Call center voice analytics, also called speech analytics, is a process of analyzing call recordings between business representatives and business clients, or it is software to automate this process. In this article, we'll talk about speech analytics specifically for call centers and how it is used to solve the chain of common problems in a contact center environment.
By default, modern voice analytics is an AI speech analytics since voice analytics is based both on Automatic Speech Recognition and Natural Language Processing, which are representatives of Artificial Intelligence technologies.
So how does call voice analytics work?
Every call that takes place at a contact center is transcribed into text. The speed depends on the speech analytics engine. For instance, the Ender Turing engine provides real-time speech-to-text transcription.
Having all the voice communication in text, you can detect keywords, phrases, or sentiments of both clients and contact center employees; all the linguistic elements are usually easily configured in the user interface and don’t require an engineer to put hands-on at all. When defined words are mentioned in the conversation, a team or a specific agent is notified in the system or via email to take over the situation.
And you may wonder how it can be helpful for a call center? Let's have a look at the top 7 irreplaceable functions of call center voice analytics that can:
- Make sure your team follows all the corporate guidelines and the verification steps and if the communication practices meet your company's regulations. It would be particularly important for financial, governmental, and banking sectors, where fines and penalties might cause budget losses.
- Increase customer loyalty by providing automatic individual tips for better performance and customer care, therewith reducing customer attrition and winning more long-term customers.
- Encourage agents to mention special offers or services to boost sales. Track down which offers arouse the interest of your clientele the most and the least; improve or change the existing promotions to make them more attractive to your customer.
- Improve the leading call center metrics by automatically identifying the crucial mistakes of your agents. For example, FCR can be easily increased when you set the system to determine the patterns that lead to better results; the same applies to AHT. This will surely also enhance the overall customer experience at your enterprise.
- Help your employees to deal with challenging calls. Thanks to an immediate notification system, you will know in seconds if any shouting or complaint has arisen. Help an agent out and advise on how to handle such conversations.
- Provide self-coaching opportunities. The system can automatically prescore every conversation, identify the top convos according to a specific topic or tag, and then share the playlists with the team.
- Save time for your managers. Usually, the call center managers are overloaded with QA, team management, reporting, and other essential tasks. That would protect the managers from a burn-out, and it will give them the missing time and space to find new ways to improve their team or call center operations in general.
Overall, AI speech analytics is an irreplaceable tool for modern call centers and customer service teams, especially of middle and bigger sizes. It's a win-win solution for every business party: the enterprise, customer, managing team, and employees. If your employees and managers find their comfort in the workplace, your business will surely prosper.
Ender Turing platform offers one of the market's fastest and most accurate transcriptions. It's not an exaggeration. It's a reality that you can easily check during the demo.
You can also check our recent webinar on the related topic: 'How to make the most out of each conversation with Speech Analytics in 2022'.