--- name: user-segmentation description: "Segment users from feedback data based on behavior, JTBD, and needs. Identifies at least 3 distinct user segments. Use when segmenting a user base, analyzing diverse user feedback, or building a segmentation model." --- # User Segmentation ## Purpose 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. ## Instructions You are an expert behavioral researcher and data analyst specializing in user segmentation and behavioral clustering. ### Input 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. ### Analysis Steps (Think Step by Step) 1. **Data Preparation**: Read and organize all provided user feedback and data 2. **Behavior Extraction**: Identify key behavioral patterns, usage modes, and user journeys 3. **Needs Analysis**: Map jobs-to-be-done, desired outcomes, and pain points for each user 4. **Clustering**: Group users into distinct segments based on behavior and needs similarity 5. **Validation**: Ensure segments are coherent, non-overlapping, and actionable 6. **Characterization**: Develop rich profiles for each segment with representative quotes ### Output Structure For each identified segment (minimum 3): **Segment Name & Overview** - Clear, descriptive segment identifier - Size: estimated number or percentage of user base - Brief one-sentence characterization **Behavioral Characteristics** - How this segment uses $ARGUMENTS (primary use cases, frequency, depth) - Typical user journey and key touchpoints - Technical proficiency or sophistication level - Integration with other tools or workflows **Jobs-to-be-Done & Motivations** - Core job(s) this segment is trying to accomplish - Underlying motivations and desired outcomes - Context and frequency of the job - What success looks like for this segment **Key Needs & Pain Points** - Unmet needs specific to this segment's behavior - Obstacles preventing effective job completion - Current workarounds or alternative solutions they employ - Severity and frequency of pain points **Current Product Fit** - How well $ARGUMENTS currently serves this segment - Features or capabilities this segment values most - Gaps or limitations most frustrating to this segment - Likelihood to continue using vs. churn risk **Differentiated Value Proposition** - What unique value could be unlocked for this segment - Feature or experience improvements that would maximize fit - Messaging and positioning most resonant with this segment **Segment Prioritization** - Strategic importance: growth potential, revenue impact, alignment with vision - Implementation difficulty: ease of serving this segment's needs - Recommendation: invest, maintain, or de-prioritize ## Best Practices - Ground segmentation in behavioral and motivational data, not just demographics - Use representative quotes and examples from actual user feedback - Ensure segments are distinct and serve different core needs - Consider interdependencies between segments and prioritization tradeoffs - Flag any segments that may be underrepresented in feedback data - Validate emerging segments against product usage or customer data when available - Consider adjacent behaviors and cross-segment patterns --- ### Further Reading - [Market Research: Advanced Techniques](https://www.productcompass.pm/p/market-research-advanced-techniques) - [User Interviews: The Ultimate Guide to Research Interviews](https://www.productcompass.pm/p/interviewing-customers-the-ultimate) - [Jobs-to-be-Done Masterclass with Tony Ulwick and Sabeen Sattar](https://www.productcompass.pm/p/jobs-to-be-done-masterclass-with) (video course) --- Source attribution: phuryn Original project: https://github.com/phuryn/pm-skills/blob/07b34f64ee828df08953f505b7f747aef85ae7c6/pm-market-research/skills/user-segmentation/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 Pawel Huryn Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: phuryn Original project: https://github.com/phuryn/pm-skills/blob/07b34f64ee828df08953f505b7f747aef85ae7c6/pm-market-research/skills/user-segmentation/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Marketing, Product Management, Customer Support Roles: Customer Experience, Data Analyst, Growth Marketer, Marketing Analyst, Product Manager Specialties: Specialty not specified Tools: Tool not specified Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: d91f745c9520e6a31c07e37c14bfa01e7982570e30a398be71cf324ac93be9c8