An extension to the challenge of adapting existing hardware to support emerging digital channels is the need to implement some form of quality assurance on all new digital channels. While adding digital channels will expand the horizon for interacting with end users, it can create a new pain of needing to ensure that interactions on new digital channels are simultaneously seamless and high in user satisfaction. This task is difficult to manage because many companies are unsure how to track quality assurance on digital channels.
Monitoring the quality of a full 100% of interactions on all digital channels is no easy task, and requires the right technology and QA systems to handle it. With the right technology and proper implementation, comprehensive quality management on all digital channels on a global scale can be made easy and manageable. Through a combination of AI and analytics, any quality assurance program can improve to reach 100% of all interactions on all channels.
For example, sentiment and text analysis can be utilized to gauge and analyze an end user’s mood during an interaction. Other information about the interaction, like call recordings and interaction transcripts, are collected and stored as well. Data collected through sentiment and text analysis can then be compiled into an easy-to-use format based on highlighted metrics and KPIs. Other information, including interaction details and recordings, can be used for retraining and quality assurance purposes.
AI-powered sentiment and text analytics can also enable real-time monitoring. Through sentiment and text analytics, the AI element can detect if an end user’s mood or overall interaction quality turns negative. End users who are on the verge of leaving can then be automatically routed to a retention specialist. Negative interactions can also generate alerts that can be sent to supervisors so that analysts can be retrained and coached to perform better when faced with similar interactions in the future.
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