Focusing on data quality should be a key objective for a variety of departments at any company. Salespeople can improve their numbers with good data, as it helps them deliver fine-tuned pitches to prospective customers. HR managers can use clean information to examine the productivity of the workforce.
But perhaps nowhere is quality data more useful than in customer service. When a consumer calls - or emails, mobile chats, tweets or posts on Facebook - a brand with a question or comment, customer care reps need to be armed with the right information to respond quickly and accurately, resolving any outstanding issues that might linger. Having the right data is key.
Why real-time data has the most impact
When people call in for customer service in 2014, they want immediate answers to their problems. If they're asking for help with health insurance, for example, they want their health care companies to have immediate access to accurate information about their account. No lag, no mistakes.
According to Business 2 Community, there's real value in this. If consumers recognize that their brands are armed with accurate knowledge, they'll become more trusting and ultimately loyal. Roy Goffer, director of marketing at nanoRep, spoke to this principle.
"The difference is apparent when one considers customer queries received via e-mail, forums or snail mail," Goffer argued. "In the aforementioned cases, a protracted period of time often passes before a customer service response is generated. The fallibility of information that is not 100 percent reliable means that customers may not receive an adequate response - even from live personnel."
Data quality is important because it helps companies overcome both problems - the delays and the inaccuracies.
Striving for maximum ROI
The truth, though, is that data quality costs money. Investing in email verification tools, for example, is not free, and when companies spend on such solutions, they want to be sure they're getting adequate returns on their investment. ROI is always king when business decisions are made.
Luckily, Goffer and other marketers and customer service reps agree. While data quality has its costs, the costs of ignoring the issue are far greater. If customer service departments attack their problems without data, consumers will notice, and they'll be turned off. If they use data that's "dirty" instead of accurate, mistakes will be made that will only have to be fixed later. Emphasizing good, clean data from the start is the most reliable and cost-effective way to go.