Happy customers are loyal customers, and the best way to keep them happy is to consistently and efficiently provide high-quality, personalized service. Given the numerous sources of customer information available to companies in the current market, the need to manage this information effectively is more critical than ever.
Poor data collection and management is a recipe for disaster when you consider the potential impact using bad data can have. Research suggests that bad data in customer communications can negatively impact total revenue by as much as 25 percent.
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What Is Bad Data?
“Bad data” refers to outdated, incorrect, redundant or incomplete information that prevents efficient business communications, wastes company resources and jeopardizes customer relationships. From poor formatting of viable data to duplicate customer records, the quality of data can make or break a customer’s satisfaction with a company’s service.
1. Misspelled Names
Receiving personalized service is one of the greatest tactics to develop loyal customers. Misspelled customer names may not only prevent items from ever reaching the intended recipient, it may lead to the customer discarding the item altogether.
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At the very least, the customer may feel irritated by the error and lose confidence in the company. As a result, time, effort and materials goes to waste.
2. Bad Addresses Means Mail Goes Undelivered
The United States Postal Service reports that in 2013, over four percent of the mail it processed was undeliverable as addressed (UAA), totaling 6.8 billion items that never made it to their final destination—all due to bad address data.
A data entry error resulting in incorrect ZIP codes and/or street addresses have serious repercussions. If a customer is expecting to receive communication—or worse yet, a shipment—from a company and never does, they may lose faith in the company’s service and business practices. Bad data involving merchandise shipping increases business expenses and is bad for the bottom line.
3. Crossing Account Names
Large data sets will invariably house customers with the same name or very similar personal information; communication mix-ups are bound to happen. Data that is not validated or poorly curated may cause a great deal of unnecessary angst over privacy issues when a customer’s account or information gets crossed with another.
In a time when security breaches in personal data are common and often disastrous, even a minor mix-up can compromise a customer’s trust in the ability to manage personal information effectively.
4. Duplicate Communications
Given the high volume of customer records a company may manage, having duplicates is a common challenge to maintaining data quality. If left unchecked, duplicate records will cause one customer to receive multiple contacts from a company.
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Flooding a customer’s email or mailbox with the same information may result in them unsubscribing from your mailings. Similarly, it will be a drain on company resources when paying double or triple to reach one individual.
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5. Repeated Requests for Data
A January 2015 B2B quality index shows up to 40 percent of leads contain bad data. Data can come in incorrect, or it can become compromised via bad management. Ineffective record keeping may include poor organization, improper collating of data or using contact practices that fail to elicit the right data to create a seamless customer care experience.
It may be necessary to confirm customer information at times, but it is important to avoid having them repeat the information repeatedly. Ideally, data should be entered correctly from the start and properly managed (cleaned) once entered. If customers note that a company is not managing their information well, it may affect their satisfaction and retention.
Assuring Valid Information
Business runs on big data and good data begets success. Customizing communication sent out to consumers means reaching the right individuals with the right information. Considering the monumental amount of information used each day by businesses, and how quickly that data can change, managing it all may seem like a tall order.
Prioritizing data quality and investing in data management resources is the best way to improve customer retention and revenue. Data validation APIs provide the means for using only the most accurate data, thereby avoiding lost mail, redundant contacts and inappropriate content material. Tools such as Service Objects’ DOTS address validation API reduces the chances of annoying customers with bad data by correcting and verifying information in real time—the gold standard in managing big data.