In order for product teams to be able to build roadmaps that guide a product over the course of several quarters, they need to be constantly and consistently collecting data. But most teams are very start/stop when it comes to discovery practices. Luckily, Discovery has evolved beyond traditional research methods. AI tools can now accelerate synthesis, identify patterns across customer conversations, and easily allow teams to build and search data banks. But without strong foundational research and innovation skills, AI can’t help much.
This workshop is for teams who are looking to improve their customer experiences, find innovation opportunities, and develop a strong value proposition for their market.
This program will cover:
Foundation theory of design thinking and AI-augmented research
Scoping frameworks for Discovery
Building and validating personas using data powered segmentation analysis
Conducting customer interviews and using AI for qualitative synthesis
Running experiments with predictive analytics
Leveraging AI for collaborative synthesis and pattern recognition
How to build roadmaps that align to org goals
Outcomes:
Understanding research best practices and the ability to avoid actions that introduce bias, including bias introduced by AI.
Product teams can craft learning goals and deploy AI tools for faster insight generation
PMs can assess when AI synthesis adds value versus when manual analysis is superior
PMs can work with design and research to quickly generate prototypes, and then deploy experiments around them
PMs are capable of framing discovery sessions and leveraging AI for post-session analysis
Product teams can gather data, use AI for initial synthesis, and apply human judgment to distill strategic insights