from local art shows and member lists from small artists’ clubs. The validity of the data is always in question due to the transient nature of the target market coupled with the often slip-shod way the data is collected.

The Challenge:
To validate data accuracy, and ensure the highest deliverability of the list. In addition to saving money on mailings, the deliverability issues negatively affected the accuracy of their back-end analysis and they were anxious to increase its reliability as a strategic planning tool.

The Solution:
Move updating, along with aggressive address hygiene routines were implemented on the client files. A previous mailing had suffered a catastrophic event when someone upstream of the client sorted 40,000 names in an Excel spreadsheet and mistakenly sorted only the “name” column, and no others. This had the effect of jumbling up the names and addresses. That entire 40,000 piece mailing list went out with completely inaccurate names.

We took a representative sample from the new file (sent again by the people who jumbled it up the first time) and validated which names belonged to which addresses. Then, a data hygiene process consisting of CASS, NCOA, Advanced Address Correction, and a proprietary validation process verified that the initial jumbling-up problem had been fixed. The list was then merge/purged to remove any duplicates and gather data elements to create more complete prospect records.

The Results:
In all, we validated the accuracy of their entire annual mailings, recorded and updated over 6,300 new / moved addresses on the file, removed approximately 74,000 dupes (expected), and purged out over 4,000 undeliverable records. At an “In-The-Mail” cost of $ 0.67 each, the client saved over $53,000.00 by removing these undeliverable or duplicate names from their prospecting list. In addition, their back-end analysis (matchback) routines are now much more reliable and actionable.