Customer Data Integration

Customer Data Integration

Customer Data Integration (CDI) is the combination of the technology, processes and services needed to create and maintain an accurate, timely, complete and comprehensive representation of a customer across multiple channels, business lines, and enterprises typically where there are multiple sources of associated data in multiple application systems and databases.

Techniques for Identifying Customers

Customer data has many attributes. Common attributes include customer name, address, phone number and perhaps a social security number. But given two sets of data that is slightly different, perhaps a nickname (Barb instead of Barbara) or a cell phone number, how can a computer determine that this is the same customer or two distinct individuals?

In the larger sense, customer data can be very complex; for example, the number of fields that represent just a name can be anywhere from six to twelve or more. For example here are some typical fields associated with a customer "name":
* Name prefix (Mr., Mrs., Dr., Captain)
* Given name (known as first name in western cultures)
* Family name
* Middle name
* Name Suffix (Jr., Sr., II, III)
* Initials
* Nickname
* Maiden name
* Married name
* Professional title
* Academic title

The address entries are almost as complex (e.g., primary address number, pre-directional (N, S, E, W,) street name, street suffix, post-directional, secondary identifier (building, suite, apt,) secondary number, city, state, ZIP, and ZIP+4(R))

Now, add phone numbers, social security number, email address, tracking( customer number, account number,) relationship, risk level, purchase history, service history, demographic, socio-economic, lifestyle, consumer behavior segmentation and privacy preferences, just to name a few, and you really get the picture.

Plus, this information changes constantly, or can be entered in error, or fraudulently. And, for most medium to large business or organizations, the data is stored in several different places, different departments, different locations,in different formats, etc.

Techniques for Managing Complexity

These attributes can become extremely complex and ultra-dynamic due to the many changes individuals go through in the course of their lives. Multiply all these fields by the millions of records a business or organization has in its data sources, then consider how quickly and how often this information changes.

The results are staggering. The Data Warehousing Institute (TDWI)says, “The problem with data is that its quality quickly degenerates over time. Experts say 2% of records in a customer file become obsolete in one month because customers die, divorce, marry and move.”

To put this statistic into perspective, assume that a company or charity has 500,000 customers, donors or prospects in its databases. If 2% of these records become obsolete in one month, that is 10,000 records per month or 120,000 records every year. So, in two years, about half of all the records are obsolete, if left unchecked.

Peppers and Rogers call the problem, "an ocean of data." Jill Dyche and Evan Levy, gurus in this field, have boiled the challenges down to five primary categories:
# Completeness – You don’t have all the data you need to make sound business or organizational decisions
# Latency – It takes too long to make the data valuable…by the time you can use it, too much is obsolete or outdated (slowed by operational systems or extraction methods)
# Accuracy – What percentage of your data is inaccurate…your Achilles’ heel
# Management – Data integration, governance, stewardship, operations and distribution all combine to make-or-break data-value and
# Ownership – The more disparate data-source owners, the more silos of data, the more difficult it will be to solve the problems.

History of Customer Data Integration

In the late 1990s, a company based in central Arkansas, named Acxiom, teamed up with Gartner analysts in the field of data management to crystalize the concepts of and coin the term Customer Data Integration (CDI.) Acxiom had been perfecting data management and integration for over 20 years and had developed several best practices from the experience. Gartner was keen to standardize the concepts and share the best practices.

The process, as Acxiom and Gartner described it, is intended to calm the ocean of data. It includes (1) cleansing, updating, completing contact-data plus (2) consolidating the appropriate records, purging duplicates and linking records from disparate sources to enable customer or donor recognition at any touch-point (3) enriching internal and transactional data with external knowledge and segmentation and (4) ensuring compliance with contact suppression to protect the individual and the organization.

Today, CDI is delivered as a hosted solution in batch volumes, on demand using a software as a service (SaaS) model and onsite as licensed software in companies and organizations that are sophisticated enough to drive their own data integration processing.

The results are promising. CDI enables the full integration of online and offline marketing to reach perfect prospects at the perfect time, please them and still protect their privacy. CDI enables companies to optimize merchandizing (assortment, promotion, pricing and rotation) based on demographics, lifestyle and life-stage…to ensure inventory turn and reduce waste. CDI enables companies and organizations to choose the best location for the next new branch office, store or kiosk.

CDI is commonly used in support of both Customer Relationship Management and Master Data Management, and enables access from these enterprise applications to information confidently describing everything known about a customer donor, or prospect, including all attributes and cross references, along with the critical definition and identification necessary to uniquely differentiate one customer from another and their individual needs.

ee also

*Identity resolution

External links

* See Data Integration at http://www.baseline-consulting.com/Practice_Integration.html
* See book, Customer Data Integration by Jill Dyche and Evan Levy, the CDI bible (and this is not a plug by the authors) at http://www.amazon.com/Customer-Data-Integration-Reaching-Institute/dp/0471916978/ref=pd_bbs_1?ie=UTF8&s=books&qid=1213831272&sr=1-1
* The MDM Institute - Headed by analyst Aaron Zornes - http://www.tcdii.com/
*
* Customer Data Integration article on MyCustomer.com - http://www.mycustomer.com/cgi-bin/item.cgi?id=133064&u=pnd&m=phnd


Wikimedia Foundation. 2010.

Игры ⚽ Нужно решить контрольную?

Look at other dictionaries:

  • Customer data integration — For other meanings, see CDI (disambiguation). In data processing, customer data integration (CDI) combines the technology, processes and services needed to set up and maintain an accurate, timely, complete and comprehensive representation of a… …   Wikipedia

  • Data integration — involves combining data residing in different sources and providing users with a unified view of these data.[1] This process becomes significant in a variety of situations, which include both commercial (when two similar companies need to merge… …   Wikipedia

  • Data management — comprises all the disciplines related to managing data as a valuable resource. Contents 1 Overview 2 Topics in Data Management 3 Body Of Knowledge 4 Usage …   Wikipedia

  • Customer — For the British rock band, see The Clientele. A customer (also known as a client, buyer, or purchaser) is usually used to refer to a current or potential buyer or user of the products of an individual or organization, called the supplier, seller …   Wikipedia

  • Customer relationship management — (CRM) is a widely implemented strategy for managing a company’s interactions with customers, clients and sales prospects. It involves using technology to organize, automate, and synchronize business processes principally sales activities, but… …   Wikipedia

  • Data warehouse — Overview In computing, a data warehouse (DW) is a database used for reporting and analysis. The data stored in the warehouse is uploaded from the operational systems. The data may pass through an operational data store for additional operations… …   Wikipedia

  • Data migration — is the process of transferring data between storage types, formats, or computer systems. Data migration is usually performed programmatically to achieve an automated migration, freeing up human resources from tedious tasks. It is required when… …   Wikipedia

  • Data mining — Not to be confused with analytics, information extraction, or data analysis. Data mining (the analysis step of the knowledge discovery in databases process,[1] or KDD), a relatively young and interdisciplinary field of computer science[2][3] is… …   Wikipedia

  • Integration Competency Center — The Integration Competency Center (ICC), sometimes referred to as an Integration Center of Expertise (COE), is a shared service function within an organization, particularly large corporate enterprises as well as public sector institutions, for… …   Wikipedia

  • Master data management — In computing, master data management (MDM) comprises a set of processes and tools that consistently defines and manages the non transactional data entities of an organization (which may include reference data). MDM has the objective of providing… …   Wikipedia

Share the article and excerpts

Direct link
Do a right-click on the link above
and select “Copy Link”