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USE CASE

Customer Handling and Call Center Optimization

 Financial Services Use Cases

Objective

  • Improve customer experience and reduce handling costs
  • Map the query by the customer to appropriate resolution section 

Outcome

  • An improvised automated method of Exploratory Data Analysis that segregates the data and provides numerical & graphical analysis based on the factors such as Date/Time, Location, Self Made Complaints, user profiles and past interactions.

  • Improvised NLP techniques + real time processing can accurately pinpoint/classify the complaints into groups.

  • Send high risk, complex complaints to the more experienced customer support agents.

  • A multi-classification AI model to give suggestions for possible resolution.

  • The model can also be used as a backend mapping engine for Chatbots and Customer Issue Resolution applications.

  • The solution can be delivered through APIs and custom application

Business Value

  • Address the complaints of customers, maintain trust and ultimately - retain. 

  • Improve case deflection, the rate that customers are able to find their own answers to issues that they would have otherwise called support for.

H2O's AI and Data Approaches

  • Conduct Exploratory Data Analysis on Customer Complaint Data. This data in the form of a Dataset will be Analysed, and numerical as well as graphical analysis will be provided. Answers to questions such as which location has the most complaints, what time period, is the complaint made on behalf of the user or made by the customer, etc. shall be provided in an organized manner.

  • NLP Techniques will be used to process the data, which can be in the form of a dataset or realtime.

  • H2O AI App:  
    • Import Data and Data Prep ( Complaint Data)
    • Exploratory Data Analysis to analyse the aforementioned points.
    • Interactive Dashboard where insights are displayed based on the searched tags, percentage rank of complaints ( #1 Rude behaviour, #2 Issues, etc.) There will also be percentage comparisons as the data increases ( Complaints in xxx domain are 15% higher, etc.) Top increases, top decreases
    • Natural Language Processing Apps
      • Applying NLP models to obtain tags based on meanings.
      • To interact with the Natural Language Processing Apps, you must log in with your H2O Cloud Account. If you do not have an account, you can learn more by requesting a demo here. This app demonstrates the use of machine learning as part of an overall plan to minimize employee attrition. Users can view predictions of employee departure, forecast churn rates, and identify relevant factors contained in employee data.

Resources

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