Speech analytics is an innovative technology that automates the process of recording and processing spoken speech: recognition, translation into text format, and extraction of basic thoughts. The tool is most often used in contact centers. Where a business is built on constant telephone conversations, it is important not to ignore a single call, answer each one in a timely manner and answer customer questions. Automation of telephony allows you to more accurately identify marketing problems, improve the quality of communication with customers, and optimize sales.
However, innovation is used not only in business, but also in other areas of professional, social life, as well as in everyday life. This is an article about how the technology works, what are the advantages of using it, and how to choose an intelligent assistant.
The algorithm of speech analytics
- The sound recorder records the speech that needs to be processed. It can be a phone conversation, a conference, a meeting, or a meeting.
- Conversation processing. At this stage, the machine separates the audio tracks of the interlocutors. This is necessary in order to accurately recognize everyone’s speech. Sometimes the paths intersect. This means that the interlocutors speak at the same time, interrupting each other, which can make it difficult to recognize.
- Converting a conversation to text. At this stage, the AI identifies sounds and letters, then adds syllables and sentences from them.
- Decoding. The resulting text is analyzed depending on the tasks set. For example, you can program the system to determine the emotional coloring of a conversation, recognize keywords or phrases, and identify topics and tags.
- Classification of data. Here, the robot shelves information about keywords, topics, and other identified aspects of the conversation. If the technology is used to work with clients, it helps to determine the most frequent requests, effective solution methods, the mood of callers, and other parameters.
- Data visualization. For clarity, the robot builds graphs or diagrams in which it displays the data obtained at the classification stage.
- Analysis of the received data. At the final stage, AI identifies patterns, draws conclusions, and forms possible solutions.
Speech analytics for business
The introduction of speech analytics technologies into the business allows:
- Improve the quality of service. Monitoring telephone conversations allows you to identify the strengths and weaknesses of marketing approaches, for example, which problems customers most often address to the manager and which of the proposed solutions work most effectively.
- Track the effectiveness of advertising campaigns by determining the audience’s reaction and determining which techniques have found a positive response and which have failed or caused a negative public reaction.
- Improve the quality of feedback: the manager gets the opportunity to respond to the problem faster and make prompt decisions.
- Increase sales volumes. Using AI helps determine which sales tactics bring the most conversions and which ones work poorly.
- To increase the effectiveness of staff training. Transcripts of dialogues can be used as training materials at training and advanced training courses for managers. Experts can use excerpts from the transcripts to illustrate the strengths and weaknesses of the negotiations.
- Monitor managers by identifying the most effective ones. Each company has a department staffed by specialists who monitor the actions of managers during a dialogue with a client. They monitor the dialogues, determine whether the manager adheres to the script, whether he is polite enough, and how he reacts to a particular situation in the conversation. Control is necessary to help managers apply more effective negotiation schemes, as well as respond in time to conflict situations with clients. It is impossible to monitor all calls, as there may be several hundred of them per day. Therefore, the check is carried out selectively, covering no more than 25% of calls. The introduction of speech analytics will increase this indicator to 100%, as well as immediately receive ready-made reports on each call and collect a database.
- Accumulate a database of negotiations in order to view it, analyze it, and compare current results with previous ones.
Speech analytics technologies
- Automatic transcription into text of audio and video clips, as well as conferences and telephone conversations.
- Voice control. This technology allows you to control devices by voice, for example:
- giving tasks to the navigator in the car;
- control devices in a smart home;
- search for information on the Internet.
- Recognition of emotional tonality. Conventional services help to recognize, decode and record speech, and some – to carry out a number of analytical manipulations. Emotion recognition is a more advanced level of speech analytics that allows you to determine the speaker’s mood, evaluate his exclamations, delight, uncertainty, irritation. Understanding the speaker’s emotions is an important aspect in evaluating the course of negotiations. Not all people raise their voices or start talking rudely when something doesn’t suit them. Many people behave with restraint, but this does not mean that they are satisfied with everything. Emotional state recognition technology helps to identify hidden emotions and turn the conversation in the right direction.
- Translator. These systems speak many languages. Some can only be used as translators, while others can also recognize speech and transform it into text in the desired language.
- Analytical systems are robots that can extract the necessary information from speech, for example, keywords, phrases, identify topics, agreements, dates. Such programs are useful for researching customer needs.
The use of speech analytics in various fields
Artificial intelligence for the analysis of human speech is used not only in the field of trade, but also:
- In banks and other financial institutions. AI is used to monitor calls in order to analyze consumer requests, as well as detect fraud.
- In medical institutions. Transcription of the dialogue between the doctor and the patient at the reception allows you to free the doctor from the need to record manually and gives more time to find out the details of the condition and select a treatment regimen. The technology helps to improve the quality of medical care, as well as monitor compliance with standards within the institution.
- In the contact centers of large companies. They usually employ dozens, and sometimes hundreds, of operators. It is almost impossible to monitor the work of everyone, identify mistakes or the best employee without using neural networks.
- In transport and logistics services, neural networks are used to negotiate between operators and drivers on a flight, as well as partners.
How to choose a speech analytics system
It should be selected based on the specifics of the business. For example, if a company works with foreign partners, it is important for it that the neural network understands foreign speech. If this is a medical clinic, then the robot must correctly recognize medical terminology. But there are also a number of general parameters that you should pay attention to. So, the service should:
- It is easy to integrate with the company’s existing CRM platform;
- have analytical skills, emotional background recognition;
- transcribe dialogues with high accuracy – at least 90%;
- suitable for real-time operation;
- have good technical support.
And, of course, its cost should correspond to the list of possibilities and the quality of work.
The best speech analytics services
| Title | What he can do |
| Roistat | Records and transcribes the dialogue, highlighting keywords and phrases.Evaluates the operator’s work according to 22 criteria.Monitors script compliance.Analyzes dialogues, identifying negativity, complaints, refusals, and gratitude.Notifies you of problematic calls.It has 21 dictionaries to check.Easily integrates with the phone communication server |
| Mango Office | Recognizes and translates audio into text with 95% accuracy.Classifies dialogs according to the specified parameters.Recognizes emotions.Writes reports according to 12 criteria (negotiation time, script compliance, level of politeness).It uses 32 dictionaries for analysis, which can be supplemented. |
| Speech analytics | Transcribes with 95% accuracy.Compiles the text of the negotiations in the form of a dialogue.Evaluates the conversation according to 24 parameters, including pauses, interruptions.Recognizes cases.Analyzes speech in 20 dictionaries, can identify phrases of complaint, aggression, discontent. |
| Imot.io | It can work with audio recordings of telephone conversations, as well as video conferences in Zoom. Recognizes speech at 90%, emotions with up to 70% accuracy.When working with calls, it can sort them by specified words and tags.It works with dictionaries with specialized terminology, which can be supplemented |
| Tinkoff VoiceKit | Analyzes calls and chats with increased accuracy: it can even detect sarcasm.It processes large amounts of data quickly.Organizes calls by category.Creates reports based on the specified parameters.Conducts semantic analysis, i.e. searches for information not by words or phrases, but by the meaning of the context.It uses 21 dictionaries for analysis. |
| WordPuls | Analyzes calls and chats with increased accuracy: it can even detect sarcasm.It processes large amounts of data quickly.Organizes calls by category.Creates reports based on the specified parameters.Conducts semantic analysis, i.e. searches for information not by words or phrases, but by the meaning of the context.It uses 21 dictionaries for analysis. |
| BSS Speech Analytics | Analyzes calls and chats with increased accuracy: it can even detect sarcasm.It processes large amounts of data quickly.Organizes calls by category.Creates reports based on the specified parameters.Conducts semantic analysis, i.e. searches for information not by words or phrases, but by the meaning of the context.It uses 21 dictionaries for analysis. |
| 3iTech | Recognizes queries by topic.It uses 20 dictionaries for speech recognition.It can determine the caller’s emotional state, as well as their gender and age.It has a setting for notification of incidents related to conversations in chat rooms, by phone, instant messengers or e-mail.Adapts to work with specific vocabulary.Recognizes speech in Russian, English, Kazakh, and Uzbek. |
Conclusion
Speech analytics technology is an effective tool that simplifies the work of marketing departments, as well as employee negotiation monitoring services. Using neural networks, a person was able to shift some of the heavy routine work to a robot:
- analyze the negotiation process;
- identify script violations;
- identify problematic calls and respond to them quickly;
- track the emotional background of the conversation, work with objections from the manager;
- identify working and non-working techniques aimed at increasing sales;
- identify the most effective employees.
