The Role of Product Managers in Conversational AI Workflows
Product Manager Brian Smith discusses the role of product managers in Conversational AI workflows, emphasizing automation, challenging traditional mindsets, and improving user experience.
00:00:00 Product Manager Brian Smith discusses the role of product managers in Conversational AI workflows. He highlights the various teams involved and the challenges of integrating conversational AI into different business units.
💡 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.
00:07:09 This video discusses the role of product managers in Conversational AI workflows, emphasizing ease of use through automation, challenging traditional mindsets, and envisioning future states. It also explores the importance of horizon worksheets.
🔑 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.
00:14:20 The video discusses how product managers play a role in conversational AI workflows, emphasizing the importance of defining the capabilities and limitations of bots. It also explores the idea of rethinking conversational AI and improving the user experience through personalized interactions.
⭐️ 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.
00:21:29 This video discusses how to incorporate a human aspect into conversational AI workflows. It explores the importance of designing open-ended prompts and personalizing responses based on customer input.
🗒️ 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.
00:28:39 Product managers collaborate with designers and developers to improve conversational AI workflows, integrating visuals and data presentation to enhance user experience and create reusable templates.
🤝 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.
00:35:45 The video discusses the role of product managers in conversational AI workflows and the metrics used to define success and measure user engagement. It also explores the qualities of a good team working on chat bot projects and strategies for infusing personality into conversation design.
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.
00:42:54 Product managers play a crucial role in conversational AI workflows, especially in optimizing the user experience and scaling the system. Insights from data scientists help prioritize improvements. Start prototyping transactional bots early to understand technology limitations and user needs.
📋 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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