Customer Data Integration

by John Jackman on September 14, 2017

One of the Most Challenging Tasks for Database Marketers

Why should you do it?

To avoid data silo risk.
The reality today is that many companies are exposed to data silo risk, which occurs when a company’s mission-critical customer data is scattered across multiple transactional and engagement databases— data silos.

When it’s time to execute a direct marketing campaign where the audience is a targeted list of customers, often the list is based on attributes that are spread out across the data silos. Now the marketing team has to rely on the IT department to get the job done. Someone from IT has to pull from each silo to create a list of the customers that meet the criteria. Then the list needs to be merged, deduped and delivered back to marketing. If the customer list is pulled incorrectly, or has too many or too few records, then the query must be redone.

This arduous process can be so time-consuming that potentially profitable marketing campaigns are delayed or never happen at all.

The solution to data silo risk is CDI—the integration of all customer databases (POS, call center, campaign history, web behavior, e-commerce) into a single marketing database that provides a 360-degree view of each customer. With a user-friendly front end, the full customer view can be accessed directly by the marketing staff.

What should you consider?

The foundation of a successful CDI platform is a superior match engine.

The ideal match engine compares multiple records and accurately determines if they are pointing to the same person, household, or business site. The optimal match engine also minimizes the most common errors—False Positives and False Negatives.

False positives occur when the match engine accepts two records as a match, but they are actually different. False positives can lead to the addition of bad data when the match engine appends the wrong demographics to a customer record. It can also cause the removal of good records that can serve as future sales opportunities if the match engine removes a record that it erroneously determines is a duplicate.

False negatives occur when the match engine rejects two records as a match but they are actually the same. False negatives can prevent the addition of good data (i.e. the match engine erroneously fails to append accurate demographics to the record) and to the retention of costly duplicates.

The bottom line is that False Positives and False Negatives lead to not only the waste of valuable resources because of bad data, but also the loss of profitable sales opportunities because of missing data.

Here is an example of the importance of high-quality matching when comparing two records that look different but are clearly pointing to the same company:

Record 1 Record 2
Mumford Ceramics
58 Main Street
Wickford, RI  02852
M Ceramics
59 Main Str
North Kingstown, RI  02852
Superior match engine >>> Matched:
Duplicate removed
Inferior match engine >>> False negative:
Duplicate retained

Here is an example of the productivity and analytical power gained by building a 360-degree view of the customer from a number of data silos across the enterprise:

Customer Data Integration is no longer a nice-to-have addition to the marketing toolkit.  It has become a necessary part of a strategic, customer focused strategy.  When data silos have been properly integrated, the full value and power of a company’s customer information can be harnessed by the marketing department to grow the business by maximizing upsell and cross-sell opportunities.

Virtual DBS, Inc. provides best-in-class database marketing tools and services including predictive analytics, marketing data, data hygiene and digital advertising. With products and services delivered in the cloud, omni-channel marketers have access to some of the most comprehensive B2B, B2C and Specialty databases available.