With the aid of a programme called speech analytics, phone conversations are analysed for meaningful information, patterns, emotions, and behaviour. To analyse it, it is typically done with customer calls.
Other client engagement channels, such as social media, chat, emails, SMS, and others, can be included in this entire process.
In most cases, customer calls are recorded, but this tool acts as an addition or a distinct mechanism that can be used immediately or at a later time. It makes it easier to understand the dialogue. Customer behaviour patterns might aid organisations in planning their future strategies. It resembles a future revelation. Call centres are typically where you can locate it.
Speech analytics can effectively handle large amounts of unstructured data and can categorise hundreds or even thousands of hours of calls. Thousands of call recordings can be indexed. Additionally, it unravels and explores its lateral information.
Businesses typically have a tonne of data, but they struggle to use it. They can access unused data from phone conversations using speech analytics and use it to gain future insights.
Speech analytics provides the data with structure as a result. Managers can identify the regions where problems arise, problems with compliance, and several other tendencies, such as drivers. It is among the greatest gifts that AI has ever given us.
How is Speech Analysis Carried Out?
The three stages of the speech analytics method are indicated above.
Data that is unstructured
The source of information is data. Real-time phone calls, recordings, or any other source that needs to be examined serve as the data in speech analytics.
The method of speech analytics
The process of arranging the data to produce its findings is completed in this part. Let’s go over every step.
Arrange client conversations
We must first organise and classify the data.
Make a file
With the help of structured data, files and indexes are produced.
It involves constructing synthetic data from existing data. We are aware that audio mining is another name for the speech analytics procedure. We can increase the dataset with the aid of augmentation in order to search for data variances. It is a crucial stage in the procedure.
Examine the metadata
Metadata enables us to locate pertinent data and ensures that we have it for usage in the future so we may reuse it. We will find the information we need by analysing the metadata.
After data analysis, look for pertinent information. It’s time to share the knowledge and put it to use in various contexts.
Utilising the data is the final step of the entire speech analytics process. Analysis of the root causes, trends, quality control, scripts, compliance, and others.
Speech Analytics in BPOs
One of those industries that has leveraged technology and its capabilities to better understand its clients is business process outsourcing, or BPO for short. One of those tools is speech analytics.
When interacting, this tool can more effectively comprehend human viewpoints and use AI to assist in problem-solving. What does the client actually desire? What’s his goal here? What does he mean? Speech analytics can provide the answers to all of these queries. If the agents can identify the precise problem, real-time experiences can be more participatory.
The agent must have said, “This call will be recorded for future purposes,” which suggests that all of the discussions will be examined in the future to identify any warning signs, compliance issues, etc., that the company has to address.
BPOs have had a lot of difficulties in this area. It is impossible to ensure that people will always be successful when they are trained to search for warning signs and other concerns. However, speech analytics can always understand 100% of calls, including recordings. With this tool, even agent performance may be kept an eye on. Many businesses have been employing this service, including Amazon and Myntra.
Numerous businesses, including NICE, Genesys, Verint, Clarabridge, and Dialpad, provide this service. The BPO industry has been able to streamline the entire process with voice analytics. Additionally, they have improved consumer satisfaction.
One can only speculate as to how exhausting this work may be for people. They will eventually grow weary, and their emotions may interfere with the conversation. Because of their personal problems, they occasionally even have to be direct with the customer. BPOs have now used this product successfully and are no longer faced with these problems.
Speech Analytics in Telecoms
Another industry that has had trouble addressing client requests is the telecom sector. However, speech analytics completely altered it. They are no longer having trouble meeting customer demands.
Customers’ requirements may be understood by machines, and all of their questions are immediately answered. One telecom company serves a sizable number of consumers, making it challenging for the business to meet everyone’s needs. Customers also feel as though their issues and voices are not being heard.
The companies have been able to foresee potential problems that a consumer might have in the future and address them even before they manifest. Speech analytics deployment is the only thing that makes this analysis possible.
AI and machine learning are used to power it. Pre-built intent models are created to meet the majority of consumers thanks to machine learning and AI. You must have heard a machine ask you to enter random numbers so it might leap to other problems you might encounter. For instance, when you call a hotline, they instruct you to press 1 for English.
Customers are also given personalised messages to ensure that they enjoy the entire experience and are satisfied. The telecom business must deal with important concerns including attracting more consumers and ensuring that they pay their bills on time. They have benefited greatly from the insights provided by speech analytics.