Customers' calls are currently manually listened to and interpreted by customer service representatives in many contact centers. However, fewer than 5% of calls are typically monitored for quality assurance (QA). This omits potentially hundreds or thousands of hours worth of data that could close your contact center performance gaps. Contact centers can now score 100% of their calls by investing in a speech analytics tool using techniques like Natural Language Processing (NLP) or artificial intelligence (AI); these tools also let you conduct a root-cause analysis of your customer issues.
With the advent of speech analytics, we can now analyze customer interactions and conversations in real time using key metrics. This makes life easier for customers and agents by ensuring that contact center and call center employees have access to crucial information when they need it.
According to McKinsey, speech analytics can result in cost savings of up to 30% and improvements in customer satisfaction scores of 10% or more. We’ll go into more detail about real-time speech analytics in this article and explain why understanding customer conversations have become so crucial.
1. What is Speech Analytics?
2. How does speech analytics work?
3. When is real time speech analytics very helpful in a contact center?
4. When is post call analytics very helpful in a contact center?
5. Real-time V/s Post Call Analytics
6. Speech analytics benefits
7. Use Cases of Speech analytics in contact centers
8. Benefits that the use of speech analytics provides to organizations
Speech analytics uses word recognition and audio pattern analysis to determine call quality, track agent performance, and identify emotions.
Supervisors and agents can use real-time speech analytics solutions to examine customer calls while they are still in progress and gain useful insights while the customer is still on the other end of the line.
Supervisors or QA can understand exactly how agents are handling phone calls, including how closely they adhere to established procedures, thanks to these real-time insights.
As a result, if a customer support agent runs into a specific issue, they may receive pertinent information and advice via an on-screen pop-up. As a result, the customer experience is improved as they are able to respond to the needs of the customer more effectively. Today, sectors ranging from financial services to retail use this type of analytics.
Two methods are frequently used to find information in spoken content. Predictive insights and keyword spotting are two examples.
Keyword Spotting: The process of locating specific words and phrases used during a call is known as keyword spotting. An API tool is then given instructions for how to use these keywords, such as scoring calls positively if they contain the words "happy" or "excellent service." This approach can be used right away because it can be implemented during an API request.
Predictive Insights: It goes beyond keyword spotting by recognizing and comprehending the subtleties and intent of the customer. Complex events like Hot Leads, Pre-Churn Accounts, Made Appointments, and others are detected using it. This process takes a little longer to parse through because it involves machine learning and predictive analytics training processes, which must be prepared before an API request.
Real-time speech analytics enable supervisors to keep an eye on conversations as they are taking place, allowing for quicker resolution of customer issues. Additionally, it is used to enhance compliance (thereby lowering the risk of violations and related fines) and partially automate the process of quality assurance.
These insights are no more limited to contact center operation. The treasure trove of customer insight is relevant for product team, social media team, operation and delivery team and other team to improve and target the customer in a better way.
Call center managers can get a bird's-eye view of how each call is handled by using call monitoring in conjunction with real-time speech analytics.
The unstructured data in source systems, like call recorders or VoIP streams, is processed by a speech analytics tool. The tool then compares the data to structured metadata, including call length, agent name, customer name, and time. Duplex channel data stream is required to easily segregate the customer and agent voice packets.
Now by applying speech recognition to the audio, the human voice is converted into text by the voice recognition software. The program also captures auditory data throughout this process, such as tones and modulations in the voice.
The speech analytics tool looks for language trends in the conversation (text format). Contacts are labeled or categorized by the tool considering their tone, language and more. Automatic scoring is supported by some sophisticated speech analytics solutions. Automatic scoring necessitates the identification of important variables or key performance indicators.
Modern speech analysis systems now include sentiment analysis, which helps identify whether a customer is satisfied or not. Customer satisfaction, first contact resolution, customer service agent efficiency and enthusiasm are also factors that will be monitored. This will help to assess the performance of the overall contact center, and depending on the findings, required changes, such as agent training, can be encouraged.
Businesses can achieve success with useful customer insights. Speech Analytics can assist businesses in making use of insightful data to enhance the customer experience.
Types of Speech Analytics
Speech analytics can be classified into two types:
Real-time speech analytics is a contact center analytics solution that highlights specific keywords in an ongoing call. It is primarily intended for short-term outcomes, assisting agents in making course corrections before a conversation becomes problematic or an opportunity is lost.
Contact center managers can use real-time speech analytics tools to examine ongoing calls and get useful insights of the customer while the call is ongoing. Like how the agents are managing phone calls, how closely they adhere to standard procedures in real-time etc.
With real-time speech analytics, if a customer care agent is having trouble, they will immediately receive assistance via pop-ups on the screen. Thereby improving the customer experience. Today, all major businesses are benefitted from the use of speech analytics.
Analyzing interactions that have already occurred is known as Post-call analytics. It can look for specific patterns and trends in a group of calls or analyze specific details of an individual call. The use of post-call analytics will increase the number of monitored calls without increasing the number of quality assurance staff.
Real-time speech analytics enable you to keep an eye on conversations as they are taking place, allowing for quicker resolution of customer issues. Additionally, it is used to enhance compliance (thereby lowering the risk of violations and related fines) and partially automate the process of quality assurance.
Both the supervisor and the agent should benefit from real-time analytics. Speech analytics can inform an agent if they are speaking too quickly and too long silence when difficult questions arise. Not every agent has the experience necessary to answer all of these inquiries on their own, but managers frequently are unable to personally coach every call.
An effective real-time speech analytics solution can be useful in this situation. For example, this feature can pick up particular keywords and prompt pop-ups with customized notes to help agents talk about various topics while on the call, in addition to transcribing calls in real time.
The best part of real-time speech analytics is that it can alert the supervisor or team leader whenever some keywords, phrases or intents are detected that are critical to business. The supervisor can monitor the conversation and if required barge-in or whisper to the agent. So it helps in coaching the agent and can save a customer churn.
Call recordings and post-call analytics are still helpful for quality control and management, of course. Whether you are on the call in real time or not, it is always helpful to have access to key metrics for things like agent performance and frequent inquiries.
|Real Time Assistance||Post Call Assistance|
|Trigger real time action||Root cause analysis|
|Helps agent with live transcript||Identify the trends- like customer concerns|
|Live coaching (during the call)||Train the agents (post the call)|
|Improves customer experience||Improves agent performance|
Brands can identify areas of high customer effort and identify specific actions that can be taken to increase customer engagement and satisfaction using post-call speech analytics. For instance, if customers frequently contact live agents after being unable to complete a specific task on the brand's website or app, this insight can be used to enhance self-service functionality, boosting customer satisfaction and generating efficiencies for the business.
The ability of self-service tools, including chatbots, to contain customers within the self-service channel and avoid the need to escalate to more expensive live agents can be improved with the help of post-call speech analytics.
One of the keys to delivering a positive customer experience and raising customer satisfaction is being able to respond to inquiries quickly and resolve issues for clients at the moment.
Customers expect it as a fundamental need. Real-time speech analytics give your agents the ability to respond to inquiries quickly. They also assist supervisors in training new hires so they are prepared to handle inquiries in less time. If need be, the supervisor can jump into the call.
Understandably, a significant factor for many businesses is customer churn. And fostering those crucial long-term loyalties requires a positive customer experience.
If you search online, you'll find lots of cute and heartwarming suggestions for increasing customer engagement (like sending out catchy emails and holding contests), but, to be honest, keeping things straightforward is frequently what will keep customers coming back. Can you deliver a satisfying experience? Can you respond to inquiries without keeping a customer waiting? These are the fundamentals, and mastering them can often increase retention and decrease churn without the use of other sophisticated strategies (real-time speech analytics can help with this).
Real-time speech analytics assist companies in reducing costs in a variety of areas. For instance, they can help businesses avoid paying fines for non-compliance, reduce the need for callbacks by increasing call resolution rates, and steer customers toward less expensive channels like IVR or online self-service when they have questions.
Additionally, some businesses may discover that by automating specific processes after implementing real-time speech analytics, they are able to reduce headcount (and save money).
Contact centers can gain insights swiftly with speech analytics. It automatically organizes, analyses, and delivers insights based on what businesses wish to measure. With this information, contact centers' productivity, customer satisfaction, and cost-saving measures, both agent and customer attrition, can all experience significant changes.
Speech analytics can track and analyze the words and phrases that customers use when interacting with them. Understanding call drivers, including new issues, can be done using this. Managers of contact centers who are alerted about emerging problems can take the appropriate actions using speech analytics reports.
The design of the speech analytics solution makes it simple to do effective quality control on every client interaction. This solution is positioned to solve problems that will aid in efficient call center quality assurance.
Speech analytics may also identify client sentiment, giving businesses a more complete understanding of their target market. By concentrating on keywords and accounting for voice characteristics like volume and pitch, speech analytics can determine a customer's emotional state. This enables contact centers to gauge public opinion and carry out some targeted consumer interventions.
Speech analytics assists organizations in understanding their users' demands and concerns. Brands can improve their products/services and marketing strategies by understanding the needs and interests of their customers. Furthermore, these tools help marketers in sorting out data to understand their client’s nature and that eventually leads to higher levels of customer satisfaction.
By using speech analytics, you can identify each customer's preferences and tailor the services to suit their tastes. This improves quality assurance, customer retention, and conversion rates while increasing customer loyalty.
With speech analytics, you can understand your customers and their emotions better. This will help agents maintain a friendly relationship with the customers. As a result of this, later they can suggest a product or service that is a good fit for them. You can upsell or cross-sell products or services.
When you have a better understanding of your customer’s needs, you will not be limited to selling a single product. A sophisticated speech analytics software can assist you in identifying and developing numerous new cross-selling and up-selling opportunities. Based on your target customers' expectations and purchase intentions, you can offer them latest deals, and product suggestions that will appeal to them.
Customers' intents and expectations can be deduced using speech analytics software. As a result, a sales representative can easily target them with innovative products, services, and strategies. This reduces overall customer churn without requiring additional effort, primarily because satisfied customers have no reason to switch to competitors.
In terms of KPI, the integration of speech analytics into your contact centers' operating environment is a major accomplishment.
Speech analytics can immediately help to explain why a certain KPIs performance level is higher or lower than imagined. Speech analytics allows you to track key performance indicators (KPIs) such as the number of calls escalated to supervisors, the number of compliance violations etc.
The contact center is where speech analytics is most beneficial. It allows them to pinpoint why exactly customers contact a business and what makes them satisfied or even unsatisfied.
Additionally, it aids contact centers in enhancing agent performance, operational effectiveness, and compliance. As part of a larger Customer Relationship Management (CRM) strategy, the majority of businesses are now using speech analytics.
These businesses use the information gained from customer interactions to continuously improve operations across the board. Artificial Intelligence-powered analytics can score your calls automatically and identify the most impactful insights for immediate business improvement. Furthermore, with real-time recording and speech analytics, you can automatically trigger immediate attention and next-best action.
AI-powered speech analytics is indeed transforming how omnichannel customer service organizations operate today. So tell us, Would you like a demo?
Author Bio: Abhirami is a passionate writer whose forte is communication, possesses strong leadership qualities, and is often kind.