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Articles - Data Marketing - 3 weeks ago

It’s Time to Get More Out of Data

Contact Centers have always had an abundance of data about customers and performance. Unfortunately, that data is not being fully utilized to benefit the company, customers or agents. The unrealized potential of data has never been more urgent than it is right now, as centers focus on the customer experience and agent experience and the excitement builds around new capabilities in automation and intelligence.

Think how important good customer data is to things like appointment reminders, ID&V, screen pops and outbound dialing. All of these examples are things people have been doing for years (if not decades), and they are constantly hindered by data issues. Now think about what you would like to do with data to personalize your customer experience, make it easier for your agents to succeed, and drive changes that will deliver the efficiency and effectiveness your center is charged to deliver.

Companies are putting great hope in the future of self-service—whether IVR, mobile, or web-based—and that hope can only be realized if the customer data is great and the data about interactions is used to optimize applications. Customers’ motivation to use self-service can aid in getting profile data updated, whether they do it themselves or through an agent. Similarly, the pain of authentication (and growing demands for fraud prevention or regulatory compliance) may motivate both customers and those who serve them to focus on data updates to streamline that process.

It is increasingly difficult to hire, train, and retain the agents to handle ever more complex contacts, so we need data to help guide them through the contact handling. There are boundless opportunities to learn from interaction data to improve and automate processes, make the case for changes or investment in systems and applications, revamp training, or even change what marketing or product leaders do.

All this data opportunity will be even more important as contact center professionals transition from the excitement stage to the execution stage on a number of “hot” topics:

  • Artificial Intelligence has a prerequisite: Lots of data, and good data. Anyone embarking on an AI project will quickly find that a critical early step is to clean up the data.
  • Bots, whether text- or voice-driven, will rely on data and will generate data. Their design and optimization must be heavily steeped in the world of data, reports and analytics.
  • Intelligent Automation

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