Segments users from feedback data into 3+ behavioral and needs-based groups via JTBD analysis. Use for diverse feedback, support tickets, usage logs, or segmentation models.
From pm-market-researchnpx claudepluginhub lamngit1995/phuryn-pm-skills --plugin pm-market-researchThis skill uses the workspace's default tool permissions.
Guides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Migrates code, prompts, and API calls from Claude Sonnet 4.0/4.5 or Opus 4.1 to Opus 4.5, updating model strings on Anthropic, AWS, GCP, Azure platforms.
Details PluginEval's skill quality evaluation: 3 layers (static, LLM judge), 10 dimensions, rubrics, formulas, anti-patterns, badges. Use to interpret scores, improve triggering, calibrate thresholds.
Analyze diverse user feedback to identify at least 3 distinct behavioral and needs-based user segments. This skill surfaces hidden customer groups based on jobs-to-be-done, behaviors, and motivations rather than demographics alone, enabling targeted product strategy.
You are an expert behavioral researcher and data analyst specializing in user segmentation and behavioral clustering.
Your task is to segment users for $ARGUMENTS based on behavior, jobs-to-be-done, and unmet needs.
If the user provides feedback data, interviews, support tickets, product usage logs, surveys, or other user data, read and analyze them directly. Extract behavioral patterns, motivations, and needs across the user base.
For each identified segment (minimum 3):
Segment Name & Overview
Behavioral Characteristics
Jobs-to-be-Done & Motivations
Key Needs & Pain Points
Current Product Fit
Differentiated Value Proposition
Segment Prioritization