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Call Center Analytics: 6 Types to Understand for Better Results

Sofia Peterson by Sofia Peterson
February 23, 2022
Call Center Analytics: 6 Types to Understand for Better Results
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Call centers, they are everywhere and they are critical to delivering top-notch customer service. Call centers also generate large volumes of customer-related data which needs to be analyzed. That’s where call center analytics has a crucial role to play.

Whether you have an in house call center team or opted for call center outsourcing, gaining a good understanding of different types of call center analytics is crucial.

Here are the 6 major call center analytics you should know.

1. Speech Analytics

This is a tool to measure the effectiveness of the call center conversations. It helps analyze a large number of calls to recognize, assimilate and analyze the requirements of the customers. It can also help identify emotional triggers and tone.

2. Text Analytics

This tool helps you analyze text or written documents. Unstructured text from social media posts, comments, etc. can be converted into data and patterns. This can be used to make your social engagement a lot more fruitful.

3. Desktop Analytics

Desktop analytics tools are designed to analyze all the activities of call center representatives on their desktops. The insights collected will help you measure the effectiveness of your systems and the performance of reps.

4. Cross Channel Analytics

Omnichannel customer service is the future and cross channel analytics is what you need to stand out. Be it social media, AI chatbots, or other means of communication, a cross channel analytics tool will help you optimize conversation on all platforms.

5. Predictive Analytics

This is one of the most prefered tools in the call center world which allows the representatives to view the history of conversations with a customer and identify the most impactful ways to communicate with them. This can boost the quality of customer services and your sales.

6. Self-Service Interactions

This tool helps you to refine your responses on self-service channels. By analyzing tons of customer queries and the suitable solutions, the tool will be able to suggest the most appropriate responses for chatbot and voice queries.

Based on your business requirements you can adopt multiple types of call center analytics and reap better results.

Sofia Peterson

Sofia Peterson

Sofia is a contributor at The Hack Post who loves to write about Technology. She also enjoys reading books and swims during her free time.

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