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To show you can further improve the performance of your contact center, fill out the calculator below to discover your business’s ROI using InMoment’s conversational intelligence tools: Calculate your business’s ROI using InMoment’s conversational intelligence tools.
For a business, that means high costs and inefficient call center operations. Call centers, therefore, want to improve firstcallresolution rate, reduce call volume, and excel at customer service while reining in high costs. That adds up to 40+ days on hold for every person over the course of a lifetime!
It can be done through various means, including phone calls, voice messages, or any other audio recording methodbut its typically all handled by a contact center callrecording solution thats offered as a standalone tool, or as part of a CCaaS or workforce engagement management software platform.
Many call center leaders cite FirstCallResolution (FCR) as the most important metric to track. Research firm Frost and Sullivan callsFirstCallResolution the “home run” of call center metrics. What is FirstCallResolution? The reason?
A comprehensive needs assessment involves: Analyzing Performance Data: Dive into key metrics like Customer Satisfaction (CSAT) , FirstCallResolution (FCR) , Average Handle Time (AHT) , and other factors of QA scorecards. Ask: Where are the gaps in performance? Are there common trends indicating specific skill deficiencies?
These metrics include Average Handle Time (AHT), FirstCallResolution (FCR), transfer rate, and wrap-up time. Call transcription tools recordcalls in textual format for easier analysis. These features are valuable for elevating call center operations and improving their ROI.
For a business, that means high costs and inefficient call center operations. Call centers, therefore, want to improve firstcallresolution rate, reduce call volume, and excel at customer service while reining in high costs. That adds up to 40+ days on hold for every person over the course of a lifetime!
How Conversation Intelligence Works The core of conversation intelligences functionality is taking callrecordings and running this data through speech-to-text AI models, then analyzing text-based data from emails, chats, surveys, social feeds, and more to make sense of the context of the conversations.
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