Cross Channel Winners

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• Customer Solutions, December 2003
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Data integration is one of those tasks that sound easier than they are. Just about any company without a CRM system from day one will have most of its customer data in separate silos spread across departments, subsidiaries, external bureaux and bought-in data feeds. And every time the company buys in a new feed or acquires a new company, thousands of new records become available outside the existing storage areas — is it any surprise that data inside companies doubles every 18-24 months, according to the Office of National Statistics? To achieve a single view of customers and prospects, these different sources have to be reconciled and brought together in a single database if the company is to avoid duplicate mailings, imprecise campaign targeting and the continual expense of trying to link these data sources.

But unless there is a simple way to match records in different data sources to each other and decide which data takes priority when there is conflict, the job of integrating suddenly becomes a lot more risky and a lot harder. In fact, according to analysis firm Forrester Research, while 98% of companies recognise the value of an accurate single customer view, only 2% claim to have built one successfully.

So, is it better to step away from the problem and let the bureaux handle these difficulties, or can the IT department use its existing skills to bring the information together for you?

According to Lynne Clafton, product leader at data management company Acxiom, and other data integration specialists, once any company starts considering developing a single view of its customers and prospects, it needs to look at its data integration approach immediately. “It’s the absolute core. It’s the dull, boring, absolutely essential bit that starts right at the beginning,” says Clafton. “Everyone is sick to death of talking about CRM, mainly because they’re not seeing the benefits they thought they would. But largely, where it all tends to go wrong is at the very beginning of the process, which is the integration of the data. You absolutely have to get it right for everything else to be optimised and meet company objectives.”

But with data integration upfront in the process, a chicken-and-egg situation arises. Unless the company plans out in detail how it is to integrate the data and what processes will be needed afterwards to ensure it remains successful and will not have to be repeated, it cannot be sure who will integrate it or what tools and expertise might be needed. But until it knows who is to integrate the data and the tools it will buy, it cannot determine how to integrate the data and what processes it will need. So where does it start?

Usually, by calling in consultants or if it has the in-house experience already, it can overcome this problem. And if it takes a step back from the project, it can also see what it really needs. “Over the last few years, the focus has been completely on ROI,” says Ian Hitt, marketing director at Identex. “For any data integration project to get the go-ahead, it’s needed a watertight case taken to the board to get signed off. So there have been internal review processes looking at what to achieve, and they’ve almost always gone through a discovery process internally.”

These review processes have usually had one of three outcomes: inexperienced companies trying to integrate their datasets without fully understanding the issues involved, resulting in a botched integration and a return to the beginning of the process considerably lighter in pocket; a decision to outsource at least part of the project to bureaux because of a lack of internal expertise and resources; or a decision to buy in expertise and resources and complete the project internally.

According to Sophie Sail, customer management consultant for Experian's Truvue data integration service, the former approach is by far the norm. “Most companies try it themselves. It’s very much standard in the UK marketplace. Software seems like a cheaper option, but companies often underestimate the resources needed to use it and maintain it. So the clients we tend to talk to have gone down that route, found it wasn’t meeting the requirements of the business because it wasn’t accurate enough and it was draining too many internal resources.”

The key to determining who will perform the data integration is the biggest potential pitfall: record matching. Using name and address rather than unique customer IDs to link databases is going to be more of an art than a science. But when integrating data from different departments or from external companies, there will probably be no other choice. Even after a concerted data-cleansing effort to standardise address formats and details to PAF, change details using the national change of address file, and eliminate customers in suppression files, all of which are necessary on an ongoing basis as well as in the initial data integration, there are still many problem areas that force companies without the resources and the right experience to outsource.

Experian’s Sail envisages situations where two people who live at the same address and have similar names – such as, Mr S Brown and Sam Brown – could be integrated during a project. However, with access to a superior “reference” database that an external bureau might have, the company would never have combined the records of Mr Samuel Brown and Mrs Samantha Brown. Experian’s own Truevue service, since it contains data on the previous addresses and names of its subjects, can help integration projects match records that may not have either names or addresses in common – the kinds of records typically causing the single view to break down and customers data ending up stored in separate records.

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