Client support chat

Chat data contains a lot of valuable information

In the world of insurance, customer support is a key player. That is why our client, a Swiss insurance company, wanted to evaluate their recently established live customer support chat. More precisely, they wanted to find out what topics were addressed in the interactions between their customers and insurance agents, as well as receive insights on the questions that had been asked. Doing so, they could use the data to improve their system, and therefore support their client better and more efficiently.

How to get deep insights out of your customer support chats

As important and informative as customer chats are, they can often be arduous. The number of requests and questions is constantly increasing, and they can be as diverse as they can be complex. Manually extracting valuable insights from those correspondences is not an easy task and a time consuming one. Therefore, we applied a 4-step approach, leveraging natural language processing with artificial intelligence algorithms to be able to provide our client’s  customers with the best possible advice. Also, once all the data was analyzed and the insights extracted, we were able to prototype a chatbot to automate the support chat.

Topic recognition
AI anonymization

We anonymized the chat protocols using the Swisscom Anonymization AI Enabler

Since the insurance chat protocols contain a wide range of sensitive information, we had to ensure data privacy. The anonymization process masks any personal identifying data such as names, phone numbers, addresses, dates and birthdays, as well as insurance policies and car registration plate numbers.

Impact by leveraging AI



questions and answers paired



major topics identified

Zeit gewinnen


less time consuming

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