CASE STUDY

Call Center Data Analytics: A Case Study on How a Leading Multi-National Company Identified and Improved Important Services That Were Negatively Affected Due to Longer Waiting Times

Dec 19, 2017

The Client

A leading conglomerate in the United States.

Industry Overview

Typically, call centers are units set up by companies for inbound or outbound telephone calls. Inbound call centers usually deal with customer service and facilitating customer inquiries or complaints. Whereas, the outbound call centers typically consist of occupations such as telemarketing, market research, and the seeking of donations. The call center and telemarketing industry have experienced steady growth over the past five years as the US economy picked up traction. The call centers have increasingly used technological advancements, including social media, cloud-based systems, voice recognition software, and several other broadband-enabled technologies, to become more efficient and stand out of the competition.

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Let’s take a look at some of the vital factors that will influence the growth prospects of this industry in the coming years.

  • High Attrition Rate: More often, the call center industry suffers from a high attrition rate. Each time a trained employee quits a firm, there are only a few resources on hand to ensure the smooth execution of work. This forces the company to hire more resources to balance out the attrition, which subsequently results in excess recruiting costs, training, and developing new staff.
  • Increasing Customer Expectations: With social and digital channels reshaping customer expectations and improving business competition, it has become harder for call center firms to meet customer expectations. With evolving customer expectations, customer attrition tends to intensify as customers expect immediate service through the channel they desire.

These factors are forcing call center companies to leverage solutions like data analytics. Data analytics solutions help businesses operating in the call center space to gain unparalleled volumes of information to access and formulate superior strategies and position their product and service offerings better. These solutions also assist clients in achieving more profound insights into the customer data sets. This would help them create customized products, prevent losses, and improve pricing accuracy.

The Business Challenge

A leading conglomerate in the United States with several call center units spread across the region wanted to analyze the inbound data for its phone operations for hotel reservations, airlines, rentals as well as service centers. Additionally, due to the increasing complexity in managing operations across various industries, the client wanted to analyze the call center data and streamline its processes to improve operational efficiency and customer service.

Our Approach

To help the call center client deal with specific business challenges, the industry experts analyzed operational, marketing and human resource data, which included information about:

  • Call ID Number
  • Timestamp
  • CSR Information and Location
  • Action Taken
  • Time for Resolution
  • CSR Status, Tenure, Training, Skills
  • Transactions, and more

Quantzig’s data analytics experts also conducted a descriptive analysis of the variables to organize and summarize the data that was provided:

  • Comparison of service durations v/s service types
  • Customer waiting times segregated by type of service/customer

The experts also identified the estimation and forecasting parameters from the data for forecasting arrival rates and predicting an increase in average service times during peak hours. Furthermore, we developed queuing models for determining the average delays for customers across services and abandonment rates.

Interactive Dashboard to Visualize Call Data and CSR Metrics

We visually represented the data for operational performance, which included metrics such as:

  • Number of arrivals and abandonment at different time periods
  • Average Service Times
  • CSR Utilization Rates
  • Delay Distribution in the Queue

Speak with our analytics experts to know more about how our data analytics helped a call center industry client and how you can leverage it for your business.

Insights and Business Benefits for the Client

  • Created an integrated data-repository that was continuously updated by multiple data sources
    • Enabled real-time data analysis across both operational and marketing data
  • Developed highly accurate forecasts for call arrival rates at different times of the day
    • In-bound call volumes were significantly higher during the weekends from 5 pm to 9 pm
    • During the weekdays the call volumes were significantly higher from 11 am to 3 pm
    • Enabled call center managers to balance center resources with the future workload during any period based on the call volumes
    • The average abandonment rates of loyal customers were around 30% during weekends and 42% during weekdays
    • The patience of customers increased linearly as their years of association with the client increased
  • There was no significant correlation between agent service times and the call arrival rates
    • Agent service times were mainly dependent on the type of issue and agent skill

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