How AI Saves Millions in After-Call Work Costs

In many contact centers, agents spend several minutes typing manual call summaries after each interaction. How much money are you spending on after-call work (ACW) like this in your contact center? While average handling time (AHT) often takes more of the limelight in discussions about contact center costs, the time your agents spend between calls is likely costing you millions.

Building Blocks:

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Generative AI

Generative AI, such as ChatGPT, can be trained on existing data sets to intelligently understand language and create new content. Customer service is no exception—with generative AI, many mundane manual tasks can be automated.

Automating After-Call Work

In many contact centers, agents are required to create a manual summary of an interaction once the call is complete. This requires the agent to remember the various aspects of the conversation and accurately and succinctly document them before moving on to the next task. Often, agents will create handwritten notes on their desk to remember details of the interactions, which can pose a serious security risk. This manual call summary process can take several minutes—minutes that could be better spent helping the next customer. Further, manual agent summaries can be incomplete and inconsistent. Verint Da Vinci Interaction Summary changes this process completely by automatically generating a consistent, accurate, and secure summary of the interaction upon completion.

How Does it Work?

The first step of the process is to turn the audio of an agent and customer’s interaction into text using industry-leading Verint Da Vinci™ Real-Time Transcription. This solution provides a highly accurate transcript of a contact center conversation in real time. This transcript is then sent to a generative AI model, which will quickly produce a summary of the conversation. This summary can appear on the agents’ screens, for example, typically through Verint’s WorkAssist desktop widget. The summary can also be sent to a CRM or other backend system that can store it, along with the interaction information.

Generative AI

Generative AI, such as ChatGPT, can be trained on existing data sets to intelligently understand language and create new content. Customer service is no exception—with generative AI, many mundane manual tasks can be automated.

Benefits

The time-saving benefits of an automatically generated interaction summary are clear. But there are even more benefits than just the regained minutes.

  • An AI-generated summary will have more consistency and completeness than a subjectively written summary by an agent.
  • The agent can focus completely on the customer conversation, rather than trying to constantly remember everything that happened over the course of the call.
  • Automation removes mundane, manual effort from the employee to drive employee engagement and satisfaction.
  • Generating this summary provides helpful insight for the next agent who may handle a follow-up interaction with the same customer. This short summary can give
    the next agent the insights they need and help reduce handle time and improve the customer experience.

A Real-World Example

Verint is working with a large insurance company that is looking to reduce its after-call work costs. The company handles 15 million calls per year, and each call has an
average of 3.5 minutes of after call work. Most of this time is spent manually typing a summary of the conversation. Not only is the process time-consuming and expensive, but the results are inconsistent and often poorly written summaries. By automating this process with Verint Da Vinci Interaction Summary, after-call work could be reduced by up to 75 percent on each call, driving cost savings of more than $20 million per year for the company.

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