Poor data quality is a disease which slowly destroys the value of your marketing database.  Quality is damaged through incomplete information, poor data entry, and data decay.  A traditional response is to purchase new records, but this only provides a temporary (and expensive) respite from your data quality issues.

The data I’ve seen indicates that contacts decay at a 25 to 30 percent annual rate.  This means that a prospect list that is 90 percent accurate today will be little more than 50% accurate two years later.  Thus, a prospect list purchase strategy is like steroids, it makes your marketing database look healthier on the day the list is purchased, but it simply masks the growing disease within your database.  Treating one or two symptoms does not address the underlying problem — a lack of a broad, continuous data strategy.

However, if you take a holistic view around data quality which includes continuous DaaS validation, ABM look-a-likes, web form enrichment, lead-to-account mapping, duplicate management, data standardization, and reference database appends, you will have a healthy database that ensures your MAP and CRM platforms contain the richest, most accurate data.

Vendors that support holistic data quality include ReachForce, D&B Optimizer (FKA Workbench), Zoominfo, InsideView, Oceanos, and Openprise.  So if you are concerned about your ability to target, segment, pass quality leads to sales, score leads, or build predictive models, then begin with a holistic data strategy.  Symptoms of poor data quality include high email bounce rates, declining email sender scores, returned direct mail, duplicate records, incomplete records, accelerating unsubscribe rates, and sales reps that ignore your marketing qualified leads.

Any firm that is adopting ABM, advanced lead scoring, a single view of the customer, or predictive analytics, should begin with a holistic data quality strategy.  Otherwise, these advanced marketing strategies are bound to fail.