Reference-Based Data Integration Boosts ROI

Catalog companies, challenged by a multichannel environment, could take a page from top retailers and financial services organizations by integrating their disparate customer data sources using reference-based customer data integration. The return on investment can be substantial for start-up companies or a powerhouse.

Increasingly, top retailers are using some type of referential matching of their customer base. They integrate a customer’s complete name and address by using historical name and address and other information to create a single version of the truth about that customer.

Referential matching transcends traditional record-to-record matching by including a historical reference database – an accumulating repository of consumer information that bridges seemingly dissimilar customer records. Referential-match technology generates a persistent individual ID that consolidates customer information, yielding the highly desired 360-degree view.

Creating and applying persistent IDs is the only way for marketers to identify and track customer information reliably over time as account numbers, online user names, addresses and even names change.

By identifying redundant and incorrect data, a company more accurately can pinpoint the most profitable customers, identify multichannel customers, reduce cycle time, drive relevant offers and, most importantly, eliminate duplicate communications. This translates into lower advertising costs and higher sales per mailing.

Three main options exist for consolidating or integrating customer data: match-code; name-and-address matching software; and reference-based customer data integration.

Match-code processing uses an abbreviated form of the customer name and address to identify unique records. This technique, still used by a few catalog companies, under-combines records by 5 percent to 9 percent, resulting in duplicate contacts to the same customer.

Most catalog firms use third-party software to match full names and addresses of customers and prospects. This produces a substantial improvement from the match-code system, but 3 percent to 5 percent of the input remains under-combined.

Several catalog companies use referential matching combined with full name-and-address matching on their customer data, which essentially eliminates under-combines.

What are the financial costs and benefits of the various matching tools? Let’s assume that 1 million catalogs are being mailed. For the match-code system, the processing cost equals 1 cent per 1,000 books, while it’s 3 cents per 1,000 for the name-and-address system and 15 cents per 1,000 for reference-based matching.

Using the match-code system, the wasted cost of mailing duplicate catalogs from the mailing list, assuming a 5 percent under-combine count and an in-the-mail cost of 50 cents per catalog, is $25,000. With the name-and-address system, the wastage from duplicates equals $15,000, assuming a 3 percent under-combine count and an in-the-mail cost of 50 cents per catalog.

With reference-based customer data integration, there would be practically no wasted in-the-mail cost from duplicates. Thus, the benefit from using referential processing instead of match-code would be $25,000, less the difference in the cost of processing. The benefit from using referential matching instead of name-and-address matching would be $15,000, less the difference in the cost of processing.

These cost-saving benefits will be amplified as postal rates continue to climb. There are other benefits, such as eliminating the opportunity cost of including duplicates instead of other unique, qualified potential buyers in your target audience. This is the time to determine whether your company would benefit from improving your customer data to identify redundant and inaccurate information.

The Gartner Group estimates that retaining bad data can raise costs by a factor of 10, as bad data leads to bad decisions. As you eliminate duplicate records, you correct the aggregation of data, which frequently leads to improvements in your mailing patterns. Timely, accurate data managed by reference-based customer data integration can reduce costs and increase profit.

As catalog companies branch out to other sales channels, an integrated view of data across those channels, as well as across business units, can further identify duplicates. Without an integrated view, it often is impossible to identify multichannel customers. Research shows that multichannel customers are five times more profitable than those who buy from only one channel.

Using reference-based technology to identify these customers lets catalog companies target communications to these highly profitable customers. By gaining a 360-degree view of your customers, you will better understand buying patterns across and within channels. This understanding of customer behavior across channels allows better decisions on where to spend advertising dollars.

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