Conversation summarization is the ability for a technology, now typically artificial intelligence (AI), to process vast amounts of textual or spoken data from interpersonal communications—such as meetings, phone calls, live chats, or email exchanges—and provide a brief summary that captures the main intents, issues, outcomes, and sentiments expressed during those interactions. If you’ve used services like Zoom or Gong, you likely use this type of technology regularly to save you time from taking meeting notes – or to quickly remember what you were supposed to do in that meeting when you were distractedly browsing Instagram (it happens).
But today we’re going to be discussing how customer service organizations are applying conversation summarization to their customer interactions and the many benefits they’re seeing – from basic efficiency to deeper insight. And while it’s less flashy and interactive than virtual assistants and other forms of AI, conversation summarization is without a doubt the customer service operations workhorse that your team needs.
Conversation Summarization drives greater efficiency
While there’s lots of different kinds of efficiency, conversation summarization kind of checks all of them off – and provides value to multiple stakeholders within the customer service organization.
- Time efficiency: This one is pretty obvious, but AI is way faster at creating a summary than a person is. Especially if the alternative is listening to a 15-minute phone call or reading a 10-minute chat transcript. Which is about as fun as it sounds.
- Process efficiency: In customer service, agents can spend multiple minutes writing a summary of their recent customer conversation. With a summary, that after-call work is essentially eliminated saving them time, which results in…
- Cost efficiency: Wrap-up work can take agents away from live customer interactions, resulting in longer wait times and the need for more agents. Conversation summarization takes lengthy, low-value tasks and automates them instantly, giving each agent more time to focus on customers.
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Conversation summarization enables easier Quality Assurance
In customer service quality assurance, understanding what happened within all your customer interactions can be a tedious task. Often, a QA analyst must listen to the entire call or read through the entire transcript multiple times in order to grade each conversation – or even answer simple questions like what was the call about and whether the customer’s issue was resolved.
Automated summarization tools can assist in quality assurance by providing that information at-a-glance – and even flagging important data points like resolution. This way, analysts can already start with unresolved conversations to focus their review efforts where they are most needed, improving the overall quality of service.
Conversation summarization generates customer insights at scale
Summarizing customer interactions across your business can provide valuable insights into common issues, customer sentiment, and feedback trends. Something as simple as understanding which product issues tend to have the lowest resolution can be extremely valuable – and not just to the customer service team. These insights can be used to inform business decisions, improve offerings, and enhance customer satisfaction.
Why all conversation summarization isn’t equal
So, if I’ve done my job right, by now conversation summarization should seem like a pretty good idea that – like the title says – you have no reason not to use. But if you’ve been reading this blog for a while you probably also know that not all summaries are created equal.
Good summaries are not just a generic abstract of events. A good summary is one that answers the questions that are relevant to the asker – in this case, a customer service professional. But a generic summary doesn’t know the specific questions you’re looking to answer, or how to scrutinize the conversation to validate those answers. This is why at Loris, we set out to answer these specific questions for every conversation:
- Why did the customer contact the company?
- What did the agent do in the conversation?
- Was the customer’s issues resolved?
- What did the agent do to follow up?
- How satisfied is the customer following the interaction?
In summary…
Conversation summarization is not just a technological upgrade but can be used as a tactical or strategic asset no matter the size and maturity of your customer service operations. If your organization is focused on driving up efficiency and cost-effectiveness, it can deliver those easily. And if you’re interested in gathering deeper customer insights, it can help your team focus on higher value work and analysis. As more organizations incorporate conversation summarization, it will also create more trust in the idea that AI can augment and improve the way we work instead of just being a replacement technology.
Want to get a live look at how Loris does conversation summarization? Register for your own self-guided product demo.
