It may sound blunt, but it's hard to argue with Richard West's logic: "Dead people don't buy."
West is the president of Peachtree Data, a Duluth, Georgia-based firm that specializes in data quality, cleansing customer data lists for direct mailings. Among other tasks, Peachtree compares its clients' mailing lists against a list of recently deceased Americans – around 60 million records a month -- that is based partly on data from the Social Security Administration. When it finds a match, Peachtree culls the customer data from the list, saving clients from sending catalogs, coupons and other items to the recently departed.
On average, just 1% of customers on its clients' mailing lists are found to be deceased, but for large mailing lists with tens or hundreds of thousands of customer records, that's still significant, West said. Combined with Peachtree's address verification capabilities, which ensure that a customer's address is indeed a valid U.S. postal address, the company saves its clients an average of more than 12% on direct mailing costs per job.
The Data Services suite was released in April 2008 and incorporates technology that Business Objects acquired when it bought data quality vendor Firstlogic two years earlier, according to SAP.
The Data Services suite is used at Peachtree to load massive amounts of data – West said Peachtree processes between 550 million and 600 million customer address records per month – into relational databases and for the data matching and cleansing itself. Prior to deploying Data Services 14 months ago, he said, Peachtree actually outsourced this work because the company simply didn't have the technical capabilities to do it in-house in a timely or cost-efficient manner.
"[Previously] it would take us seven to 10 days to process a single file if we did the work ourselves," West said. With Data Services, Peachtree can now analyze and remove deceased customers from the average client mailing list in five to 10 minutes.
West cited two factors that account for Data Services' speed. First, the suite loads and analyzes the list of recently deceased Americans on a relational database, rather than in a flat file form. Second, the suite then uses embedded logic to reduce the number of records that it compares per job.
For example, if a Peachtree client's customer mailing list has 10,000 records that consists mainly of people in Boston, Data Services will recognize this fact and compare the list only against records of the recently deceased whose addresses are also in Boston, maybe 30,000 to 40,000 people, West explained. "If it were just a flat file, [Data Services] would have to read 60 million records against 10,000," he said. "That could take days and maybe even weeks to run."
Data Services is not cheap, however. West wouldn't reveal what Peachtree paid in licensing or maintenance fees for the suite, but he acknowledged that "it is kind of expensive. But given this is what we specialize in … bringing it in-house was worth the cost justification."
It is not at all clear, though, whether the cost justification will make sense for other small and medium-sized business (SMBs) – Peachtree has just 17 employees – as SAP BusinessObjects says it will, especially those SMBs not in the same direct mail/data cleansing business as Peachtree.
SAP wouldn't disclose pricing details either, but a spokesperson did say the company employs a CPU pricing model for Data Services, which allows customers to start with small deployments and grow them as needed. The suite is also available in a SaaS model, which could prove attractive to SMBs with small IT staffs and infrastructures.
"I don't know exactly the price point, but I suspect this product may stretch the budget of typical SMBs," said Ted Friedman, a Gartner analyst who covers both data quality and data integration. "Having said that, it is likely less expensive than a similar combination of functionality from other vendors [including IBM and Informatica]."
The vendor has also been cited for a decline in the quality of its technical customer support as it relates to data quality products, according to Gartner. The Stamford, Conn.-based research firm speculated that support staff shake-ups following SAP's acquisition of Business Objects could be one cause.
Another, however, is probably the high price of SAP data quality products.
"While there could be various reasons for this decline [in the quality of technical support], the turnover of personnel following the acquisition of Business Objects, the substantially larger size and complexity of the SAP organization, and the current economic conditions [where high-priced products create challenges for customers] are likely to be contributing factors," wrote Friedman and Andreas Bitterer in their recent Magic Quadrant report for data quality tools.