Use Case

Customer Service Automation​

Manual processes in customer service significantly inflate operational costs due to prolonged engagement durations, varying levels of CSR expertise, and repeated incidents from unresolved issues. Implementing an intelligent automation framework can mitigate these challenges by classifying interactions into live agent resolution, bot-assisted CSR journeys, and fully automated resolutions.

This approach not only enhances interaction volume and resolution rates but also drastically reduces the cost per serve. By leveraging real-time data, machine learning, and unique automation workflows, companies can achieve a minimal bot volume mix of 60%, aiming to lower costs by up to 90%

Problem

Manual Processes Inflate Costs ​

Engagement Duration

"Cost per serve" tracks interaction expenses. Longer interactions mean higher costs, emphasizing the need for prompt resolutions.

CSR Expertise

Not all CSRs can handle multiple chats concurrently; this skill is limited to a select few, with an average capacity of 4 chats.​

Region & Language

Another factor impacting the cost per serve is the language used during interactions.​

Resolution

Failure to accurately resolve a customer's issue often results in repeated incidents. This exponentially inflates the cost spent on resolving the same problem for the same customer.​

Solution Ecosystem​

An intelligent automation solution, which aims at containing the entire customer services cycle, possessing following characteristics:

Impact of CS Automation​

Learn more on how we can help automate your contact center!

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