The Client
A car manufacturer often has to deal with a large influx of customer issues and maintenance requests daily. To sort through these requests it clusters them into various classes to then be passed on to relevant parties, mechanics, IT, and customer service. This results in thousands of possible classes that change over time as new models are introduced and suppliers change. With so many classes, any error is not just a lost opportunity, but an additional cost. As mistakes receive push-back from dissatisfied service representatives assigned out-of-scope issues, leaving customers issues unaddressed, and increasing costs. While they have already developed an AI model with a prestigious university to help with clustering, that model was only able to achieve 40% accuracy. They are looking for help in better accuracy
The Solution
The key problem we identified was the lack of communication on classes of interest. OneClick.ai’s meta-learning allows it to incorporate a wider range of customer data. By asking customers to specify classes based on the data they submit, our platform learned what types of classes they would be interested in. Customer data is then analyzed using a variety of techniques to build a better clustering model. This approach led to a model accuracy of 90%, a 50% increase over the previously best model.
The Benefits
The addition of an intelligent clustering model into their CRM system allows a level of efficiency never before possible. Customer issues are handled faster and more accurately than ever, and problems are correctly assigned to relevant processes the first time. This leads to a much happier customer base.
When it comes time to update the system, the platform nature of OneClick.ai allows a new model to be made in moments without needing any of the original data or team.
OneClick.ai 