One-Fifth of Companies Believe Most of Their Customer Data Is Inaccurate

How accurate is your marketing data?

In a study conducted by Experian of 1,000 employees worldwide who have visibility into how their employer manages data, respondents said that on average about 30% of their firms’ customer data is inaccurate. About one-fifth of respondents believed that more than half of their customer data was wrong.

Experian’s study certainly isn’t the first to shine a light on inaccurate data.

In 2017, Deloitte had 107 US adults anonymously review the information that data brokers were selling about them. More than two-thirds of the respondents said that the third-party data about them was more than 50% incorrect. Since third-party data brokers don’t have direct relationships with users, they make inferences to build their data sets, which are less likely to be accurate than first-party data providers who have direct connections with users.

What may be troubling for advertisers is that unlike Deloitte’s research, Experian’s study didn’t exclusively examine third-party data. Instead, Experian found that companies have inaccurate information throughout their various types of customer data.

Human error was cited as the main cause of data inaccuracy, as half of the respondents indicated that basic missteps contribute to their company’s erroneous data. The second biggest contributor to data errors is the lack of internal communication between company departments, which was cited by 36% of respondents. “It’s also ironic to think that human error is increasing at the same time as our uptake of automation,” Experian researchers wrote in the report.

For marketers, data errors can lead to money wasted and decreases in efficiency. Experian researchers noted one way companies can get a clearer view of their data challenges is by centralizing ownership of their data. About half of the marketers, publishers and tech developers in North America surveyed by Winterberry Group in 2017 said that centralizing ownership of data would be one of the most important changes that their organization could make to derive value from their data.