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According to Gartner, in 2004, businesses are expected to be managing thirty times more data than in 1999. But the average company only utilizes 7% of its data warehoused information. Also, through 2006, greater than 50% of Business Intelligence (BI), CRM, and Enterprise Resource Planning (ERP) undertakings will suffer limited acceptance despite the cost and effort to implement them. Why? It’s primarily due to a lack of attention to data quality.

Far too often, the emphasis is placed on obtaining and analyzing the output of sophisticated, high-end analytics systems with little consideration given to the data that fuels them. Basically it boils down to the old adage, Garbage In, Garbage Out!

Therefore, to improve the viability of CRM, BI, etc. as useful decision-making tools, concerted efforts must be taken to improve the source data. Only then can companies begin to truly know their customer.

Does It Really Matter?

How do companies accurately identify customers and what difference does it make? This can best be understood using the following example.

Are Eugene W. Foster and Gene Foster the same person?

On the surface this seems like a simple question. But determining whether or not they are one and the same can require some comprehensive analysis. There are numerous Fosters in the U.S., so how do we determine if they are the same person? We must examine any and all common attributes available in the data store. This might include an account number, address, telephone number, birthday, or any other information available that might link them together. It’s also important to note that any “similar” information found may not be stored in the same format. For example, a birthday on one file might be stored as mmddyy but as ddmmyyyy on another. The ability to dissect this information and boil it down to a common format is equally important as identifying it.

Now, how does determining whether or not two records represent the same person impact the business? Again, a few examples will quickly crystallize the benefits of having clean data and knowing your customer.

1 Source: The Direct Marketing Association

Maintaining Customer Goodwill
A non-profit agency periodically sends fundraising campaign correspondence to its donor base. The donor database contains “dirty” data, resulting in donors receiving duplicate mailings. They begin questioning the misuse and waste of scarce funds by the agency and become hesitant to continue donations. At the end of the campaign, the agency sees that contributions have fallen from prior campaigns and must try to determine why. Is it the economy? Are former donors now giving to other charities? They may never find out even though the root of the problem might simply be internal. It’s unfortunate that their image might be irreversibly tarnished based on dirty data. Even worse is the fact they could have taken preventative steps to maintain and possibly increase their donor base!

Reduced Mailing Costs
Similar to the previous example, sending duplicate mailings can be very expensive, running from $1/pc upwards to $10/pc depending on the application. In 2001, the Data Warehousing Institute estimated that poor data cost U.S. businesses $600 billion annually in wasted postage and marketing costs.

One case study involved a client with 934,000 households. Removing the dirty data reduced the number of households to 905,000. In this instance, the reduction of 29,000 records yielded a savings of $43,500 per mailing, as the campaign costs were $1.50/pc. And for four quarterly mailings, what marketer wouldn’t want an extra $174,000 in their budget?

It should now be very clear that a solid foundation for knowing your customer is achieved through the utilization of clean data. Still not convinced? Remember, you wouldn’t build your dream house with warped or splintered lumber so why would a business use flawed data to drive its decision-making system. Quality data is the first and perhaps, most important step a company must take in achieving an accurate view of its customers.

And the prior examples are just the tip of the iceberg in identifying the potential applications and markets where clean data can make a difference. The need spans many sectors including financial, entertainment, publishing, health services, etc.

Financial Services
Banks and brokerage houses can cross-sell clients and improve retention by using their data to better understand the relationships that exist within and across accounts.

• Householding
  Through the process of householding or consolidation, individuals can be linked and treated as a single entity. One benefit might be the discovery of an older teenage child in the family. The parents might then be targeted for a college loan or home equity loan for the anticipated expense.



• Real Time Targeted Marketing
  Nearly everyone uses Automated Teller Machines (ATM). A bank can turn the ATM from a simple cash-dispensing machine into an interactive marketing vehicle with messages tailored to individual customers. For instance, while conducting a transaction, the ATM might display to an existing loan holder “Interest rates have dropped ½%. Would you like us to send you a pamphlet or have a banker contact you, yes or no? The bank can quickly and inexpensively reach a customer with a customized message saving call center and/or mailing expenses by targeting the client directly at the right time. This “customized” (one-to-one) communication also produces an intangible loyalty effect by making the customer feel special.

Gaming/ Entertainment
Several states now require casinos to comply with regulation requiring a Disassociated Players List. The list is intended to keep problem gamblers from receiving enticements to visit the casino. In complying, they remove disassociated persons from all direct marketing lists, refuse check-cashing privileges, and deny participation in player programs. Having accurate data on their client base will allow the casino to compare its marketing list with the disassociated list and remove those gamblers. Casinos failing to comply can face fines upwards to $75,000.

Also, many companies in the entertainment industry are owned by the same parent company. By combining multiple sources of data, more information can be learned about each individual from the types of properties visited to their room and meal preferences. Analyzing this information will result in more accelerated target marketing for future campaigns.

Publishing
Newspapers are constantly faced with reducing churn when promotions end or competing newspapers try to sway existing customers with incentives. Knowing when subscriptions are about to expire and contacting customers beforehand can help minimize churn. Furthermore, by accurately identifying those customers who only take advantage of promotions by slightly varying first and last name spellings, publishing houses can reduce the cost of incentives and promotions intended to attract the genuine prospects.

Health Care
Due to the Health Insurance Portability and Accountability Act (HIPAA) requirements, the medical profession as well as others has become increasingly sensitive to protecting patient information. The ability to more accurately identify patients, safeguard records, and provide audit trails is becoming mandatory. Again, the hospital database serves as the starting point for complying with the HIPAA requirements. Accuracy is vital.

What Have We Learned?

The examples can go on and on but the point should now be clear; having the ability to reach out to customers in a professional manner and to accurately identify their wants and needs isn’t just desirable but a requirement for business. Targeting the right person or company at the right time with the right message is key to success. If customers have favorable experiences, they are likely to remain loyal customers.