Having poor-quality data is like buying a new car and never changing the oil. That's what Adam Nenning, Executive VP of Personalization and Marketing Automation at Inte Q, thinks. Other industry experts agree, and the data backs this up — recent Gartner research has found that organizations believe poor data quality is responsible for an average of $15 million per year in losses. In fact, IBM estimates that the cost of poor quality data in the United States was $3.1 trillion in 2016 alone.
Read more to learn about the quality of your customer data.