Users experience leads Technology.
Speech Analytics Technology enhances quality by improving agent skills, detecting taboo words, providing quality alerts, quality reporting, and enhancing First Call Resolution (FCR) metrics.
Speech Analytics Technology helps in process efficiency by reducing call volume, improving script adherence, enabling efficient search, and providing speech-to-text capability.
Speech Analytics Technology helps improve customer experience through Customer feedback, trend spotting, preventing customer churn, and emotion detection.
Speech Analytics Technology helps in sales by identifying competitive advantages, sales potential, sales risks, and detecting topics.
Speech Analytics Technology helps with compliance phrase spotting, auto-categorization, document consultancy calls, risk alerting, and fraud detection.
Speech Analytics Technology provides public safety with Threat call alert, improved emergency processes, relief for the dispatcher, and fast prioritization.
Improving Agent Skills - Using technology to develop employee skills is crucial in business. Examples include automatically selecting sample recordings for training and identifying employee weaknesses for personalized training. Technology aids in streamlining training preparation and assessment, benefiting long-term skill development.
Taboo Word Spotting - The use of forbidden words has an impact on communication within and outside organizations. It can lead to issues related to feelings, beliefs, or preferences of individuals. The use of forbidden words may cause conflicts or dissatisfaction in the workplace. Moreover, it may create a negative image in the community or society.
Quality Alerting - Identifying keywords indicating quality issues is a critical step in managing feedback and addressing problems. This process enables companies to address issues promptly, providing management with immediate notification to take instant action. This approach significantly minimizes the risk of recurring errors.
Quality Reporting - Improving service quality is crucial for sustainable business development. Using automated tools helps efficiently assess and categorize communications. Visualization through dashboards and reports aids in understanding trends and making systematic service improvements.
Reducing Call Volume - Recognizing the reasons for repeat calls to increase the First Contact Resolution (FCR) rate helps businesses improve their customer service processes efficiently. When a company can identify and address issues during the initial contact effectively, it helps reduce customer dissatisfaction, resulting in more efficient and satisfactory customer service experiences.
Script Adherence - Monitoring every call and conversation is crucial for efficient business operations. Accurately and quickly identifying script issues helps in pinpointing problems and refining scripts as needed. It's also a great way to assess how well agents adhere to their call scripts.
Efficient Search - Searching for important information within conversations can be challenging and time-consuming. However, with reliable tools such as a call recording system equipped with fast search capabilities, it can reduce traditional search efforts and enhance data analysis efficiency.
Speech to Text - Converting spoken words into written documents and generating a comprehensive call transcript provide a quick overview of the content of the conversation. Sending the document to customers via email helps ensure understanding and clarity.
Customer Feedback - Listening to customer feedback is crucial for the development of online businesses. Analyzing data from customer feedback may help us better understand their needs and issues. To achieve this, targeted filtering of customer feedback from all conversations can help us focus on the most relevant information and use it more effectively in business development.
Trend Spotting - In conducting online business, understanding the trends and hot topics emerging from all conversations can be immensely beneficial. It allows us to adapt and respond to customer needs appropriately. However, before we can do so, we need to classify the conversational data effectively.
Preventing Customer Churn - Monitoring and alerting for critical phone calls for immediate intervention is crucial in building customer confidence and satisfaction. Having an efficient system in place helps us to be aware of situations and enables us to address issues quickly and appropriately. It is essential to establish trust and satisfaction in customer service.
Emotion Detection - Identifying critical communication and alerting when emotional signals appear in customer interactions is essential for effectively managing customer relationships. Understanding these emotional cues helps businesses respond to customer needs efficiently. Moreover, identifying emotional signals helps businesses prevent issues before they escalate into customer dissatisfaction or loss.
Identify Competitive Advantages - In an era where online market competition is rapidly increasing, automatic competitive analysis is a crucial tool for investing in faster time-to-market product launches. It helps businesses gain insights into their competitors and understand what customers think about them.
Identify Sales Potential - Understanding the frequency of various customer requests helps us gain deeper insights into customer needs. Targeted identification of hot topics and threads within communication and promotion assists in developing more successful sales strategies.
Identify Sales Risks - Targeted analysis of customer experience, especially for dissatisfied customers, is crucial. Targeted identification of issues and enhancing success in problem resolution are essential components.
Topic Detection - Identifying common topics to derive FAQs and self-service topics is a crucial step in developing more efficient services or products for an organization.
Threat Call Alert - In the digital world filled with various risks, maintaining security is crucial for businesses of all kinds. One of the key ways to maintain security is by detecting and responding to breaches as they occur. Categorizing inbound calls and real-time alerting of threat calls is essential.
Improved Emergency Processes - A crucial aspect that organizations must prioritize to effectively deal with emergency situations. Structured classification according to events enables us to respond to various situations promptly and efficiently. By categorizing events and having organized plans in place for each event, we can ensure an appropriate response to emergencies.
Relief for the Dispatcher - Utilizing technology to aid dispatch work is highly beneficial. The Text to speech system converts text to speech, reducing time and increasing communication efficiency. Automated protocol creation and document completion further minimize errors and save time in operations.
Fast Prioritization - In fast-paced environments, the ability to swiftly prioritize is crucial. Whether it's detecting crises or clustering topics, automated prioritization of all conversations streamlines decision-making. Furthermore, real-time alerts ensure timely responses during emergencies.
Compliance Phrase Spotting - Automatically spotting if the mandatory compliance statements are used is an efficient way to detect non-compliance. Detecting deviations, such as incorrect usage of compliance statements, is an effective tool in promoting legal adherence within organizations. When deviations are detected, listing non-compliant calls provides organizations with necessary information to improve policies and processes to align more closely with the law.
Auto-Categorization - Categorization of calls according to compliance relevance and automatic archiving, with a retention period according to a category.
Documentation of consultancy calls - Transcription of calls for later approval or as evidence saves post-processing time for manual documentation.
Risk Alerting - Automatically filtering through many calls can help identify any suspicious behavior exhibited by customers or employees. It also assists in identifying potential legal threats against the organization, allowing for immediate responses in real-time.
Fraud Detection - To avoid regulatory penalties, early detection of potential non-compliance in various processes within the organization is crucial. Rapid detection helps mitigate the risk of penalties. Automated analysis of all conversations is important for identifying key information and accurately matching it with legal requirements.
Using Speech Analytics for compliance is crucial for businesses as it enables them to adhere to regulations and standards effectively. By analyzing customer and employee interactions, businesses can verify compliance with relevant regulations such as GDPR or PDPA and use the insights to improve operations in alignment with legal requirements and ethical standards. Additionally, Speech Analytics helps mitigate the risk of personal data breaches and enhances customer confidence in the proper and secure handling of their information.
For public safety work It is an important part of every city's infrastructure. Both from the point of view of prevention and relief of public disasters Especially during emergencies, it is necessary to rely on resources from all sectors. Our Analytics solutions can support your organization's work in this area as well.
Using Speech Analytics for compliance is crucial for businesses as it enables them to adhere to regulations and standards effectively. It helps confirm compliance with relevant regulations such as GDPR or PDPA and reduces the risk of personal data breaches. As for public safety, it's vital in every city, and our Analytics solutions can support work in this area.
This image illustrates the operation of a voice and video recording system integrated with Microsoft Azure and Microsoft 365 through the ASC Recording Insights platform, which stores data in Blob Storage. Users can conveniently search and replay recorded data. The recorder sends data to the database server (DB Server) via an export job. Then, ASC imports data from the DB Server through CIFS/SMB requests using TCP ports 445 and 139. The imported data is sent to ASC neo, which is the main recording system of ASC. The data in ASC neo is then transferred to ASC Recording Insights, where it is stored in Blob Storage in the cloud. The recorded data is integrated and stored in Microsoft's Azure cloud system for secure and fast access. Users can search and replay the recorded data through the ASC Recording Insights interface. All data is available for search and replay for analysis and verification as needed. In summary, this system helps in recording, storing, searching, and replaying voice and video recordings efficiently and securely, leveraging Microsoft’s cloud services for better data access and management. We are experts in Speech Analytics Technology. We can integrate our system with your existing recorder system. Even though it's not the ASC brand.
Speech Analytics is a technology that combines multiple disciplines to analyze audio data from customer and business conversations. It uses advanced engineering methods and tools to extract valuable insights. This process consists of the following main steps:
Speech Recognition uses Automatic Speech Recognition (ASR) algorithms to convert speech into text, for example using Deep Learning models such as Recurrent Neural Networks (RNNs) and Long. Short-Term Memory (LSTM) to increase accuracy in speech recognition.
Natural Language Processing (NLP) to understand and analyze text from speech recognition Using techniques such as Tokenization, Part-of-Speech Tagging, Named Entity Recognition (NER) and Dependency Parsing to distinguish and understand sentence structure.
Sentiment Analysis of received messages To understand the mood and attitude of customers using classification techniques Classification Techniques such as Support Vector Machines (SVM), Naive Bayes and Neural Networks to analyze positive, negative or neutral sentiment.
Data Mining and Data Analytics Using advanced data mining and analysis techniques such as Clustering, Association Rule Mining and Predictive Analytics to find insights and trends from audio data.
System Optimization and Customization: Continuous system improvement by customizing models to suit specific business contexts, such as training models with specialized data. (Domain-Specific Training) and using Transfer Learning techniques to increase system efficiency.