Poor customer service costs businesses about $75 billion annually. Given this tremendous loss, having poor customer service is not something you can ignore. To avoid ending up with a service your customers are unhappy with, you need to understand and answer their expectations effectively. And you can do this by listening to your customers, in other words, monitoring and analyzing their conversations.
Customer interactions across different service channels include invaluable insights about customer behavior, the latest trends, and business productivity. To unveil these insights, you need to apply in-depth data mining methods, and thankfully, with today’s conversational analytics technologies, you can do that easily.
Conversational analytics, also called conversational intelligence, converts natural language conversations into a machine-readable format and extracts data from them. Using artificial intelligence and machine learning technologies, conversational analytics collects, analyzes, and makes sense of interaction data from multi-channels.
According to McKinsey, live voice interactions through a call center are crucial in providing high-quality customer service in a digital age. Therefore, analyzing call center interactions which can be defined as call center analytics, becomes more critical in evaluating the customer experience.
Call center analytics gives essential details about customer service through collecting, measuring, and reporting performance metrics within a contact center. To track call data, evaluate agent performance, and determine service quality, call center analytics uses the following criteria:
It evaluates elements that directly impact the customer journey and gives businesses essential details about customer satisfaction, probability of customer loss, agent performance, campaign efficiency, etc.
Using analytics tools to uncover hidden insights in call center interactions is key to ensuring high-quality customer service. But not all analytics tools are created equally. To get the most out of this technology, there are some key features to look for:
Knovvu Analytics collects 100% customer interaction data and transforms it into actionable business intelligence. By applying advanced data mining and quality management technologies, Knovvu Analytics helps decision-makers objectively evaluate business performance and make the right decisions to improve customer service.
Knovvu Analytics outperforms the competition with the following features:
If Knovvu Analytics sounds like what you need, fill out the contact us form or request a demo now. Our team will contact you soon to figure out how we can help.
The term “user experience” was first used in the 1990s due to the rising use of solutions and interfaces that enable people to use products and services without a live intermediary.Read More
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