Conversational AI & Generative AI: Next-gen Agent Assist for Customer Support

Conversational AI & Generative AI: Next-gen Agent Assist for Customer Support

In the rapidly evolving landscape of customer service, the necessity for real-time, efficient support is more crucial than ever. An innovative solution in this domain is integrating AI-powered bots to provide human agents with actionable insights and dynamic support. The following article exemplifies how Conversational AI, spurred by Generative AI, can revolutionize the agent assist experience, using a demo featuring a customer named Sebastian.

The Scenario

A demo visualizes Sebastian calling airline support with a last-minute question regarding his booking. We witness how the Agent Assist experience, powered by sophisticated AI, smoothly transitions through the interaction. Here are the key steps captured:

The Conversation

Agent Introduction:

Good afternoon Mr. Glock, this is Nick from Airline Support. I understand you have a question about your flight to London, is that correct?

Customer Inquiry:

Um, yes. We're in the car on our way to the airport, bringing our cat, and I was wondering if the cat counts as carry-on baggage.

Agent Response:

Okay, let me have a look. 

... Yes, pets in cabins count as one carry-on item. You don't need to check them in. They do require a valid passport. Did you upload a copy of the pet's passport because you're flying to the UK?

Customer Realization:

Ah, no. I knew I forgot something.

Agent Solution:

No problem. Let me send you a text message with a link to the travel portal. You can simply upload the documents there. Sending it now.

Customer Confirmation:

Yeah, I got it.

Agent Wrap-Up:

Great. Do you have any other questions for me today, Mr. Glock?

... No? All good. 

Okay then, I wish you a very pleasant flight given the circumstances. Take care.

Key Highlights

1. Informed Agent Start:
   The agent initiates the call with detailed contextual knowledge. The Genesis Cloud workspace displays various widgets including previous contact experiences, flight status, customer profile, and sentiment analysis based on past interactions.

2. AI-Driven Insights:
   The bot feeds relevant information to the agent, utilizing Conversational AI to transcribe the customer's input and extract pertinent answers from a knowledge base using Generative AI.

3. Efficiency Tools:
   The agent can send an SMS with a link to a travel portal effortlessly, allowing the customer to upload necessary documents. Additionally, the bot drafts a Salesforce case, which the agent only needs to review and approve, significantly reducing callback requirements.

Keywords

• Conversational AI
• Generative AI
• Agent Assist
• Customer Support
• Real-time Support
• Genesis Cloud
• Customer Sentiment
• Knowledge Base
• Case Management
• Salesforce Integration

FAQ

Q: What is the role of Conversational AI in customer support?
A: Conversational AI helps transcribe customer input and provides real-time, relevant information to human agents, enhancing the overall support experience.

Q: How does Generative AI assist in this scenario?
A: Generative AI extracts essential data from a knowledge base to provide accurate answers, streamlining the support process.

Q: What advantages do AI-powered tools offer to customer support agents?
A: These tools supply contextual insights, automate routine tasks like document uploads, and draft case summaries, thus reducing the workload on human agents.

Q: How does sentiment analysis benefit customer support?
A: Sentiment analysis helps agents understand the customer's emotional state, allowing for more empathetic and effective interactions.

Q: What are the key functionalities demonstrated in the Genesis Cloud workspace?
A: The Genesis Cloud workspace shows previous customer interactions, flight status, customer profile, and real-time sentiment analysis, all facilitating a well-informed agent start.

Q: How does the bot aid in case management?
A: The bot drafts case summaries and automates submissions to Salesforce, requiring minimal input from the agent, thus enhancing operational efficiency.