ultimate guide to contact center analytics

The Ultimate Guide To Analytics In Contact Centers


11 August 2022

Companies that do not use sophisticated analytics miss out on significant customer-service gains. However, to effectively benefit from sophisticated analytics, firms must have the proper foundations to make the most of their data. Technology facilitates real-time business transformation - analytics technology makes organizations more flexible in keeping up with changing client wants and business trends. Today's prominent data pioneers use analytical techniques for high-level predictions and real-time visualization. Businesses that adopt analytics technology modify their business models and discover new customers, products, income streams, and service options. Contact center analytics may be used in enhancing the contact center productivity at one end and customer satisfaction and loyalty at the other end.


1) What Exactly is Contact Center Analytics?

2) Advantages of Contact Center Analytics

3) What Are the Different Kinds of Contact Center Analytics?

4) What Analytics Metrics Can You Measure?


What Exactly is Contact Center Analytics?

Contact center analytics are gathering and analyzing customer data to get critical insights into the operation of your service company. Customer satisfaction (CSAT), revenue, customer retention, customer effort score, and service-level agreement (SLA) performance are all included.

However, having a real-time, comprehensive perspective of contact center performance across all channels is a typical difficulty for many service practitioners. Only highly escalated problems, such as a system breakdown, a significant customer complaint, or an employee needing coaching get the attention of several agents who interact with numerous clients daily. This implies there are several prospects for advancement.

Advantages of Contact Center Analytics:

Let's take a look at how an analytic solution might help your contact center:

1. Enhances service quality

A significant aspect of contact center analytics is speech analytics, which studies recorded conversations to acquire customer information and enhance communications.

It also provides vital data about customer engagement, such as the frequency of call transfers, unwanted repeat calls, and other system bottlenecks.

The analytics assist in determining which circumstances result in duplicate calls.

Among these elements are:

This information may be used by the contact center management to simplify operations, procedures, and so on. This form of optimization has the potential to significantly increase customer service levels, business results, and the avoidance of follow-up contacts. As per Salesforce79% of service professionals say it’s impossible to provide great service without a complete view of customer interactions.

2. Determines Training Requirements

Specific data analytics systems use artificial intelligence to analyze employee behavior from their voice, cross-over talks, and even silence.

You can rapidly detect an employee's soft skills and customize your training programs appropriately.

For example, if a contact center employee seems uncomfortable when dealing with complex client concerns, the contact center management will know they need additional in-depth knowledge and training.

Managers may determine if the agents require hands-on training or whether a webinar would be sufficient based on their expertise levels. This form of labor optimization will significantly improve the contact center's operation.

3. Promotes Self-Improvement

The data analytics tool may provide scorecards for assessing agent performance.

4. Improves Insights into Customer Satisfaction

The majority of firms continue to conduct surveys to get client feedback.

However, speech analytics is a superior means of measuring client happiness.

5. Offers Insights from Several Channels

Efficient analytics assist businesses in determining which of their communication channels are favored by their consumers.

What Are the Different Kinds of Contact Center Analytics?

Advanced contact center analytics give information regarding customer experience and agent performance.

The following are the six kinds of contact center analytics:

1. Speech Recognition

Speech analytics examines recorded conversations to learn about the customer experience and agent performance.

The contact center analytics software identifies and tags emotions automatically. This data is mainly concerned with analyzing client complaints based on the tone and intonations of their voice.

These metrics show the flaws in existing scripts in the contact center solution and give practical suggestions for improving them.

You may also develop a new system to improve the consumer experience and distinguish your business from the competitors.

2. Text Mining

Social media platforms are growing in popularity, not just for people but also for companies and brands.

Furthermore, many firms rely on email marketing to reach a larger audience.

Because these platforms depend primarily on text, organizations must utilize text analytics to understand better the terms used in these communication channels.

Text analytics can track messages exchanged by contact center personnel and customers.

You may be able to gauge your team's success in providing excellent customer service by analyzing the information generated by these cutting-edge analytic tools.

Text mining can help businesses to identify the sentiments, satisfaction levels, and call compliance.

3. Predictive Analytics

A call or contact center may benefit from predictive analytics.

It employs an in-depth examination of several indicators to forecast which issues are likely to repeat so that you may be prepared with remedies.

Predictive analysis measures call volume, handling time, customer satisfaction, and so on.

Using these analytics, you may effectively handle issues like:

4. Analytics on Self-service

Several businesses are increasingly using self-service facilities for specialized purposes.

You may use a self-service application or chatbot to monitor shipments, update bank information, track food delivery, etc.

After being integrated with the company's websites or systems, these technologies need very little human participation.

An examination of these chatbots helps guarantee that there are no technical concerns with them. It also reveals how clients feel about doing these duties themselves.

These analytics will help you improve the self-service channels, retrain your bots, reconfigure Interactive Voice Response and improve the knowledge base.

5. Analytics on the Desktop

Desktop analytics captures and monitors all activity on the agent's desktop.

When this is combined with real-time call monitoring, you may quickly:

You may also employ sophisticated analytics to detect duplicate processes, reducing agent and customer annoyance.

6. Cross-Channel Analytics

Customers utilizing various platforms may call your contact center.

Some may prefer a chatbot; others may choose to tweet their problems, and others may prefer a more personal relationship via phone conversations.

A thorough examination of all of these platforms using analytics tools may assist you in tailoring the consumer experience appropriately.

For instance, if a client chooses to pay through PayPal, the phone representative may get real-time contact center script updates on this choice. They may persuade the consumer to pay their past-due bill using the same portal.

These little adjustments help guarantee a good client experience.

What Analytics Metrics Can You Measure?

Every statistic and Key Performance Indicator may be measured with analytics software (KPI.)

Let's look at a few of them:

1. Average Wait Time

The time clients spend waiting to be connected to a live agent is the average wait time.

If your average wait time is extended, your contact center may be understaffed, or your IVR menu may not be properly redirecting customers to the right queue.

2. Initial Contact Resolution

First-contact resolution refers to addressing a customer's issue or problem during the first interaction.

Customers that have a high FCR end up being happy or at least satisfied customers. It helps your contact center run efficiently, increasing client loyalty.

3. Average Handling Time

The average handling time is the length of the typical client call.

However, the metric should not be your North Star as in pursuit of having lower AHT, agents may try to close the call earlier than desired by your customers.

4. Rate of Abandoned Calls

The abandoned call rate represents the number of calls that clients leave.

A high abandonment rate almost leads to client annoyance and displeasure.

5. Transfer Rate on Average

Nobody enjoys being moved from one department to the next with no resolution.

The average transfer rate tracks how many calls are forwarded to other agents, the contact center management, or even other departments.

Call transfers have a substantial impact on the customer experience and are hence an essential quantifiable statistic.

6. Agent Attrition Rate

It is a significant problem for every customer-focused company. A high employee turnover rate might be due to a variety of factors.

An examination of these reasons might assist you in identifying the regions that result in attrition.

You may then deploy solutions to address these concerns, improving workforce management and increasing agent retention.

7. Satisfaction of Customers

A customer-oriented company and the contact center's ultimate purpose is to increase satisfaction throughout the client journey.

You can identify which channel is more successful and creates a better CSAT score. You can then encourage consumers to utilize it more often.


Contact centers are now poised to lead a paradigm change and provide revolutionary customer experiences for businesses and consumers. Intelligent data or contact center analytics are unquestionably an essential component of a client-centric company strategy. These actionable statistics will enhance the consumer experience and help your business establish its identity. Finally, brand loyalty is derived from a happy consumer! Why not invest in a decent analytics solution and watch your business grow?



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