CASE STUDY

Smart AI Customer Service Assistant For A Financial Business

Customer Profile
Location:
North America
Industry:
Banking & Finance
Vertical:
FinTech
Technologies Used
Dialogflow
Google Cloud Storage
Google Cloud Function
Google Kubernetes Engine
Business Impact
63%
Resolution rate without manual intervention
4.46
Average customer satisfaction rate
45%
Reduction in employee time spent on customer service

Problem Statement

The client is a well-established banking and financial company in the US. They own a significant market share in the industry and wanted to increase that by providing better services to their customers.
The company already had a very good digital presence and based on their yearly surveys, customers were increasingly using their digital services. This insight encouraged them further to increase their digital services while lowering the workload of its contact center employees so that they can focus more on increasing their sales.
They reached out to us for developing an AI solution that could handle most of the customer queries on their website while providing the best customer experience to users.
Objectives
  • Develop a digital AI solution for answering customer queries on the website
  • Ensure delightful customer experience in using the solution
  • Reduce manual contact requests by covering all basic customer queries

Smart AI Customer Assistant

Solution
Attri developed a conversational AI assistant that could help customers tackle all basic queries asked by customers. We used Natural Language Processing and trained the assistant with multiple questions that were most frequently asked by the customers.
The model is also trained to identify patterns in the way questions are asked and suggests further questions that could be answered. This feature ensures that the customer has an engaging experience while using the assistant.
Upon asking any complex question, the assistant directs the question to the contact center which is later picked up by a customer support executive. The AI assistant closes the conversation with a customer by asking to rate their experience on a scale of 1 to 5.
The assistant sends detailed reports on a daily basis signifying the number of requests handled, the daily average customer satisfaction rate (taken from the ratings given by the customers), and the number of manual interventions called.
  • More than 1,000 requests handled on a daily basis
  • A 63% resolution rate by the assistant itself, eliminating any manual intervention
  • 45% reduction in employee time spent on customer service
  • An average customer satisfaction rate of 4.46 for a period of 2 months

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