💡 Brian Smith has been working in the conversational AI space for four years and is currently a senior product manager at Intuit.
👥 Product managers in conversational AI work with various teams, including business units, product teams, experience owners, and conversation designers.
🌍 One of the main considerations for product managers is ensuring that conversational AI experiences are globally ready, taking into account localization and different market requirements.
🔑 Product managers play a crucial role in the development of conversational AI workflows, from local proof of concept to global scalability.
💡 Automation is important in ensuring ease of use for content designers and conversation designers, allowing them to focus on writing content while personalizing the user experience.
🚀 Challenging traditional form-based experiences and thinking outside of the box is essential for driving innovation in conversational AI.
⭐️ Identifying what the bot can and cannot do is crucial for effective design and refinement.
🔍 Different bots can serve different levels of complexity and must align with the specific goals of the customer journey.
💡 Using clickstream data to personalize the bot experience and incorporate visual elements can enhance usability and engagement.
🗒️ Brands that incorporate a human aspect into conversational AI designs can build trust and loyalty with customers.
💻 Shifting from traditional bot design to open-ended prompts allows for more natural and meaningful customer interactions.
👥 Real-time collaboration between product managers, designers, and other stakeholders enhances the development and refinement of conversational AI workflows.
🤝 Collaboration between product managers, designers, and developers to identify use cases and improve the user experience.
👥 Creating reusable flows and templates to streamline the development process and make it easier for designers to implement.
🖊️ Streamlining the approval process by sharing flows and prototypes with legal and stakeholder teams for feedback and sign-offs.
Product managers play a crucial role in the workflow of conversational AI.
Success for a bot experience is defined by adoption, engagement, interaction, and containment.
Building a good team for conversational chat bots involves learning, scaling, and optimizing the experience.
Infusing personality into conversation design requires collaboration with marketing and maintaining a consistent tone and voice.
Metrics for conversational AI include containment, task completion, and seamless flow across different experiences.
📋 The approach to task completion in conversational AI involves attribution models, similar to marketing campaigns.
💡 Data scientists play a crucial role in monitoring and optimizing the conversational AI experience.
🔄 Scaling conversational AI involves integrating back-end systems, API calls, and data, as well as continually optimizing the conversation.
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