# User Psychology > Master user psychology domain - understand decision-making, cognitive biases, behavioral patterns, motivation, adoption barriers. Use for designing features users will love, reducing friction, and predicting user behavior. - **Type:** Skill - **Install:** `agentstack add skill-gianggiangtran-ba-skills-user-psychology` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [GiangGiangTran](https://agentstack.voostack.com/s/gianggiangtran) - **Installs:** 0 - **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [GiangGiangTran](https://github.com/GiangGiangTran) - **Source:** https://github.com/GiangGiangTran/ba-skills/tree/main/skills/user-psychology ## Install ```sh agentstack add skill-gianggiangtran-ba-skills-user-psychology ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # User Psychology for BA People are not rational. Design for how they actually behave. ## What is User Psychology? **Definition**: Understanding how people make decisions, what motivates them, what biases influence them, and what causes friction - the human factors in product adoption and use. **Why it matters**: - Features nobody uses: Built without understanding motivation - High friction adoption: UX doesn't match how people think - Resistance to change: Didn't anticipate psychological barriers - Poor engagement: Doesn't align with user incentives **When to Use**: - ✅ Understanding why users do (or don't do) something - ✅ Designing engagement and motivation - ✅ Reducing adoption friction - ✅ Managing change resistance - ✅ Predicting user behavior --- ## 5 Core Psychology Concepts ### **1. Cognitive Biases: Why People Make Decisions They Do** People are predictably irrational. ``` CONFIRMATION BIAS: People seek evidence supporting their existing belief Impact: Users ignore warnings, skip steps they think unnecessary Fix: Make required steps impossible to skip, not just recommended LOSS AVERSION: People fear losing what they have 2x more than gaining equivalent Impact: Users resistant to change even if beneficial Fix: Frame as "keep what's good, improve problem areas" STATUS QUO BIAS: People prefer things to stay the same Impact: Users reluctant to adopt new features/products Fix: Make switching easy (migration tools, training) ANCHORING: First number heard becomes reference point Impact: First price offered anchors negotiation Fix: Present realistic prices first SUNK COST FALLACY: People continue because they invested so much Impact: Users reluctant to switch even to better solution Fix: Reduce switching costs CHOICE OVERLOAD: Too many options paralyzes decision-making Impact: Feature-rich UI prevents users from choosing anything Fix: 3-5 options max, clear recommendations ``` **See**: `references/cognitive-biases.md` --- ### **2. Motivation: What Drives Behavior** People are motivated by different things. ``` INTRINSIC MOTIVATION (Internal rewards): - Autonomy (control over choices) - Mastery (getting better at something) - Purpose (contributing to something meaningful) → Creates sustainable engagement EXTRINSIC MOTIVATION (External rewards): - Money, status, badges, recognition → Works short-term, fades over time BEHAVIORAL DESIGN FRAMEWORK: Action = Motivation + Ability + Trigger Example: User completes task - Motivation: Feels sense of progress (mastery) - Ability: Task is easy enough to complete (design) - Trigger: Notification reminds them (notification) All three required for behavior to happen. If missing one, behavior doesn't happen. ``` --- ### **3. The Adoption Curve: Who Are Your Users?** People adopt at different rates. ``` ADOPTION DISTRIBUTION: Innovators (2.5%): - Love new technology - Don't need convincing - Will use for no reason - Get them involved early Early Adopters (13.5%): - Will try new thing if it solves problem - Influential opinion leaders - Can drive adoption - Build with their feedback Early Majority (34%): - Will adopt if proven to work - Need evidence of value - Need training/support - Represent majority of growth Late Majority (34%): - Will adopt when necessary - More skeptical, need clear ROI - Require strong support - Network effects matter (everyone has it) Laggards (16%): - Adopt only when forced - Deeply resistant - Need extensive training - Often never fully adopt ``` **BA Implication**: Different segments need different strategies. --- ### **4. Friction Points: Why People Abandon Products** Users abandon when friction exceeds value. ``` Friction Equation: Decision = Value - Friction - Risk High Value + Low Friction + Low Risk = ✓ Users adopt Example - Sign up for service: Value: Saves 5 hours/week (High) Friction: 15-minute setup (Low) Risk: $100/month, can cancel anytime (Low) → Likely to adopt Example - Switch email provider: Value: Slightly better UI (Low) Friction: Export/import data (Medium) Risk: Lose existing contacts (High) → Unlikely to adopt despite better product ``` **Common Friction Points**: - Data entry (long forms reduce completion 25% per field) - Learning curve (confusing UI stops users) - Setup complexity (multiple setup steps, 80% abandon after step 3) - Password/authentication (friction increases if password reset required) - Integration with existing workflows (requires behavior change) --- ### **5. Behavioral Triggers: How to Prompt Action** People need prompts to take action. ``` TRIGGER TYPES: Spark (Motivation): - "Get 2x more done with automation" - Creates desire Action (Ability): - "Click here to start" (easy next step) - Remove friction Signal (Trigger): - Notification, email, button - Prompts remembering COMPLETE LOOP: 1. Spark: Show value 2. Action: Make it easy 3. Signal: Send notification 4. Reward: Positive outcome → Habit forms Example - Fitness App: Spark: "You can beat your friend's step count" (motivation) Action: One-click challenge (easy) Signal: "Friend challenged you!" (trigger) Reward: See your score vs theirs (positive) → User forms habit of checking daily ``` --- ## User Segments: Different Psychology, Different Design ### **Enterprise Users** ``` Motivation: ROI, avoiding risk, doing job well Biases: Loss aversion (resist change), status quo bias Friction: Complex setup OK if justified Triggers: Admin requirement, team nudging, metrics showing value Design: Show business impact, risk mitigation, training ``` ### **Consumer Users** ``` Motivation: Convenience, delight, entertainment Biases: Confirmation bias (only see what confirms choice) Friction: Very low tolerance, quit immediately if confusing Triggers: Social proof, FOMO, gamification Design: Delightful, frictionless, shows progress ``` ### **Power Users** ``` Motivation: Mastery, control, advanced features Biases: Sunk cost (invested time/learning), anchoring Friction: Will tolerate complexity if more powerful Triggers: New features, competitive leaderboards, mastery challenges Design: Advanced features, customization, performance ``` --- ## Adoption Barriers & Solutions ``` BARRIER: "I don't understand the value" Psychology: Feature complexity > perceived benefit Solution: Show value clearly before asking to try Simplify feature, or build tutorial BARRIER: "It's too hard to use" Psychology: Learning curve, cognitive load Solution: Reduce steps, add guidance, build onboarding Make first success easy BARRIER: "I don't have time to learn" Psychology: Time scarcity, habit inertia Solution: Minimal learning curve, fits existing workflow Show time savings upfront BARRIER: "I don't trust it" Psychology: Risk aversion, unknown unknowns Solution: Show social proof, build gradually Start with small stakes, low risk Transparency about how it works BARRIER: "It disrupts my workflow" Psychology: Change aversion, loss of control Solution: Minimize workflow change Let them control pace of adoption Support old way while transitioning ``` --- ## Tools & Templates - 📋 **User Persona Template**: `assets/user-persona-template.md` - 📋 **Jobs-to-be-Done Template**: `assets/jtbd-template.md` - 📋 **Adoption Barrier Assessment**: `assets/adoption-barrier-template.md` - 📋 **Behavioral Design Canvas**: `assets/behavioral-design-canvas.md` - 📋 **Friction Analysis Worksheet**: `assets/friction-analysis-template.md` --- ## Usage Examples ``` /user-psychology "Why are users abandoning at step 3 of onboarding?" /user-psychology "How do we design for late majority adopters?" /user-psychology "What's preventing users from using Feature X?" ``` --- ## BA Standards & References Based on: - **Behavioral Economics**: Irrational decision-making patterns - **Cognitive Psychology**: How people think, process information - **Change Management**: Overcoming adoption resistance - **UX Psychology**: Designing for human behavior - **Habit Formation**: Building sustainable behaviors **Detailed Frameworks**: - 📚 `references/cognitive-biases.md` - 20+ biases and design implications - 📚 `references/motivation-framework.md` - Intrinsic vs extrinsic, designing for sustainable engagement - 📚 `references/adoption-barriers.md` - Common barriers and solutions - 📚 `references/behavioral-triggers.md` - Prompting action and habit formation - 📚 `references/user-segments.md` - Different psychology by user type ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [GiangGiangTran](https://github.com/GiangGiangTran) - **Source:** [GiangGiangTran/ba-skills](https://github.com/GiangGiangTran/ba-skills) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-gianggiangtran-ba-skills-user-psychology - Seller: https://agentstack.voostack.com/s/gianggiangtran - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.