Database Slideshow: Bad Customer Data is Common, Costly

By Dennis McCafferty  |  Posted 09-24-2010

96.2 percent

96.2 percent of respondents say their organizations view data accuracy as an essential issue.

96.2 percent

One-third

Nearly one-third of respondents say their organizations do not enforce the accuracy of data, despite the widespread perception of how important this is.

One-third

84 percent

84 percent of respondents say their organizations plan to invest - or that they should consider investing - in data-quality initiatives over the next 12 months.

84 percent

60 percent

60 percent of organizations participating claim at least 6 percent or more of their databases contains inaccurate or missing information.

60 percent

56 percent

56 percent of those surveyed say outdated information is a common data error.

56 percent

28 percent

28 percent of respondents say that all departments contribute to data errors.

28 percent

63 percent

63 percent of respondents say that 5 to 30 percent of their organization's marketing budget is wasted as a result of bad data.

63 percent

26 percent

26 percent of respondents cite senior management support as a barrier to maintaining accurate data.

26 percent

39 percent

39 percent of respondents cite budget as a barrier to maintaining accurate data.

39 percent

48 percent

48 percent of respondents say they use manual processes to measure the accuracy of contact data.

48 percent

47 percent

47 percent of respondents say they use analysis of response rates from marketing campaigns to measure the accuracy of contact data.

47 percent

56 percent

56 percent of respondents say they use staff training to maintain and improve contact data.

56 percent

48 percent

48 percent of respondents say they use software tools to maintain and improve contact data.

48 percent

Four best ways to ensure clean data

1. Understand your database. Review contact data to determine common errors within. If area codes are constantly wrong, for example, the problem could be systemically fixed.

Four best ways to ensure clean data

Four best ways to ensure clean data

2. Remove duplicate records. They inhibit an organization's ability to collect a singular view of each customer or prospect.

Four best ways to ensure clean data

Four best ways to ensure clean data

3. Verify data during all capture processes. By knowing data, businesses can determine the best place to implement point-of-capture verification tools. Two common areas where data entry is flawed, for example, are sales and customer-service points.

Four best ways to ensure clean data

Four best ways to ensure clean data

4. Enhance and update the data. It improves accuracy while providing additional, fresher customer insight.

Four best ways to ensure clean data