How the prompt works
The system prompt sets the LLM up as a product analyst and requires five specific sections in every response. Without that structure, models return a vague summary instead of something a product team can act on. The user prompt takes four variables — product name, review text, focus areas, and current priorities — so the output is always scoped to what the team is actually working on.System prompt
Sets the LLM’s role and defines the five sections it must always include in the output.User prompt
Four variables that give the model enough context to return insights scoped to the team’s current priorities.Sample output: ShopEasy Mobile App
Sample output: ShopEasy Mobile App
Customer review analysisOverall sentimentMixed sentiment — 60% negative, 40% positive. Customers appreciate product selection and deals but are frustrated with core functionality.Top 5 recurring pain points
- App crashes during checkout (High) — direct revenue loss, cart abandonment
- Confusing payment process (High) — conversion rate reduction
- Poor search functionality (Medium) — product discovery issues
- Inaccurate delivery tracking (Medium) — increased customer support load
- Cluttered interface design (Low) — general UX degradation
- Immediate: Fix checkout stability and implement crash reporting
- Short-term: Redesign payment flow with progress indicators
- Medium-term: Improve search with better filtering and AI suggestions
- Long-term: Add wishlist functionality and fix delivery tracking integration
- High: Checkout stability, payment flow redesign
- Medium: Search enhancement, delivery tracking accuracy
- Low: UI decluttering, wishlist feature
- “Love the product selection but payment process is confusing.”
- “App crashes when I try to checkout.”
- “Great deals but search function is terrible.”