As we understand more about conversational automation, we realize that not all conversations are alike. Some are unstructured and free flowing, while others are highly structured and rule-bound. And while many hoped Conversational AI and Generative AI powered Digital Assistants (chatbots) would magically handle them all, we are learning that is not the case.
The reality is that Digital Assistants are very good at answering questions and triggering actions, but they are not effective at context-rich, process-bound conversations, especially where customers need advice not just assistance. Their decision tree’d scripts can’t handle the multi-dimensional, contextual logic that these expert-level operational conversations require.
As a result, high volumes of operational conversations still need to be handled by live agents.
Virtual Agents help expand your CX capacity by automating these operational, rule-bound conversations so your live agents are freed up to focus on the lower volume, higher value relational conversations that have the greatest impact on customer satisfaction and brand loyalty.
Virtual Agent (VA) | Chatbot | |
---|---|---|
The role they perform | Digital Expert | Digital Assistant |
The technology that powers them | Conversational Process Automation | Conversational Al |
The work they can do | Clarify, Analyse, and Resolve Queries | Answer Questions |
The process logic they support | Simple to Complex | Simple |
Their resolution success | High (Low Agent Handoff) | Low (High Agent Handoff) |
How they follow processes | Multi-Dimensional Logic Objects | Coded Decision Trees |
The effort to keep them compliant | Low | High |
The experience they offer | Dynamic, Bi-Directional | Menu-Driven |
1Proof of Concept
1 Week
2Proof of Value
8 Weeks
3Multi-Year SLA
Ongoing
The cost of a Virtual Agent depends on the work it must perform. This impacts the upfront training (build) and deployment effort, and the volume of conversations it automates across channels.