3 min

4 Ways to Take Advantage of Contact Center Analytics

Data analysis and reporting tools can drive improvements for enterprise contact centers.

In the contact center, data is everything. 

It can help organizations improve the customer experience, prevent cancellations and returns, inform employee training programs and build a company’s brand around excellent service. To achieve these benefits, however, organizations must first harness their data and take steps to unlock its potential. This can be especially challenging for fragmented IT environments where data is stored in different places. 

Organizations should follow these four steps to take advantage of analytics and reporting tools in their contact centers.

Step 1: Gather Data for a Holistic View

Companies already have an enormous amount of customer data. The true power of this data is unleashed when silos are broken down and this data comes together to create meaningful human stories.

Typically, the data that flows in and out of contact centers lives in numerous environments. This is especially true of cloud contact center environments (also known as Contact Center as a Service, or CCaaS), since organizations may use one cloud provider for a main contact center, another cloud provider for workforce optimization and yet another for customer resource management data. Because these pieces of information reside in separate public and private cloud environments, organizations can struggle to get a holistic view of their data. Customer experience management solutions can help bring all this data together in one place, which is a prerequisite for leveraging data for value-added insights.

Step 2: Interpret Data for Deeper Understanding

The next step on the analytics maturity model is interpreting the data that an organization has gathered, leading to a 360-degree view of the customer. During this stage, data from sources such as surveys, impact analyses and business units is analyzed to identify trends and areas of need. One of the goals at this stage should be to locate customer pain points and determine ways to decrease customer effort and improve overall satisfaction. Simple metrics such as time to resolution are a good start, but organizations will have more success with analytics — including predictive analytics — if they are able to also leverage less structured data from sources such as customer call transcripts.

Step 3: Validate Data to Enhance Trust and Accuracy

As new data comes in from existing and new sources, IT leaders must continuously work to validate it and ensure its accuracy. (Analytics programs that rely on bad data are essentially the textbook example of the phrase “garbage in, garbage out.”) For instance, an organization’s speech recognition analytics might show that a customer is frustrated, but then the customer gives the interaction a 10 out of 10 on a post-call survey. Clearly, there’s some sort of disconnect happening here. Organizations must dive deeper into these interactions to clear up confusion, resolve any problems and validate their data to ensure meaningful insights.

Step 4: Refine Processes to Stay on Top of Changing Conditions

The data coming into a contact center is constantly changing, and analytics programs should evolve over time to reflect new understandings of how the information can be better used to achieve an organization’s goals. This includes rethinking what sorts of data might help stakeholders to better understand the customer journey and eliminate pain points. For instance, CDW recently worked with a hospital that had a one-question survey: “How could we have improved your interaction today?” Far more than a numerical rating, this sort of open-ended question can yield answers that truly reflect the nuances of the customer experience — giving organizations the information they need to make improvements.

Story by Matt Holbrook, a passionate technology architect with over 18 years of experience in unified communications and contact center architecture, design and development using industry leading technologies.

As a distinguished solution architect within CDW’s Cisco Contact Center Practice, Matt is responsible for leading the architectural design and pre-sales support of solutions to meet customer needs for business-critical unified communications, enterprise contact center, omnichannel, IVR/self-service applications, and CRM integrations.