Save the time and effort of your customer service, agents using AI
Automatically generate ready-to-send answers for categorized messages
Accelerate your communication, reduce errors, enhance your customer relationship
Automatically categorize the vast majority of incoming messages
Supercharge your customer support with artificial intelligence
Your customer service receives a large number of messages, and human operators manually answer repetitive queries. Sound familiar to you? The AI-powered customer support inbox ARIS can prepare ready-to-send answers, to significantly reduce mistakes and improve the efficiency of your team. It reduces their load, saves their time, and allows them to focus on tasks with more added value.
Classify, and generate follow up actions automatically
Automated intelligent message classification keeps your customer queries organized. The platform uses natural language processing to analyze the content of incoming messages and suggest an answer and follow-up actions in the connected back-office systems. ARIS can be deployed not only in customer service, but also for message dispatching (forwarding messages to correct departments), or to pre-process tickets in the ticketing system.
Fully adjusted to your needs
The platform learns from your data and is thus adaptable to your specific needs. It can be integrated with your systems, propagating changes to the CRM or booking system. It also improves continuously – with feedback from the field. Up to 90% of messages are automatically categorized, 75% have a ready answer, and 40% can be sent out automatically. And all this on-premises, or in the cloud.
A lending platform can automatically answer 60% of messages
A European-based, peer-to-peer lending platform provider deployed ARIS in their customer service operations. ARIS was able to categorize correctly more than 80% of the messages from day one and provide ready-to-send answers for 75% of them. All resulting in 60% of all incoming messages solved with minimal human input.
After ARIS implementation, it took only 10 seconds on average to complete the basic customer query.
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