3 Ways to Use Big Data to Improve Customer Service in Your Call Center

By Shauna Geraghty
0 min read
Oxford defines “big data” as “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.” Big data is of special interest to businesses that wish to gauge their consumers’ preferences and ideas regarding customer service.
A recent survey from Software Advice, a web-based reviews center for helpdesk systems, on how to improve call routing using big data revealed some interesting findings:
- 67 percent of people over 65 tend to prefer slower paced customer service calls, while only 57 percent of 18- to 24-year-olds prefer more time consuming attention.
- 24 percent of city residents prefer agents around their age, while only 10 percent of rural residents and 9 percent of suburban residents valued this.
- Casual engagement was preferred by 49 percent of Midwestern callers, 36 percent of Northeastern callers preferred formality.
- U.S.-based agents were preferred by 78 percent of 55-64 year-olds, while only 48 percent of 18- to 24-year-olds had this preference.
These findings highlight the fact that customer service is practically unique to the individual – however there are some trends and consistencies depending on the caller’s characteristics. Their age or location may determine by whom and how they wish to be addressed, which presents a challenge to call centers hoping to offer personalized attention. Yet by knowing these facts, call center agents, teams and departments can tailor their approach and demeanor to each customer, enabling them to provide a more personalized experience.
So how can your team use big data to provide top-notch customer service? By considering the following:
Customer Insight
Once companies obtain information about the specific preferences of their customers, they can provide personalized service. As such, in order to be effective, agents must have access to customer information such as their previous interactions, support requests, emails and notes, as well as data from CRM, Helpdesk, back office solutions, Facebook, Twitter and LinkedIn directly in their call center software interface. This will allow agents to personalize their conversations according to the caller’s unique characteristics in an effort to increase interaction quality.