La Mobilière's Customer Service team receives a large number of emails every day without having visibility or quantitative metrics on requests. The result is a fragmentation of internal processes and a consequent loss of efficiency.
To address this issue, La Mobilière decided to partner with Indigo.ai to overcome these challenges and facilitate the work of the Customer Service department.
The project developed with La Mobilière is a combination of technology, knowledge and collaboration. Classifying such a large number of e-mails on very technical subjects was no trivial challenge, but with the use of modern and innovative artificial intelligence models we managed to achieve a high level of accuracy.
Our goal was to help La Mobilière handle its customers' requests more efficiently, saving time and effort for everyone involved in customer service activities. We created a system that classifies incoming requests, based on the collection of 1 million anonymous emails extracted from La Mobilière's databases. An automated service based on artificial intelligence to help classify incoming requests and emails, categorise them and process them in a more sophisticated way. The first step of the project was a semi-supervised analysis of the entire email history of the last few years. This allowed Indigo.ai to create a structured Knowledge Base to map all the different types of requests.
Indigo.ai has therefore developed a classifier capable of automatically labelling incoming emails with their area of interest and related subject matter. The classification of incoming emails allows La Mobilière to proceed with several actions to increase the efficiency of the Customer Service Department: sorting emails, creating automatic drafts to facilitate responses, proceeding with internal integrations to interact with management and retrieve data automatically. By relying on Indigo.ai's technology, La Mobilière can channel the huge amount of unstructured data coming in and get important information such as numbers, precise information from emails and the most common topics handled by the team.
Anonymous analysed e-mails managed by the classifier.
Knowledge Base areas created using the classifier.
classes of responses that can be automated by our AI technology
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