Why Does Data Quality Matter?
It takes a long time for a brand to build a reputation for quality through features, performance, service, reliability, and/or durability. Unfortunately, losing a quality brand reputation can be accomplished in moments.
One of the fastest ways to lose a quality reputation is to use poor data when communicating with a customer or prospect Here are some examples of seemingly simple data-related issues that can cause a relationship to go sour:
- Confuse one customer with another customer.
- Use the wrong name for a customer, such as using their family name as their given name.
- Using the wrong gender for a customer (e.g., he instead of she).
- Have incomplete or erroneous information about a customer.
- Send multiple offers to the same person, especially if they are slightly different offers based on past purchases.
- Send a personal greeting that contains a default value, such as one that begins “Dear (Insert Name Here).”
- Send documents or packages with an address or phone number that uses the incorrect format for the local market.
Bad customer data can also lead to bad analysis and forecasting. If you are trying to analyze your company’s ideal buyers, you will get the wrong answer if you cannot match a customer to all of his or her transactions.
Related Topics:
Personal Names Around The World
Global Name Standardization Services


Sixty-nine percent (69%) of organizations believe that inaccurate data will undermine their ability to deliver an excellent customer experience.
“Garbage in/garbage out erodes customer satisfaction,” stated Forrester Research in a report entitled Poor Data Quality: An Often Overlooked Cause Of Poor Customer Satisfaction Scores.” Customer service agents need the right data about their customers, purchases, and prior service history at the right point in the service cycle to deliver the right answers. But when their tool sets pull data from low-quality data sources, agents don’t have the right information to answer their customers.”
Sixty-nine percent (69%) of organizations believe that inaccurate data will undermine their ability to deliver an excellent customer experience, according to a 2018 study conducted by Insight Avenue for Experian Data Systems.
Poor customer experience has a direct impact on a brand’s reputation:
“Overall, 71% of respondents said their typical response to a bad experience is to stop doing business with the company. A slight majority (55%) typically tell friends and family about it in person or by email, while 42% said they complain to the company and 26% post a comment on social media,” according to a study released by the Economist Intelligence Unit (EIU).
The impact is that poor customer data costs organizations 6% of annual revenues, according to a Royal Mail study of businesses in the U.K.
How bad is the problem? A recent study of the more than 10-million customer records by Global-Z showed the following:
- 45% of the records contained invalid information.
- 38% had terms such as “Need New Address” in the address field.
- 12% had duplicate information in multiple fields.
- 5.5% had the identical values in the given name and surname fields.
Many of the remaining 55% valid records contained significant problems for creating a quality customer interaction. Different records about the same customer often did not match exactly. For example, information may have been typed incorrectly or a customer may enter his or her name and address differently on different documents. Name matching becomes a critical factor in building complete customer records.
Related topics:
Quantifying Data Quality Errors
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