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Importance of Call Centre Analytics in Improving Customer Service

Posted by Taniya arya
Call centre company

In today’s dynamic business landscape, uber-fast mobile technology, breakneck social media have made the customer king. It’s no longer enough for a company to have quality products and services to win a customer’s heart. To truly stand ahead of the competition and carve a niche in the evolving marketplace, companies need to provide quality customer services relentlessly.

In this modern era, call centres are experiencing a high influx of structured and unstructured customer data coming from a variety of sources. The insights generated through data analysis can aid companies to create the peerless customer service experience that further helps in attracting new customers, driving customer retention, advocacy and achieving the competitive edge.   

Understanding call centre analytics

To break the terminology in the simple words, call centre analytics is a branch of advanced analytics buoyed with a variety of tools that companies can employ through multiple support channels to operate their functions uninterruptedly. One of the major challenges with call centre operation of any size is that management has access to a limited piece of information. While a great number of agents dealing with scores of customers every day, only a few of them pertaining to highly escalated situations (such as server downtime, a customer complaint, or an employee in need of guidance) would alarm management to possible issues. As such, under the traditional way of monitoring the calls, many opportunities for improvement get collapsed.  

Take a quick look at how corporate call centres can leverage call centre analytics to improve customer services:

Call centre speech analytics: Calls between customers and reps are brimming with information, through speech analytics, can yield valuable insights that companies can use to enhance the customer experience. On the agent’s end, speech algorithms can identify areas in which agent might require attention and training. By using a team of analysts to monitor calls in the real-time, a call centre company can uncover the obstacles in their current model, and consider process improvements, such as shifting to a prompt call script or building systems for call centre agents to achieve desired call results.   While on the customer’s end, the real-time speech analytics program can examine customer emotion and satisfaction by analysing their voices and sentiments.

Predictive analytics: New generation predictive analysis engine is an important tool for call centres that predicts customer behaviors and trends. With the help of in-depth review of past performance in areas including call volume, handle time, customer satisfaction, and service level, predictive analysis makes it possible to implement past solutions to forthcoming problems. How many reps will be needed on Christmas occasion? How will a new product rollout affect the call volume? By analysing the past results, companies can plan for the future.    

Self-service analytics: Modern business players are finding new ways to incentivize self-service channels. In spite of having a customer call a representative to update their address, it is better to provide them with the self-service option to do it online. It reduces the possibility of any error, incoming call volume and importantly the company cost. While some customers still prefer calling in customer care department, many customers are discovering that self-service option is an efficient way and hassle free alternative. Similar to other analytics tools, self-service requires minimal human intervention. Call centres, however, must ensure that their self-service analytics is amenable with their current technological model.

Cross-channel analytics: A well-managed call centre company needs to have a way to determine which communication channels any of their customers are choosing at a given point of time, and tailor their service options accordingly. Today’s customers armed with smartphones can call, email, chat and use social media applications to connect with a representative. The data flowing in across each channel contains valuable customer insights. Cross-channel analytics enable call centres to identify the various channels that users prefer to interact with them, and determine channels to use to optimise interactions with their customers. In this way, a customer can get a more pleasing and personalised respond.

Read Interesting Article At: 4 Secrets To Ensure Impeccable Customer Service

All these analytics will help call centres to identify the loopholes in the call centre operations. Armed with customer insights and intelligence from service analytics software, a company will be able to find out patterns and make effective decisions based on real customer behaviors and activity all together. Get advanced with data and service customers with the call centre experience they expect.

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