call center, speechanalytics

Retention of existing customers is vital to the survival and growth of any business. This would hardly come as a surprise to any business-savvy individual, and recent research demonstrates the importance of customer retention:

The acquisition of new customers can cost five times as much as retaining existing customers.

The success rate of selling to a customer you already have is 60–70%, while the success rate of selling to a new customer is 5–20%.”

As easy as customer retention sounds, implementing an effective strategy to increase customer retention rates may prove challenging for various reasons such as a business’s priority on gaining new customers, lack of resources, poor customer service, an insufficient amount of customer feedback, or lack of tools.

But which of those factors should a business focus on hr most to increase customer retention?

According to 89% of businesses surveyed in a recent study, customer satisfaction is the major factor in boosting customer retention.

In this piece, we will analyze how businesses can use speech analytics tools in their call centers to boost customer satisfaction, thus increasing customer retention rates.


One critical aspect of customer satisfaction is to provide solutions to customers when they encounter problems using your products or services. Once such a problem occurs, the main interaction medium between you and your customer will probably be Call Centers.

During these calls, the more effective solutions you provide, the more fulfilled your customers will feel.

Although the queue time, the average speed of answer, percent of calls blocked, quality of service, and the success in resolving the issue in the first call impact customer satisfaction, research shows that resolution of the issue at the first call is the most determinant metric for customer satisfaction.

Fewer repeated calls mean higher levels of customer satisfaction and high customer satisfaction is directly linked to increased profitability; the sole purpose of your business.

Despite all the data showing the value of the FCR rate to a company, nearly 30% of all the calls relate to the unresolved issues from the previous calls that the customers make.


As companies focused more on understanding their customers and extracting more insights about their businesses, analysis of human speech has become more critical, making the voice data collected via Call Centers all the more valuable.

Speech analytics refers to the process of analyzing call recordings to extract insights to improve services and enhance the communication with the customers. It is used to detect patterns, discover strengths and weaknesses of the business, reveal the real-time trends and categorize the calls.

These potential advantages of Speech analytics make it a powerful tool to be used on calls made to Call Centers.


1. It is cost-effective because repeated calls mean higher costs.

Call Centers spend 23% of their operating budget on repeated calls. Therefore, resolving the customers’ problems at the first call will save your businesses’ financial resources, which can be reallocated to another department.

2. Repeated calls translate to lower customer satisfaction, leading to decreased profits.

Not being able to resolve the problems of customers is likely to lead to loss of your customer: research shows that A poor first call resolution rate translates into decreased profits.

For example, when customers’ problems are not resolved in their first calls, 19% of them expressed their intent to stop buying products/services from the relevant business.

Having to make multiple calls will lead to frustration and contempt for the business because the customer will feel like being ignored and wasting his time.

Although the importance of the FCR rate is obvious, Nearly a third of all the calls made to call centers relate to unresolved issues from the first calls.

Let’s now look at the primary reasons so many calls still go unresolved and show how Speech Analytics can solve these problems.


In this section, I will explain the reasons for repeated calls first. Then, solutions using speech analytics will be presented supported by specific scenarios.


Problems brought up by customers are so complex that the call center agents cannot respond to them effectively and quickly.

When your customers call, they don’t care about the complexity of the problem at all, all they expect of call center is to solve their problems as quickly as possible.

However, the high complexity of the problem is a hurdle before a higher FCR rate.

This complexity can be due to two factors:

The businesses offer a wide variety of products/services and introduce additional features so frequently. This makes it harder for agents to remember them all and solve the problem on the first try if they cannot find the information related to the problematic issue immediately.

Secondly, a dynamic regulatory environment requires constant updates and leads to more customer calls. New privacy laws, new rules about banking and insurance cause Call centers to be flooded with customer calls.

These complexities make it harder for call center agents to comprehend the problem and develop a solution; leading to repeated calls.


Deploying Speech analytics in the call center can analyze real-time data and equip agents with all the necessary information.

Speech analytics allow the analysis of real-time data as conversations are occurring, it does not just analyze words, but it rather deciphers the meaning of words and phrases within the context of the conversation.

Based on this analysis, it can quickly determine the cause of the problem and report it to the agent, it can even display the relevant solution for the problem and help the agent provide an effective solution.

Furthermore, Speech analytics can pick up certain trigger words and phrases from the conversation to determine what product/service the issue relates to, accelerating the resolution of the issue at first try.

These advantages allow call center agents to quickly figure out a solution to the customer’s problem in the first call, reducing the number of repeated calls.


A bank has adopted a new privacy policy because of a new regulation. In this privacy policy, it states that the bank can share all information of account holders such as spending habit and money transfers with third parties under certain circumstances.

A customer hears about this new privacy policy on the news and reaches out to the call center. She wants to find out about whether her spending habits(extracted from her personal data) will be also shared with insurance companies because it can affect her premium.

The call center agent is perplexed by this request because he/she may not even know such a complex legal issue.

If speech analytics is used, the algorithm will understand the request of customer quickly based on the usage of words and context and scrape the relevant legal information from the database and even display the possible answer on the agent’s computer.

Thankfully, the issue will be resolved in the first call and this will improve the FCR rate.

If it was not implemented, the call center agent would struggle with the question and hung up the phone and tell the customer to call them later once they find out the answer.


Call Centers are slow and inefficient at determining the root-causes. This reduces the FCR rates.

A call center handles thousands of calls every day and manual review of those calls by supervisors to detect root causes driving the calls would be almost impossible because of human labor and time constraints. Therefore, Call Centers only analyze a tiny sample of calls to determine root causes of customer problems, disregarding the large proportion of the calls.

Manual review of calls is inefficient for two reasons:

**The manual analysis will not be accurate at detecting trends for root causes because it only reviews a small portion of the calls. If prevalent causes for problems are not detected, the customer problems will not be resolved, leading to more repeated calls.

**Manual review will be slower at developing a swift action plan against real-time trends in root-cause analysis. Lack of an effective solution will cause the Call Center to be flooded with repeated calls, reducing the FCR rate.

When a problem occurs in a product, system, or service the business provides/runs, people will have the same problem and make a call for help.

If such a problem is detected in the first couple of calls, the solutions can be found immediately, and when more customers call, their problem will be resolved based on this solution at the first call and this will reduce the volume of repeated calls.


Using Speech Analytics in a call center can improve the root-cause analysis and help increase the FCR rate.

Speech Analytics technology is capable of transcribing all the conversations into text and determining patterns within the text, it will consider 100% of calls instead of analyzing a small and unrepresentative sample of calls.

Hence, it will be more accurate at detecting trends for root causes.

Secondly, Speech analytics will be faster at detecting patterns for root-causes compared to manual review. While the manual analysis may take days to detect root causes, Speech analytics can find them within seconds.

It can categorize root causes according to demographics, location, topics and products, making it easier to devise customized solutions.

Speech analytics will improve the root-cause analysis process so that the Call Center will be aware of the source of the problems customers are facing and develop an effective action plan immediately. As a result, future calls related to the same problem will be resolved in the first call, increasing the FCR rate.


An e-commerce platform processes payments via its own website.

However, there has been an update to the payment method and the customers now have to enter the three-digit code sent to their phones via SMS before logging-in.

However, the SMS system does not support some telecommunications providers, so 10% of the customers cannotcannot make payments as they could not receive the three-digit code.

A few customers facing this problem contact the call center for this issue to be resolved.

If the use of speech analytics in call center is implemented, it will quickly and accurately determine the root cause of these problems is the same and will send a real-time notification to supervisors alerting them.

Before more customers experience the same problem and contact, the call center will be able to resolve this issue so that the call center is not flooded with calls related to this; reducing the number of repeated calls.

This will make sure that the upcoming calls will not be repeated as the root of the problem is detected early on and resolved immediately.


Using speech analytics in the call center will increase the FCR performance because:

a) It is more accurate and quicker at detecting the root-causes of customer calls. It can alert the supervisors of the root- cause of a problem early so that the problem can be fixed before more customers face the same problem and make a call.

This will lead to fewer repeated calls; thereby increasing the FCR rate.

b) It can analyze real-time data instantly as conversations flow, detect trends, and equip the call center agents with the information and tools to solve customer problems; enabling the quick resolution of the problem.

c) This will in turn lead to increased customer satisfaction and will boost the customer retention rates.



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