Data quality is critical for CRM solutions

However, the reality is that many CRM implementations have fallen far short of the promised single, integrated customer view that would deliver improved revenue. Whether organisations have opted for in-house, outsourced or cloud-based solutions, failure to deliver is a fairly common theme surrounding CRM, not because the solutions do not work correctly, but because the information used in the systems is poor. A TDWI Report Series study - Data quality and the bottom line - showed that underlying data issues are at the heart of the perceived failure of CRM. Quality data is critical to the success of CRM solutions - with bad data, even the best technology will fail to deliver as expected.

The lure of CRM solutions when they first became popular was their promise to provide a single view of the customer. This led to rapid uptake of in-house CRM solutions, with companies migrating their data into new systems expecting to see immediate improvements to their business' bottom line. However, despite investing heavily into CRM, many organisations found that their customer interactions did not achieve dramatic improvements - because the root problem of poor quality customer data was not being addressed.

Data quality and data validation are not built into the CRM applications, so a single view of the customer becomes impossible. The data captured by the sales team does not reflect a single view.

The upshot of this was a perception that in-house CRM did not work, because duplicated customer records and other data quality issues resulted in customers continuing to experience a lack of consistency when dealing with organisations. Cloud-based solutions promised to deal with this 'failure' and offer cost effective CRM solutions that would finally deliver this coveted single customer view. However, because the underlying data quality issues were not being addressed, these solutions once again failed to deliver.

Poor data quality can occur for any number of reasons. In fact, according to the Data Warehousing Institute, "Experts say 2% of records in a customer file become obsolete in a month because customers die, divorce, marry and move. In addition, data-entry errors, system migrations and changes to source systems, among other things, generate volumes of errors." Missing information, incorrect information, and inconsistencies are just some of the common challenges with data quality, and often have one thing in common - they lead to duplicate customer records, which make a single customer view impossible. For example, John Anderson and Jon Andersen may be the same person, but a spelling error creates a duplicate record. John Andersen may also bank at Leading National Bank, which is written in full on one record and abbreviated to LNC in another, creating further duplication. A lack of standards and enforcement of data quality policies can create havoc with customer records, which in turn will all but ensure that CRM fails.

Whether CRM is implemented in-house or in the cloud, or even outsourced, systems have, over the years, offered new applications that promise to be the 'silver bullet' without fixing the root of the problem - the quality of data. CRM applications are merely tools - it is an organisation's customer data that enables the sales process, and the quality of this data is key in unlocking the value from this information.