Virtual assistants like Siri, Cortana and Alexa as well as other speech synthesis techniques have solved many customer use cases by offloading repetitive and mundane searches or activities. Customer-oriented businesses leverage this technique to provide better operational efficiency and improve customer experience. They can then run analytics over the voice/audio content to derive predictions.
Many start-up businesses & products have been acting as a platform to collate and aggregate untapped audio and voice data, either in its raw phonetic form or converted into text. This text, when run through speech analytics, identifies the mood, context, sentiment of a customer or group of customers, helping businesses to take strategic decisions and next-best action.
Putting Audio Analytics to Work
Domains including insurance, technology, financial services, telecom, governance and healthcare are leveraging audio analytics to generate insights into customer needs. Broadly, it is used to increase call center efficiency, streamline market research and even proactively manage risk. Here are some examples of how audio analytics are used.
Agent Analysis in Telecom & Insurance
In the insurance or telecom industry, it is easy to produce a transcript or report from an agent’s call with a customer. However, analysis of the report is still a manual and time-consuming task left to team members. Leading voice analytics solutions today go one step further and leverage speech to text or transcription technology which applies a language model to automatically piece together a full conversation and identify common, trending, and hot topics. Conversational analytics bring out the tone of the conversation and highlights from the agent’s responses. This provides the ability to see what the agent’s pain points are and if they require more training on certain subjects for better performance.
Information Governance & Litigation Case Detection
Ernst & Young, a leading company in information governance, has reported cases of “false and misleading representations in debt collection communications”, highlighting the findings from audio analytics recordings.
The Consumer Financial Protection Bureau (CFPB) and U.S. Commodities Futures Trading Commission (CFTC) have actively analyzed phone recordings and found that certain phone representatives were overly optimistic about the rehabilitation of debtors’ credit scores. It misrepresented the waiving of collection fees and misled debtors into believing that they must pay electronically.
The audio data was reviewed and confirmed by the CFPB. Additionally, the audio/voice analytics were used for proactively predicting the risks from the conversations. Audio analytics can detect fraud in the enforcement space. It can also save time and money where legally trained managed document review teams demand high hourly wages.
Health Care and Risk Prediction
Imagine that you could predict the risk of customer leakage before the call even starts, allowing the customer representative to prepare accordingly. The solution works by building keyword and key phrase search definitions within a speech analytics solution, and as the calls are processed, they are categorized by the keywords and phrases that define a search, which is customized for every customer. This information can be used to help improve clinical performance and marketing effectiveness as well as provide better customer service. Voice analytics enables auditors to review specific portions or points within any recorded conversation and utilize the information for their reports.
Voice analytics help in predicting customer complaints caused by misunderstandings, process issues or unrealistic expectations. Health systems can automatically transcribe and score every patient interaction to identify relative compliance risk and give next-best action to quickly address issues during the interaction.
There are other use cases that show the benefits of voice analytics when used in product improvement, marketing optimization and sales optimization.
Providers Helping Businesses with Audio and Speech Analytics
There are several providers in the market that offer solutions for voice analytics:
Voice Sense: A language-independent solution, predicts the individual’s tendencies by linking speech patterns to personal characteristics like intonation, pace, emphasis focusing on prosodic speech parameters (non-content based).
IntelligentVoice: This solution collates call center voice data and converts it into text therefore making e-discovery and compliance easy.
Invoca: Leverages machine learning-based speech analytics to classify calls and measure their quality and outcomes to improve marketing performance.
What is the Difference Between Voice and Sentiment Analytics?
Voice analytics focus on content of customer conversations (how it is said) to derive the context, tonality of conversation pertaining to product or services.
Sentiment analytics focuses on the current disposition of the customer to derive the happiness factor of the customer (positive, neutral or negative). It considers any interaction, demographic, or engagement life cycle information about the issues that matters most to the business.
These behavioral patterns help the business units predict next best steps to improve operational targets. It also assists in making strategic decisions to optimize marketing campaigns, promote cross-sell opportunities, personalize retention, and the list goes on. Some examples are predicting forecast market trends, customer segment trends, customer buying/loyalty behavior, or compliance/risk behavior.
Industry analysts predict a huge growth in speech and voice analytics. In fact, they expect the market size to grow from $941.1M in 2017 to $2,175.8M by 2022. There is a driving need and expectation for higher customer satisfaction and real-time analytics. The good news is that we can look forward to more technological improvements for increasing the customer experience!
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