The third largest city in California, San José is the most linguistically diverse city in the United States. As the “capital of Silicon Valley”, it serves as a hub of technology and innovation for the region. The City of San José Information Technology Department (ITD) aims to provide meaningful impact through smart uses of technology in service of employees and the community, including managing the Customer Contact Center.
The City of San José was on a multi-year journey to deliver a cohesive 311 experience via its portal and app. However, long wait times and high call volumes continued to plague the city’s call center – citizens would call to schedule junk pickups, report abandoned vehicles and report missed pick ups, but often ended up abandoning their request when it was not handled in a timely manner. Plus, out of the box translation services were not robust enough to accommodate the needs of its diverse population.
SpringML and Google Cloud worked with the City of San José to implement Contact Center AI (CCAI) solutions to increase call handling speed, capacity and customer satisfaction — without adding headcount in the City Customer Contact Center. We built a machine learning model to create a custom trained translation model that facilitates adding more languages and access to services. Virtual agents were implemented to support both English and Spanish, and we were able to integrate with the city’s existing systems for a seamless user experience.
We focused on creating self serve requests across four main areas:
- Schedule Junk Pickups
- Report abandoned vehicles
- Order replacement bins
- Report missed pickups
Citizens can now easily create real-time requests via an online virtual agent or telephone at any time of day, freeing up live agents to handle more complex requests.
“The new Virtual Agent provides an efficient way to help our residents get the critical City services they need while reducing the burden on our call center. Furthermore, the Virtual Agent’s machine learning language translation features improve equity for residents who are not fluent in English.”