Claude-skill-registry gamification-marketing

Design gamified marketing campaigns using points, badges, leaderboards, streaks, challenges. Use for loyalty programs, referral campaigns, onboarding flows, engagement boosts, email gamification. Provides mechanics selection, psychology alignment, strategy docs, templates, KPIs.

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/gamification-marketing" ~/.claude/skills/majiayu000-claude-skill-registry-gamification-marketing && rm -rf "$T"

manifest: skills/data/gamification-marketing/SKILL.md

source content

Gamification Marketing

Design and implement gamified marketing campaigns using behavioral psychology and game mechanics.

Quick Decision Tree

GOAL → MECHANICS
├─ Acquisition → Referral leaderboards + dual rewards + social proof
├─ Retention → Streaks + tiers + loyalty points + loss aversion
├─ Engagement → Challenges + leaderboards + badges + daily quests
├─ Conversion → Variable rewards + time-limited offers + progress bars
└─ Onboarding → Progress bars + micro-badges + unlockables

Core Mechanics (10)

Mechanic	Best For	Psychology
Points	All goals	Achievement, progress tracking
Badges	Recognition, milestones	Competence, social proof
Leaderboards	Competition, engagement	Social comparison, status
Levels	Progression, retention	Mastery, unlocking content
Streaks	Habit formation, retention	Loss aversion, commitment
Challenges	Engagement, conversion	Goal-setting, achievement
Quests	Extended engagement	Narrative, exploration
Unlockables	Retention, progression	Curiosity, exclusivity
Rewards	All goals	Dopamine, variable schedules
Progress Bars	Onboarding, completion	Visual momentum, Zeigarnik

Workflow

Identify Goal → Use decision tree above
Select Mechanics → See mechanics-selection.md
Align Psychology → See psychology-frameworks.md
Design Campaign → See campaign-templates.md
Implement → See implementation-guide.md
Measure → See kpi-tracking.md

Key Stats

Streaks: 3.6x retention at 7-day milestone (Duolingo)
Progress bars: 40% completion lift
Leaderboards: 40% engagement increase
Variable rewards: Higher dopamine than fixed
ROI: $4.90 return per $1 invested

White Hat vs Black Hat

White Hat (70% - long-term): Levels, badges, achievement, community, creative expression Black Hat (30% - urgency): Scarcity, time limits, loss aversion, FOMO, variable rewards

Player Types (Bartle)

Achievers (10%): Leaderboards, points, visible progress
Explorers (10%): Hidden badges, easter eggs, discovery
Socializers (80%): Team challenges, sharing, community
Killers (5-10%): PvP, competitive rankings

References

mechanics-selection.md - Mechanics guide, selection matrix
psychology-frameworks.md - Octalysis, SDT, Fogg model
campaign-templates.md - Email templates, calendar
challenge-configs.md - JSON configs, rules engine
implementation-guide.md - Architecture, API, caching
database-schema.md - PostgreSQL schemas
kpi-tracking.md - Metrics, alerts, reporting
analytics-events.md - Event schemas, tracking
case-studies.md - Duolingo, Starbucks, Nike

Report Output

Activate:

assets-organizing

skill for report file paths

Gamification reports go to

assets/reports/performance/{date}-gamification-analysis.md

Common Pitfalls

Issue	Fix
Too many mechanics	Pick 2-3 core; phased rollout
Unclear reward value	Show math: "100 pts = $5"
Leaderboard toxicity	Friendly framing, hide ranks below top 10
Impossible challenges	Start easy, progressive difficulty
No personalization	Segment by player type