Today, we are presenting an idea which can help in routing the Chat/Voice interaction in the contact center to the right skilled agent. As we all know Contact center plays a bigger role in any organization when providing the best customer service to the users. Ideally, in any digital interaction in a contact center ecosystem, like voice, chat or email involves a virtual agent which is the first layer to interact with the customer. VA tries to welcome the user and understand the Intent. Based on the intent, query the VA tried to have the conversation. If the Intent is complex we might need human assistant to look upon, we have a routing strategies traditionally build. Based on the parameters collected by virtual agent, routing strategy executes and determines a skilled agent but might not be appropriate everytime. So today, we thought this can be resolved by AI or provide AI prediction as an additional parameter in determining the right Queue and right agent. In this demo, We have defined 5 Queue and given a Name as shown here. Q1_GB_CHAT: Agents belonging to this queue, can help with general banking queries like account information, online bank, branch address, contact number only. And this agent can speak english, spanish. Q1_GB_CHAT_ESP: Agents belonging to this queue, can help with general banking queries like account information, And this agent can speak only spanish. Q2_HL_CHAT_ENG: Agents belonging to this queue can help with mortgage loans, home loans, home loan eligibility. The agent belonging to this queue can only speak english. Q3_CC_CHAT: Agent belonging to this queue can help anything related to credit card. Q4_FR_CHAT: Agent belonging to this queue helps with fraudulent activity on credit card. So we have given simple description or defining this Queue. We have created a Prompt template, with this description & chat summary injected dynamically into Prompt template. This prompt is sent to Text-bison model, which responds with the Queue ID.Category tags:
"Awesome documentation of components and functionality. Overall great work!"
PhD Computer Science Student
"great work, keep it going"
Walaa Nasr Elghitany
Data scientist and doctor