What Happens After Go-Live: The Importance of Fine-Tuning Your AI Virtual Agent
Whether your company is starting to think about contact center automation, or you’ve just invested in a conversational AI solution, there’s one question you may not have asked – what happens after you deploy the intelligent virtual agent?
The cold, hard truth of conversational AI is that it’s not a ‘set it and forget it’ type of technology; it needs constant fine-tuning to ensure the AI virtual agent performs on par or better than live agents.
Join us for this informative webinar as we discuss life after go-live – because that’s where the real work begins. From monitoring how your customers engage the virtual agent to tailoring the natural language understanding (NLU) engine, you’ll learn best practices for improving virtual agent performance and delivering the most seamless self-service experience possible.
Key Takeaways:
- The maintenance and continuous optimization required after deployment
- What happens if you don’t continuously train your AI virtual agent
- How to make the transition – for your customers and internally – to AI self-service as smooth as possible
Watch This
Webinar
Brian Morin
Chief Marketing Officer,
SmartAction
Helena Chen
Director of Product Marketing,
SmartAction
What Happens After Go-Live: The Importance of Fine-Tuning Your AI Virtual Agent
On-Demand Webinar
Whether your company is starting to think about contact center automation, or you’ve just invested in a conversational AI solution, there’s one question you may not have asked – what happens after you deploy the intelligent virtual agent?
The cold, hard truth of conversational AI is that it’s not a ‘set it and forget it’ type of technology; it needs constant fine-tuning to ensure the AI virtual agent performs on par or better than live agents.
Join us for this informative webinar as we discuss life after go-live – because that’s where the real work begins. From monitoring how your customers engage the virtual agent to tailoring the natural language understanding (NLU) engine, you’ll learn best practices for improving virtual agent performance and delivering the most seamless self-service experience possible.
Key Takeaways:
- The maintenance and continuous optimization required after deployment
- What happens if you don’t continuously train your AI virtual agent
- How to make the transition – for your customers and internally – to AI self-service as smooth as possible
