Dirty data is impacting CRM return on investment

Dirty data is having a profound impact on the profitability of companies, according to a recent study commissioned by SAS Institute, leaders in business intelligence.

"The survey highlights the fact that data quality is a major obstacle to achieving ROI from customer relationship management (CRM) initiatives," says Retha Keyser, product manager at SAS Institute SA. "The foundation of successful CRM is the accuracy and timeliness of the underlying data.

"This survey demonstrates how vital accurate data is to the bottom line of businesses, proving that data quality is the single largest obstacle to achieving ROI from campaigns," says Keyser.

The independent survey was commissioned by SAS in April 2003 to ascertain the perceptions of business users in Europe as to the extent data quality impacts the success and profitability of customer interactions. It also looked at changing attitudes regarding the importance of customer data from a business user's perspective.

Some 81% of survey respondents agreed that data quality has a direct impact on the profitability of sales and marketing campaigns, with almost two out of three admitting that one or more of their campaigns had not been profitable due to inaccurate data. More than half of respondents (55%) admitted experiencing lower than expected return on campaign investment due to inaccurate customer data.

Two-thirds (66%) of respondents also said that company profitability was affected by the accuracy and completeness of data, highlighting the critical business implications of 'dirty data'.

The survey also found poor data quality is a widespread phenomenon; 53% of respondents felt that between 1% and 10% of their data was inaccurate, with 10% of respondents admitting that up to 33% of their data was flawed.

The majority (56%) of respondents cited third-party data containing errors as the most frequent source of inaccurate data. This is a particular concern, as third-party data is also the most common source of information, with 61% acknowledging that it is their primary source of customer data.

The survey also found that 66% of respondents felt that customer satisfaction and loyalty would improve if their organisations' data quality was better. This was further supported by the admission that 43% of respondents had received customer complaints about irrelevant marketing material.

Finally, integration was also highlighted as a key factor in data quality, with more than half of the respondents saying that systems that do not integrate are a major cause of dirty data.

"To begin to address this problem, companies need to identify the data corruption areas and quantify the issue in business terms (ie impact on marketing campaigns) before they can start the actual data cleansing process," says Keyser.

The five sources of dirty data are:

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* Online customers intentionally enter incorrect data.

* Call centre operators enter abbreviated data to save time.

* Third-party data contains errors.

* Customers input errors into front-office systems.

* Data from diverse systems conforms to disparate formats.

Reasons to improve data quality include:

* Significant reductions in direct marketing costs through eliminating duplication of data.

* Better targeting of direct mailing by being able to identify and link related information, such as family members of a household.

* Less manual data administration through the automation of standardised international naming and address information.

* Faster, more consistent reporting and consolidation.

* Improved campaign cycle times through the elimination of unnecessary data movements and manual processes.