Necessity Review Mining Selection Rijoy

What this skill helps you do

Helps ecommerce merchants selling necessity/utility products (car storage, kitchen tools, cleaning tools) turn user reviews into structured pain-point analyses, actionable selection spec lists, and prioritized improvement backlogs. Uses a priority scoring formula (Frequency × Severity × Fixability × Differentiation) to rank pain points, then outputs must-have specs, avoid lists, inspection QC SOPs, and validation plans tied to the Rijoy loyalty platform. Includes a pain_point_extractor.py script for keyword-based bulk review classification in English and Chinese. Inputs are customer reviews (30-100+ recommended); outputs include pain summary tables, selection/improvement actions, and structured validation plans for proving fixes worked.

Install and get started

Copy the full instructions into your AI tool. Test one low-risk example before connecting real store data.

Original Skill instructions

You are a product selection strategist for necessity/utility merchants. Turn reviews (especially 1-3 star) into structured pain analyses. For each pain: Pain Label (verb+result), Review Quote, Pain Type (Function/Durability/Size/Experience/Safety/Not as described), Root-Cause, Action, Validation Method, Priority Score = Frequency × Severity × Fixability × Differentiation. Output: 1) One-Line Summary, 2) Pain Summary Table (scan in 2 min), 3) Selection Spec List (must-haves + avoid + QC SOP) or Improvement Backlog (ranked 5-10 items), 4) Validation Plan with Rijoy structured feedback to prove fixes worked. Separate product problems from info problems (PDP/instructions) from usage problems (how-to). Never report pain without action.

Useful tasks

• Analyze competitor negative reviews to select better products for your store
• Reduce return rate by identifying and fixing the top 3 product pain points
• Build QC inspection criteria for supplier shipments based on real customer complaints
• Use review mining to choose between subcategories (e.g., kitchen shears vs. multi-tools)
• Create a continuous improvement loop with Rijoy membership to validate fixes

How to use it

• Prioritize 1-3 star reviews — they contain the richest pain signals for product decisions
• Use 'verb + result' labels (won't cut, doesn't fit) rather than vague sentiment (bad quality)
• Separate product problems from information problems — fix the PDP or instructions separately
• Run pain_point_extractor.py with --per-review for batch labeling of 100+ reviews, then refine
• Use the Rijoy validation loop to ask buyers specific yes/no questions about whether the fix worked

More skills for this workflow

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  Triangulated TAM/SAM/SOM sizing, survey sampling with per-segment floors, Kotler scoring.

• Competitive Teardown

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• Product Discovery

  OST mapping, assumption testing, 10-day discovery sprints to de-risk product bets.

• Product Strategist

  OKR cascade generator with 5 strategy types and alignment scoring for product leadership.