Your Data is Worth Its Weight In Gold! Part 2

Part I

This is the second in a series of articles that will explorethe importance of quality data and mailing lists that you maintain. This segment will cover the application Match Consolidate to extract useful information out of data sets for reporting, re-import of data and analysis.

Data analysis is becoming more and more important as organizations push to streamline their mailings and information flow to clients. As organizations collect new data on their clients, prospects and the like at alarming rates it becomes verwhelming when attempting to use this data in a meaningful manner. It is estimated that companies stockpile of information on their clients is doubling each year. According to the research firm Gartner Inc and DM Direct, “many companies are suffering from an ‘information crisis’ stemming from woefully deficient data.”

Let’s explore some ways to work with your data, from simple to more complex as they apply to duplicate detections and merging of files for various applications such as direct marketing, telemarketing, eMessaging and reporting. The term householding has long been a term known in financial services and direct marketing circles, and is quickly becoming part of the corporate vernacular today. Most organizations have a faint understanding of what a household is and the value it provides or the methodologies of implementing such strategies.

According to Firstlogic a software vendor specializing in data quality, householding can be defined as a “hierarchical structure defining relationships.” Generally, organizations are attempting the define relationships between and among various data sets whether in a corporate, residential setting or both. Put in simpler terms, a company might try to identify all the records at a single address with the same last name such as Irwin or all the employees with the same last name at Mailmedia Inc. Since there are four Irwin’s at Mailmedia these would be put into a group of records for later identification or manipulation. Once an organization makes the decision to implement the data quality strategy to create a single record view, they need to implement business rules that will govern their overall business strategy as it applies to these types of data sets.

Once the business rules have been defined organizations can turn to Mailmedia for the necessary solutions to implement the data quality strategy. Mailmedia uses a very powerful tool called Match / Consolidate™ to analyze, combine and implement such strategies. Our matching engine uses an extremely powerful and pragmatic combination of lexical/transpositional, empirical and rule driven matching algorithms. This approach allows you to experience useable, repeatable and consistent results maximizing the data assets. The end result may be used for a mailing, reporting, or simply be exported back to the client for analysis or overlay of their data files.

The technology is capable of associating records based on more than just ZIP Code, Address and Last Name. It can associate records to identify relationships between distinctly different sets of data. For example, you can find your customers that have both a summer and winter residence or have a business address and residential address, by consolidating these records that overlapping information in common. Even though the records may be consolidated, you can retain both sets of address so that you can market to them. One marketing campaign may be solely directed toward a B to B sale while another may be for some purchase within the home.

Moving up the ladder of complication takes us to another level of matching. You can household all records from ABC Company into one “household” data set, as well as every employee at their corporate headquarters in Seattle. Finally, you could even create a household of all the members of the ABC Company Marketing Department in Seattle. In doing this you now have one point of contact or the much sought after single customer view, and more importantly this can be done in a single pass keeping your costs down.

You will also be able to apply this technology to the residential arena in ways that makes you appear to your clients as if you know them and their family members. If you have a residence such as PO Box 62 in Tacoma, WA and there are four members of a household with the same last name, you can consolidate these records into one “mailing record.” For example, say that you have Jim, Carol, Cary and Clark Smith living at this residence. The four records can be consolidated into one for mailing while removing the other three extra records. You will reduce your mailing file by three records contributing to postage savings and you reduce your paper and printing costs because you can print less. The end result on the mailing panel would read something like “Jim & Carol & Cary & Clark Smith” all addressed to the PO Box.

The next article will continue to explore data cleansing and what you can do to “wash” your lists. These lists may not be entirely related to mailing, but they can be cleansed as well. Mailmedia offers a wide array of solutions to reach true data quality.

Part III