The Role of Product Managers in Conversational AI Workflows

💡 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.