Call center data is any type of data stored in a contact center. Call center data can include information such as customer accounts, agent performance records, and company finances. This type of data can be sensitive, especially when customer accounts contain payment information. These days, most call center data is stored in cloud-based servers. Some may feel as if this isn’t safe and prefer to have their data kept in on-site servers. However, technology has advanced significantly, and cloud-based servers rely on advanced network and system security controls to ensure that hackers cannot access a company’s sensitive information. Most call centers opt for cloud-based storage since on-site servers can be extremely costly to install and maintain. Troubleshooting is much easier with cloud-based servers, and usually involves only a phone call to tech support.
In order to keep information safe, call centers employ strict cyber security protocols to prevent hackers from gaining access into their servers. In addition, call centers aim to keep up with updated data protection laws. Most are PCI DSS and SOC 2 compliant. Depending on the industry a call center serves, leadership may also implement HIPAA, FISMA, or FedRAMP compliance standards. It’s critical for call centers to protect the data they store. Implementing strict standards prevents others from stealing information. For example, if an agent decides to write down a customer’s credit card number to ensure they aren’t missing any numbers, it can be very easy for that information to fall in the wrong hands. Call centers can be held liable if an agent is found to have been stealing credit card information.
More Call Center Data Resources for Contact and Customer Service
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Remember that you have to start with “why” when trying to establish how to analyze call center data. The most common “why” will be to become more agile as a business.
Workforce optimization and business intelligence tools like traffic dashboards and automated scheduling by volume assist with demand planning and agent engagement by centralizing information about processes as opposed to within your processes. This means that you can have more detailed reviews of disparate data.
Phone calls contain some of the most valuable data in the call center. Speech analytics lets you mine that data. Advances in artificial intelligence, natural language processing, and machine learning have made this process more efficient than ever.
Speech analytics is a valuable tool for assessing how you can improve your customer interactions. Inbound calls become opportunities for learning, training, and improvement.