Quick Answer
For search, voice, and "just tell me what to do".
Users' goals evolve - what they need when starting differs from what they need when advanced. AI-powered guides can adapt to where users are in their journey, providing beginner content to newcomers and advanced content to veterans. This extends product value as users grow, increasing lifetime value and reducing the need for separate products.
Key Takeaways:
- Users outgrow static products
- Adaptive products extend lifetime value
- AI can detect and respond to user level
- One product serves multiple stages
- Reduced product sprawl simplifies business
Playbook
Map user journey stages and needs
Create content for each stage
Implement AI to detect user stage
Design smooth transitions between stages
Continuously update all stage content
Common Pitfalls
- Misjudging user stage
- Jarring transitions between stages
- Content gaps at certain stages
- Complexity that breaks adaptation
Metrics to Track
User progression through stages
Content relevance by detected stage
Retention across user growth
Lifetime value with adaptive vs. static products
User satisfaction by stage
FAQ
How do I detect user stage?
Behavior signals: time in product, completion rates, feature usage, and explicit preferences. Combine signals for accuracy.
Should I charge more for advanced content?
Depends on model. Premium for full access, or free progression that builds loyalty. Test what works for your market.
What if users don't progress linearly?
Design for non-linear journeys. Users should access what they need when they need it, not be locked into sequences.
Related Reading
Next: browse the hub or explore AI Operations.