Tips on How to Become a Data-Driven Contact Center

Posted by Rodney Kuhn

3/13/15 1:03 PM

BigDataImageCompanies have become obsessed with customer service. After all, it’s now seen as a major competitive differentiator for brands and separates today’s more-profitable companies from their less-lucrative counterparts. In fact, nearly 60 percent of organizations say that service and support will be the top source of competitive differentiation in the next three years, according to research from SAP. However, in a world in which competition is fierce and customer expectations high, satisfying customer needs is becoming increasingly difficult for companies.

Enter big data.

Big data has fundamentally changed the way businesses operate, giving them the ability to make better, more-informed decisions about everything from product development to marketing segmentation. According to findings from the Economist Intelligence Unit, companies that have embraced a data-driven culture are three times more likely to rate themselves as substantially ahead of their peers in financial performance.

No arm of business is set to benefit more from big data than the contact center, as it already has access to a goldmine of consumer and agent information—including consumers’ preferences and buying behaviors, call handle times, contact resolution rates and more—housed within their customer relationship management and workforce optimization systems. When effectively analyzed, this data can help contact centers better understand their customers and, in turn, provide a more personalized experience.

While becoming a data-driven contact center sounds simple, careful planning and execution is required. Below are three tips and tricks to help your organization leverage big data to improve customer service:

  1. Know what you want to measure: The first step to becoming a data-driven contact center is to determine what questions you want your data to answer. For example, do you want to know why hold times are longer than usual? Or why your first call resolution numbers are decreasing? Determining these questions beforehand will help you verify which key performance indicators you should be collecting and analyzing.

  2. Unite data from across channels: There are waves of customer data entering your business from various channels, including social media, billing services, surveys, Web downloads and more.Oftentimes, this data is spread thin across different systems, making it difficult for contact center agents to get a 360-degree view of the customer. To get the most from big data, merge data from different departments and channels into one unified view
  3. Start slow and steady: As with any big undertaking, start small when considering deploying a big data program to avoid becoming too overloaded and overwhelmed. Focus on one area and then gradually scale to something larger; for example, begin by analyzing agent metrics—such as how long they spend in each application—to determine where additional training and support is needed.

As the customer experience becomes increasingly more important, businesses will have no choice but to use the data they have to their advantage or risk falling behind the curve. Let Envision help you put the tools in place to utilize data to improve customer service. Contact us to find out how.

Topics: customer experience

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