Know the Basics of Contact Center Analytics

Written by KOVA Corp

There are many tools that contact centers are able to leverage to get the most from their technology, systems, processes, and employees; however, full optimization comes from having the ability to analyze data gathered from the output of these functions. Analyzing this data means gaining insights and lessons that can be used to make continuous improvements. Understanding and implementing fundamental call center analytics will provide invaluable knowledge that, when applied, produce immediate results.

Speech Analytics

When it comes to customer interactions, the most fundamental questions asked of any contact center manager are 1) Why are customers calling us? and 2) Why do customers continue to call us?

Speech analytics can provide the necessary insight about these questions by converting conversations from unstructured audio data and into data structured in an index that can be readily searched and analyzed. This activity takes place during three stages:

Stage 1. Processing from audio to data.
In this stage, audio (unstructured form of data) is converted into an index (structured form of data) that can then be easily search and analyzed. Think of it as a stenographer copying down the conversation in a courtroom.

Stage 2. Refining the data.
The indexed data is made usable by creating a list of user-predefined words to detect in the conversations. The predefined terms are also counted for frequency and their use in relation to other words during the conversation.

Stage 3. Analyzing the data to make it actionable.

After the information is processed a user can analyze the data and create actions based off the collected information. One way to analyze this data is through keyword spotting, or searching for specific words or phrases used in the calls.

The technologies used during each stage affect the functionality that can be provided in later stages. This is a key consideration when evaluating speech analytics solutions.

Data Analytics

Good data analytics should not be confused with data analysis; this confusion happens often in many contact centers where management uses spreadsheets to track and chart a wide array of key performance indicators (KPIs) that can vary widely from one center to another, such as:

  • Queues, agent, and team productivity from the automated call distributor (ACD)
  • Agent time utilization and activity management from the workforce management system
  • Individual agent and team quality scores from the quality monitoring team
  • Agent time and attendance
  • Absenteeism
  • Skill development scores
  • CRM system data

Note that data analytics is the methodology whereas analysis is the actual study. Data analytics, for example, is meant to improve data analysis. To make it easier to understand, pretend that data is a pie. Data analysis is concerned with just one piece of the pie: Studying how many berries it has, its contribution to the whole, and so on. Data analytics is concerned with the entire pie, such as identifying meaningful patterns from the study of each piece.

Data analytics should go far beyond presenting KPIs because it provides data that can assist call centers in:

  • Uncovering hidden service and quality issues in the contact center
  • Reducing costs by pinpointing actions that harm productivity
  • Increasing revenue by uncovering conditions favorable to up selling and cross selling
  • Increasing first-call resolution by detecting key reasons why customer issues are not resolved
  • Identifying star performers and underachieving agents
  • Establishing a return on investment for initiatives to improve performance

Customer Feedback Management

Customer feedback can be very difficult to capture and analyze because of on-going challenges in gaining the information needed to analyze because of issues concerning time, cost, and participation. Yet this information is critical to the success of a contact center. Solid customer feedback reporting helps organizations influence customer satisfaction by providing detailed reports including:

  • Survey result reports that provide overviews and detailed views of response and completion rates, question details, individual and aggregated responses, access to recorded calls, and more.
  • Performance analysis reports that summarize effectiveness metrics for agents, supervisors, and managers, helping you identify strong and weak performers.
  • Quality Reports that correlate and plot internal (company-driven) and external (customer-driven) metrics, illustrating discrepancies between the two to depict areas of strength or weakness.

For more information on how KOVA can help your call center deploy an analytics program within your organization, contact our team of solutions expert for a complete needs assessment.

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