Call Center Analytics: How to Effectively Analyze Call Data

Call centers are fast becoming the voice of companies across the board. They are both the spokesperson and the sounding board, and in most cases the first point of contact for a customer. With customer experience and customer satisfaction taking center stage in the current landscape every single customer interaction matters. Why? Every single customer interaction is a goldmine of data and effectively utilizing call center data and call center analytics can help optimize call center efficiency and improve customer experience.

But first things first, before we get into the nuances of how to effectively analyze call center data, let’s first get a thorough understanding of what call center analytics mean. In this blog:

• What is call center analytics
• Types of call center analytics
• How and why use call center analytics
• Must have analytics features in a call center softphone

De-coding call center analytics

In the modern business landscape call centers are the primary point of contact with a company’s customer which is why customer satisfaction is of utmost importance for call centers. In fact, a whopping 95.7% call center executives view customer satisfaction as the most important performance metric and call center data analytics can play a big role in maintaining a healthy customer satisfaction score. Call center analytics enable the agents to keep the customers happy by anticipating their needs and resolving their issues. Call center analytics enables organizations to maintain a healthy relationship with its customers and clients.

Call center analytics can be understood as the collection, measurement, and reporting of performance metrics within a contact center and multichannel contact center. Tracking call data, agent performance, agents efficiency in handling inbound or outbound calls, all of these and more come under the purview of call center data analytics.  These analytics take into account metrics like  how agents handle calls and the overall customer experience. Such  data is accessed and utilized using specialized analytics software inbuilt in most VoIP softphones.

Earlier such data access was available to managers and supervisors, however modern day VoIP softphones also provide real-time data points relevant to agents to help them boost productivity and deliver customer service that makes an impression. Thus, call center data analytics enables enterprises to deliver memorable customer experiences, foster brand loyalty, and optimize efficiency and productivity. To get a better understanding of call center analytics lets walk through the various types of analytics call centers use.

Types of call center analytics

#1. Speech analytics

One of the most important metrics in voice-based call centers, speech analytics refers to the process of analyzing voice call recordings or live customer calls. The speech analytics software recognizes speech, analyses audio patterns, and is also able to detect any stress in a speaker’s voice. Call centers use speech analytics during customer voice call interactions to identify the reasons for calls, the way agents respond, identify a pattern, identify products/services which have more issues, understand customers’ expectations, and identify areas that need improvement. Speech analytics enable businesses to identify issues which may otherwise not come up in regular surveys, NPS, and C-Sat ratings.

#2. Text analytics

Text analysis refers to an automated process of converting huge volumes of unstructured data from various sources (emails, social media comments, website reviews, chat interactions) into structured and quantitative data. Thanks to the internet and social media, a humongous amount of data is generated every second, managing and identifying data that makes sense can often be a huge challenge. Text analytics helps businesses extract data in quantifiable ways and get insights on what works and what doesn’t, design targeted and relevant marketing campaigns, and much more.

#3. Desktop analytics

A comprehensive desktop analysis tool captures all the activity on an agent’s desktop while they are on a call in real-time. Desktop analytics help identify any inefficiencies, monitor how efficiently agents are using the systems, whether or not all systems are working properly, identify areas that require more training, and help in enhancing the overall call center security. Desktop analytics enable call centers to significantly improve their processes by identifying and eliminating redundant tasks.

#4. Cross channel analytics

Omni-channel communication is the new normal. Businesses and customers are interacting with each other not just through emails or phones. There are multiple communication channels such as webchat, LinkedIn, website comments, Instagram, Facebook, Messenger, WhatsApp, Twitter and a host of many such platforms. Cross channel analytics help business enterprises identify and assess the different channels customers use to interact with them and design a more personalized and effective communications strategy based on customer preference.

#5. Self–service interactions

The do-it-yourself (DIY) momentum has gained huge popularity among millennials and generations after that. Businesses are recognizing this trend and have been smart to incentivise this trend by providing self-service or self-help channels in the form of FAQ’s and knowledge guides on their website or options to update personal information like change of address, uploading documents etc instead of calling a call center to help. By doing this companies are not only able to significantly reduce incoming call volumes, errors and costs, but also make the overall experience hassle-free and smooth for customers. While self-service interactions require minimal human involvement, analysing self-service interactions enable a business to assess customer experiences, identify technical glitches if any, and make the required improvements well in time.

#6. Predictive analytics

Predictive analysis tools give businesses insights on how past campaigns performed, when was called volume high or low, what challenges did agents face in peak holiday season such as Christmas and Thanksgiving.  With predictive analytics data businesses can better plan their product launch, marketing campaigns, staff requirements during peak and lean seasons, and overall improve your process efficiencies such as sales, services, and client/customer interactions. The data also helps you identify loopholes that increase call handling times.

These different call center data analytics help businesses understand customers better and provide them with meaningful experiences and a robust customer service. Call center analytics when used effectively can result in business outcomes that business owners always desire, such as:

• Improved efficiency
• High customer satisfaction level
• Customer retention and loyalty
• High revenue and profits

How and why use call center analytics?

Individual call center data analytics don’t offer much value, but together they give a holistic view of both your call center operations and customer journey. Analytics help  scale call center operations in an effective manner and deliver consistent experiences. Call center analytics measurable, integrated,  and make operations manageable. Use these analytics in totality and not individually to make the most of it. Now, coming to why should you use call center analytics? Well, there are many reasons that make a strong case, let’s look at them one by one.

#1. Helps track agent performance

Call center analytics enables supervisors/managers access specific reports to check their teams performance, identify bottlenecks, and areas for coaching. A few reports which managers use to track agent performance:

• Agent summary reports: This report tracks the average and longest times spent on various types of calls.
• Calls by skill report: Most call centers these days use automatic call distributor (ACD) for routing inbound calls. This report helps track the kind of calls each agent takes.
• Activity reports: In this era of remote and hybrid work keeping track of productivity can be a huge challenge. Activity reports give managers a historical view of each agent’s call activity and time spent in different call states.
• Custom reports: VoIP softphone also enable managers supervisors to get custom reports to track and analyze specific KPIs such as average handle time, speed of answer, first call resolution, number of calls, etc.

#2. Improve customer satisfaction

Analytics help identify customer issues, pain pcenteroints, process breakdowns, areas of improvements, giving businesses the opportunity to resolve these and deliver satisfactory customer experiences.

#3. Help enhance customer relationships

When it comes to call center operations the most common complaint is long hold times, waiting time, slow resolution to a problem, explaining an issue every time a new agent answers a call, and non-satisfactory closure to a problem. Analytics enable the business management to look at call volume data by hour and ensure there is adequate staffing to cater to call volumes at different hours of the day. This will help reduce customer hold and wait time, enable agents to provide satisfactory and quick resolutions which will translate into a bond of trust between the customer and the business owners. All systems will perform their best and deliver satisfactory outcomes.

Must have features in a call center softphone

By now it’s clear that the primary motive of call center analytics is to make data more accessible and usable in a systematic way. More so now, where remote and hybrid work formats are becoming the new normal. As a business investing in a call center softphone make sure to have the below features to get the most out of your investment.

#1. Integration with existing systems

Choose a call center softphone that can easily integrate with your CRM, email, team chat, and any other tools employees use to collaborate. This way it is not just the enterprise that gets data on team performance and customer satisfaction, employees get access to data which helps them provide quick resolution to customer queries.

#2. Easy access to metrics that matter

Ideally VoIP softphone should come with built-in reports which process and structure data such that you can make sense of it. The softphone should also enable supervisors to get customized reports specific to their needs.

#3. Real-time analytics

Picking up historical data, analyzing it, and doing what is required makes a huge difference but that alone is not enough in today’s cut throat competitive environment. Real-time data is the secret to stay on top of your customer service game.

#4. Actionable insights

Each business has its own unique requirements. While most built-in reports are designed keeping in mind all aspects of a business, tracking metrics that matter most to your business is of utmost importance. In case of call centers look for a softphone that can track and provide in-detail reports on metrics such as:

• First time response
• Average handle time
• First call resolution
• Average call answering speed
• Average waiting time
• Call volume

#5. Omnichannel capabilities

Customers connect with a business entity through various channels of communication besides phone and email. A call center softphone should not be cut-off from other communication channels, it should rather pick up data from all channels of communications so that you know which channel of communication you should focus the most on.

At the end of the day, the trick lies in bringing all customer data lying in disparate locations at one place in a structured manner so that you can create workflows and solutions that are effective and make an impact. Call center analytics helps you achieve this and much more.