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., Mr. instead of Ms.).
- 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 a 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.
“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.”