Use classification for concrete, automatable actions with Akio Interaction Analytics
Analysis of incoming interactions, providing information on the sentiment and topics of requests.
Key features include interaction categorisation, workflow efficiency improvements and targeted message routing. A feature that allows supervisors and agents, via filters in particular, to manage their workload more efficiently. The aim is to improve customer satisfaction by streamlining request handling, reducing unnecessary transfers between agents, and automating certain processes to improve service quality.
Overview
At a glance
Intelligent interaction analysis for optimised customer service
Leveraging Natural Language Processing (NLP) to automatically detect sentiment and topics in messages, enabling targeted routing and efficient categorisation of customer requests.
Increased efficiency and enhanced customer satisfaction
Thanks to new filters and process automation, agents can more easily manage their workload, reduce transfers and offer a smoother, more personalised customer experience.
Key benefits
Advanced NLP integration
Advanced Natural Language Processing techniques to analyse customer interactions
Enhanced categorisation
Agents can categorise incoming interactions, giving them greater insight into customer needs and sentiments
Dynamic filtering
New filtering capabilities allow supervisors to view the workload associated with specific subjects
Targeted routing
The system routes messages to the appropriate agents based on sentiment and subject matter, reducing response times
Customisable rules
Administrators can configure customisable routing rules, significantly improving the responsiveness of the customer service team
Automation
The module paves the way for increased automation in customer interaction management, improving service quality
Sustainability
New features further refine the capabilities of the Akio Interaction Analytics module to meet evolving customer service demands
Detailed features
🧠 NLP as a tool for change
The use of Natural Language Processing transforms customer service by enabling real-time analysis of customer interactions to identify customers’ underlying sentiments and topics, allowing agents to respond more effectively.
🩺 Comprehensive data analysis
The integration of qualitative and quantitative data improves supervisors’ ability to understand not only the volume of interactions, but also their nature and underlying sentiment. This holistic view enables better strategic decision-making.
✅ Workflow optimisation
The introduction of dynamic filters that display the volume of requests by subject allows agents and supervisors to prioritise their work more effectively. This capability can lead to faster resolution times, thereby improving overall customer satisfaction.
💼 Enhanced agent experience
By categorising requests according to specific topics, agents can better manage their workload and focus on priority tasks, which can lead to increased job satisfaction and performance.
✉ Smoother customer interactions
Akio Interaction Analytics routes messages based on subject matter and sentiment significantly reduces the likelihood of customers being transferred between agents.
📈 Relevant Performance indicators
Analysing both the volume & sentiment of requests leads to better performance metrics for customer service teams for a better understanding of customer needs.
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📅 Upcoming upgrade and automation
The system is undergoing continuous improvement, with a focus on automation. This development aims to reduce manual workloads and to increase the accuracy and speed of responses.