Craft human-like experiences with conversational design

Brillio’s GenAI-powered customer experience is based on a conversational design modeled on human conversations to drive contextually relevant interactions with customers.

Building effective conversational AI for a robust customer experience is a complex endeavor that requires careful consideration of various strategic and technical challenges. While conversational applications may appear simple, developing AI that delivers meaningful, user-centered experiences is among today’s most demanding AI objectives. Key challenges begin with identifying the proper use case for a conversational interface and designing a natural language understanding model that reliably interprets user intent with high containment rates. Achieving the desired customer satisfaction depends on crafting responses that encourage adoption and engagement while continuously expanding the AI’s knowledge base. Measuring performance and gauging customer usage post-deployment becomes essential to refining the bot’s utility. Furthermore, implementing a framework for continuous improvement and scaling across additional use cases ensures conversational interfaces remain relevant and efficient, evolving to meet dynamic customer needs.

Brillio’s conversational design methodology

Brillio approaches conversational design with a deep understanding of human interaction as the foundation for digital communication. This methodology leverages natural dialogue principles to build systems that create a truly engaging, human-like user experience.

Conversational design goals

• Engage: Respond only where it adds value without interrupting.
• Recall: Maintain contextual awareness, avoiding repetitive questions.
• Anticipate: Predict user needs to enable proactive, insightful responses.
• Adapt: Adjust dynamically to shifts in sentiment, context, and user needs.
• Reflect: Reiterate key information to confirm understanding and satisfaction.
• Pull: Use subtle cues to guide the conversation forward smoothly.

Design process

• Set up foundational elements, including greetings, error handling, fallbacks, and small talk.
• Develop a ‘blue-sky’ script for each intent to envision ideal conversational outcomes.
• Define entities, slots, synonyms, and disambiguation as intended to ensure clarity.
• Apply extensive training and test data for each intent to enhance AI understanding.
• Continuously test and refine dialogue flows to perfect user interactions.

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