Many people’s first interaction with speech recognition technology came in the form of the dictation feature in Microsoft Encarta – the multimedia encyclopedia that used to be standard fare on every PC manufactured in the late 90’s and early 00’s. Needless to say, it was pretty underwhelming.
Dreams of dictating a random train of thought to the computer and having it spit out a perfect history paper for school were crushed. Luckily, speech recognition and analytics technologies have come a long way since then.
According to Research and Markets, the global speech analytics market is expected to reach $14.1 billion by 2029, growing by 20.1% CAGR between 2022 and 2029.
Given its widespread proliferation throughout many industries, it’s crucial to have an understanding of how speech analytics works and how it can benefit your organization.
This article will cover these basics and more to give you insight into the value of speech analytics and why its use is so widespread today.
What Is Speech Analytics?
At its core, speech analytics is a tool that automates the process of listening to customer interactions. Delivered as an enterprise software solution, speech analytics extracts information from customer conversations that might otherwise be lost.
In addition to using speech recognition technology to identify spoken words or phrases, many speech analytics solutions can analyze the emotional character of the speech (sentiment analysis) and the amount of silence in the conversation.
How Does Speech Analytics Work?
It is a multi-step process to take the unstructured data trapped in the audio of recorded calls and turn it into structured data that can be searched and analyzed.
The first step involves incorporating conversations from the source system (call recorder, VOIP stream) and the associated metadata such as which agent handled the interaction, what day and time did it occur, and who the customer was.
Next, the audio undergoes the speech recognition process where sounds are turned into text. At the same time, acoustic signals such as agitation and silence are extracted and text transcripts are normalized into a consistent form.
If multiple channels are used for customer contacts (email, chat, etc.), these nuances in the different formats need to be dealt with in order to use a single system and process for analyzing the contacts. The end result is a unified data view for all types of customer interactions.
Finally, the system automatically analyzes the interactions for certain language patterns to categorize or tag contacts as containing certain language or characteristics.
Advanced speech analytics solutions such as CallMiner also support automatic scoring. This combines the presence of certain language and other key metrics into an index that measures various performance indicators such as agent quality, customer satisfaction, emotion, and first contact resolution.
Discovery, category analysis, and score analysis is achieved through a web interface that allows users to search for contacts using any criteria, visualize data in any number of ways, and conduct automatic topic analysis.
All of this data can be put into action by providing direct feedback to analysts, supervisors, and agents through notifications and reports.
Speech Analytics Use Cases and Benefits
Speech analytics is used across an array of industries today. According to Research and Markets’ Outlook on the Speech Analytics Global Market to 2029 report, market growth is driven by factors such as the continuous growth in the use of speech analytics by call centres as well as increased need and growing demand for:
- More robust reporting and data visualization by retailers
- Solutions to drive customer experience and engagement
- Solutions for identifying consumer needs and interests
- Risk mitigation and compliance
- A deeper understanding of agent performance
Speech analytics offers myriad benefits across its many use cases. Here’s a look at some of the most common use cases for speech analytics and their benefits.
Gaining Customer Insights
Gaining customer insights is one of the most common use cases for speech analytics. There are many valuable insights hidden in the unsolicited feedback in customer interactions, and speech analytics can help you extract that value and better understand your customers, their needs, their sentiment about your products and services, and what motivates their behavior.
Conducting Competitive Analysis
The same customer interactions that have a wealth of hidden insight into your customers are also filled with hidden gems about your competitors.
For example, customers may mention things like how your pricing compares to your biggest competitor, what they feel your competitors do better than your company or vice versa, and more.
Improving Agent Compliance
Companies in industries such as collections, healthcare, and financial services have stringent regulations to comply with, and many of those requirements involve what can, cannot, and must be said during customer interactions.
Speech analytics can help to ensure your company maintains compliance by monitoring interactions to detect the sharing of health information or sensitive financial information, whether collection agents state the Mini-Miranda at the start of communications with a debtor, and whether agents are using acceptable language and behavior in accordance with the Fair Debt Collection Practices Act (FDCPA).
Some speech analytics solutions monitor interactions in progress, alerting agents to risky behavior to reduce non-compliance.
Enhancing Self-Service Offerings
Many consumers today prefer to engage with companies through channels other than phone calls, such as email support, chat, or self-service knowledge bases.
When customers don’t find the solutions they need using your self-service channels, they typically call the customer service line.
By leveraging speech analytics, you can identify missing answers and solutions in your existing self-service offerings when customers say things like, “I couldn’t find the answer on your website,” or “The chat agent directed me to contact a live agent.”
These insights will help you shore up your FAQs, knowledge base, and chat services to include solutions to these issues.
Improving Call Centre Metrics
Tracking call centre performance metrics requires monitoring all interactions across communication channels.
Speech analytics and conversation analytics software monitor every interaction on every channel, converting unstructured information into structured data to aggregate, analyze, and explore data on all customer interactions.
A speech analytics solution can help your business:
- Reduce first response time (FRT): By enabling agents to handle calls more efficiently, they’ll be able to answer more customer inquiries in less time, shortening customer wait times on hold.
- Reduce average handle time (AHT): CallMiner Eureka offers real-time, next-best-action guidance to empower agents to get to the root of customer issues and resolve them quickly.
- Minimize customer effort score (CES): Speech analytics provides deeper insight into the customer journey so that businesses can simplify it, making it easier for customers to find the answers they need when they need it.
- Improve first call resolution (FCR) rates: By providing real-time agent guidance during interactions, speech analytics empowers agents with the right knowledge to resolve issues fully during a single interaction. In addition, it helps to identify gaps in agent knowledge so that companies can more effectively route calls to the right agents.
- Improve customer satisfaction (CSAT): Analyzing every customer interaction provides deep insight into what drives customers’ needs, their opinions, and emotions, enabling companies to proactively craft a compelling customer experience that meets customer needs at every touchpoint.
Boosting cross-selling and up-selling
When you provide an exceptional customer experience, you’ll drive customer retention and loyalty, earning you repeat business and valuable referrals.
With analysis of every interaction throughout the customer journey, you’ll develop a deeper understanding of what drives customer buying behavior, so you can fine-tune the buyer’s journey from start to finish to increase sales and conversions.
A speech analytics solution helps retailers and e-commerce companies understand customer expectations across every channel, provide real-time next-best-action guidance to agents for cross-selling and up-selling opportunities, and refine marketing campaigns to reach the right customers with the right messaging that drives buying behavior.
Gaining Product Intelligence
Insights from the people who use your products are invaluable for innovation. Speech analytics solutions gather and analyze interaction data across channels such as comments, suggestions, and feedback for insights that can help you develop new products, enhance product features, and ultimately boost customer satisfaction.
Product intelligence solutions help you gain visibility into what your customers value most, improve the quality and safety of your products — such as taking action on safety issues to avoid product recalls, and analyze solicited and unsolicited feedback to inspire new features and new products.
What’s the Bottom Line?
Speech analytics can extract valuable business intelligence that would otherwise be lost in random call sampling.
Traditionally, the most powerful returns are realized in the contact centre, where speech analytics can be used to identify the reasons why customers call the company and what causes dissatisfaction. It also helps contact centres improve compliance, operational efficiency, and agent performance.
Today, many companies are implementing speech analytics as part of a greater Customer Relationship Management (CRM) strategy, using the intelligence mined from customer interactions to continuously improve processes throughout the entire business.This blog post has been re-published by kind permission of CallMiner – View the Original Article
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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.