Contact Data Quality and Retail Organizations: Current Perceptions, Cleansing Practices and Accuracy Levels

Contact data quality plays an important role in the retail market as it touches every part of the business, from package delivery to decisions around new store locations. But when contact data is managed incorrectly, costs are wasted and customer relationships are damaged.

To take a pulse check on the industry, Experian QAS conducted a survey in August 2010 to look at contact data perceptions, cleansing practices and accuracy levels. This report reviews current thoughts on contact data quality and includes advice on how to clean and maintain retail databases.

One hundred U.S.-based retailers took part in the survey, produced by pureprofile, an online marketing research firm, for Experian QAS. Company size varied from less than 50 employees to more than 1,000 employees, and a variety of departments were surveyed, including IT, marketing, operations, etc.

Data Quality is Top of Mind
Retailers are heavily focused on contact data management as a priority in 2010. This is reflected in the fact that 76 percent of retailers said that they plan to invest or should consider investing in data quality initiatives over the next 12 months. In addition, 58 percent of respondents have or are currently working on a contact data management strategy. Furthermore, 64 percent recognize and enforce data
accuracy as an essential issue.

This isn't surprising when reviewing the reasons that retailers maintain contact data quality. According to the survey respondents, the primary reasons for maintaining quality contact records are to save costs, enhance customer satisfaction and increase efficiency.

Contact data impacts a retailer’s ability to deliver product. Additionally, it greatly affects customer analytics, which are used by retailers to enhance marketing efforts and improve upsell and cross-sell opportunities.

Contact Data Inaccuracies Persist
Despite the strong investment in data quality mentioned previously, retailers still find their databases riddled with errors. Of those surveyed, 55 percent stated that at least 6 percent or more of their database contains inaccurate or missing contact data. The top data errors reported were incomplete or missing data, followed by outdated information and incorrect information.

Sales was cited as the main department that causes data errors, but many retail respondents also stated that multiple departments contribute to contact data errors. Budget, staff errors and internal resources were reported as the main barriers to maintaining accurate contact data.

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