What is Speech Analytics?

Speech analytics is a solution that transcribes voice interactions, usually phone conversations, and discovers insights to help enterprises and governments to improve their business and operation. It combines various artificial intelligence and machine learning technologies in speech recognition, natural language understanding, clustering, and others.

How Can Speech Analytics Help Businesses?

Speech analytics software like Fano Labs’ Callinter can analyze all voice interactions of enterprises and governments to identify areas of business growth; improve operational efficiency; follow regulatory compliance, as well as enhance customer satisfaction.

Gain Business Insights

Most business operations involve interacting with customers on a daily basis via service hotline or live chat systems. With speech analytics, businesses can make full use of these interactions and gain invaluable insights on customers, the market, and the businesses themselves. Analyzing calls and client inquiries can help businesses discover potential sales opportunities, and understand the hottest topics and trends with a more accurate view into their customers' needs. One of the use cases is for contact centers to identify potential churn customers through analyzing complaints, and follow up with customer retention strategies.

Automate Risk Control Work

Speech analytics can be used as a monitoring tool for regulatory compliance in banks and financial services. In order to manage potential risks for both the institution and the customer, sales interactions are strictly monitored by the internal compliance team and financial regulators to make sure proper disclosure, due diligence processes are conducted. During any solicitation or selling practices of investment products, the relationship managers are required to perform suitability assessment and ensure investors are aware of their rights, benefits, and risks. Analyzing these calls can detect any mis-selling or amiss practices and protect businesses from the risks of heavy fines and lawsuits.

‍Enhance Operation Efficiency for Quality Assurance

Typical contact centers carry out quality control by sampling a small percentage of calls for monitoring, yet the processes are tedious, ineffective, and costly. The capability to analyze 100% of customer interaction means Speech Analytics can provide a more comprehensive view of customer engagement without the need of adding any human resource (in fact, it can even reduce the number of quality assurance staff) in less time as well.

How does Speech Analytics work?

The entire process of Speech Analytics adopts different technologies to serve in the following key areas:

Speech-To-Text

Automatic Speech Recognition (ASR) technology first transcribes the audio files into text. Most of the ASR engines in the market require users to set a default language before processing the transcription, which means it only supports one language at a time. However, this might not be practical in places like Hong Kong, where people speak different languages in one single conversation. Fano Labs has developed a speech technology that can auto-detect language and can be used to recognize language switches on the fly, which fits perfectly for multilingual environments. The generated transcription with high accuracy is the foundation of subsequent analysis.

Speaker Separation

On many occasions, enterprises and governments need to store phone recordings for many years due to regulatory or compliance reasons. In order to reduce storage space, these recordings are usually reformatted into mono recordings. The voices of the agent (service representative), the customer, and sometimes possibly multiple speakers, are combined into the same audio channel. With Speaker Diarization technology, it can distinguish and segregate multiple speakers from these mono channels in order to differentiate the roles of the speakers.

NLP Analysis

After the transcription is generated, it is then passed down for analysis. With some basic speech analytics software, their analysis work is limited to keywords detection instead of fully understanding the context of the call. For obvious reasons, this is usually not good enough, as people can communicate their views in many different ways without mentioning specific keywords. Therefore, Fano Labs has also offered Natural Language Processing (NLP) for advanced, high-accuracy text analysis:

Understand the context

NLP can identify the intentions of a phrase based on the full context, which makes it more robust than keywords. For example, in retail banking, “I lost my wallet” would imply “card loss” without having to say the word “card”.

Speech Pattern (or Text Similarity)

By detecting similar phrases, the speech pattern technique is useful for assessing whether agents have followed their scripts properly, such as greetings, disclaimers, closing.

Business Logic

A tool for enterprises to better categorize their calls based on different business nature. For instance, understand why customers are calling, identify high-risk interactions (e.g. mis-selling or false statement), or detect any missing steps or activities.

Dashboard and Reports

Dashboard, various data visualization, and reports are generated to facilitate business users and operation managers to better understand their business and operation at both high and granular levels. These data include the trends and hot topics, the causes for long handling time, abnormalities in call traffic or spike, or even why certain telesales can close more deals than the others. Enterprises can further adjust different business strategies and better utilize resources.

Score Card

Score cards are used to evaluate the quality of the customer service calls and the performance of the agents. They are configurable based on business requirements through detecting multiple factors, for instance, whether agents have followed the required guidelines or scripts, any high-risk behaviors, cross-talk, silence time, speech rate, and so on.

Intent Cluster

In cases where the business receives novel inquiries that they do not anticipate in the first place, the intent cluster is a way to discover the uncharted waters. By leveraging unsupervised learning, Fano Labs has introduced the Intent Cluster feature that automatically clusters data. This allows business users and operation managers to easily discover new topics raised by customers for business improvements, and also to finetune any existing business logic or call classification they configured in the system.

Learn more about how Speech Analytics can help your business here: https://www.fano.ai/solutions/speech-analytics-callinter