Challenges 

The customer, a public transport company, wanted to determine the dialog flow of its AI chatbot to help patrons with smart card self-service. This project’s prerequisite was to extend the reach of their customer service offerings while providing the company with an opportunity to streamline and reduce their customer service representatives’ headcount and ultimately reduce costs.  

Also, they wanted to modify the API library to support transactions initially built for an antiquated IVR system.   

They were challenged with the dense technology and development calendar, which needed incredible coordination with teams and SMEs across the US and European countries.  

Solutions 

Neal Analytics created a transaction bot to support transit patrons with the ability to check the balance of their smartcard, add to their stored balance, and purchase a pass all through SMS. Our solution leverages Natural Language Processing (NLP) to help the chatbot interpret customer intents and offer a proper response in the context of a transaction. Along with this, we used Application Insights to capture telemetry and Power BI to display data visualizations.  

The Neal Analytics team added functionality to report a lost or stolen card, transfer balance, and issue a replacement through the chatbot. We also provided the ability for the bot to assist patrons in self-diagnosing any account access issues, which helped reduce the workload for the customer service representatives so that they could focus on high-value tasks. 

Finally, we created a secondary bot to help customers plan their trips when using a variety of transportation methods such as walking, biking, and riding the bus.   

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Results 

The chatbot leveraging Neal’s solution now supports over 8 million people. The automated chatbot helped reduce strain on customer service representatives. In addition, the public transport company can now also make transaction estimates based on the rider trends.