Hooked UX

Hook Model Framework

Framework for building habit-forming products. Habits are not created — they are built through successive cycles through the Hook.

Core Principle

The Hook Model = a four-phase loop that connects the user's problem to your solution frequently enough to form a habit, moving usage from deliberate to automatic.

Trigger → Action → Variable Reward → Investment
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Scoring

Goal: 10/10. When reviewing or creating product engagement mechanics, score the loop by the four Quick Diagnostic rows (internal trigger, dead-simple action, variable reward, investment loads next trigger): each row earns 2 (fully satisfied), 1 (partial), or 0 (absent), then score = round(total / 8 × 10). Then apply the ethics gate: if the Manipulation Matrix places the product as Dealer (or it hits any "When NOT to Use" condition), cap the score at 3 regardless of mechanics. Bands: 9-10 = complete loop, internal trigger identified, ethics clear; 5-6 = loop runs but leans on external triggers or predictable rewards; <=3 = broken loop or extractive design. Always state the current score and the specific diagnostic rows blocking 10/10.

The Four Phases

1. Trigger

Core concept: The actuator of behavior. Triggers are external (environment-driven: notifications, emails, ads) or internal (emotion-driven) — and the goal is to migrate users from external to internal triggers.

Why it works: Every habit starts with a cue. External triggers get users started, but internal triggers — boredom, loneliness, uncertainty, FOMO — drive unprompted usage because the emotion itself fires before any reminder can.

Key insights:

• Map your product to the specific negative emotion it resolves (boredom, loneliness, confusion, FOMO)
• Effective external triggers are well-timed, actionable, and lead to the simplest possible next action
• If users still need external prompts after ~30 days, no internal trigger has formed

Product applications:

Copy patterns:

• "Don't miss what happened while you were away" (FOMO trigger)
• "Your friend just..." (social trigger bridging to internal)
• "Pick up where you left off" (routine trigger)

Ethical boundary: Don't build triggers that fire on vulnerable emotional states (depression, addiction, grief) — those users can't exercise the autonomy the loop assumes.

See references/triggers.md when mapping triggers — the emotion-to-product mapping exercise and the external-to-internal transition plan.

2. Action

Core concept: The simplest behavior done in anticipation of a reward, guided by the Fogg Behavior Model: Behavior = Motivation + Ability + Trigger, all converging at the same moment.

Why it works: Increasing motivation is hard and unreliable; reducing friction (increasing ability) is easier and more effective. Every extra step, field, or decision is a drop-off point.

Key insights:

• Six elements of simplicity: time, money, physical effort, brain cycles, social deviance, non-routine
• The action is the simplest behavior in anticipation of reward — not the full task
• Hick's Law: more choices = slower decisions; reduce options to increase action rate

Product applications:

Copy patterns:

• "Just one tap to..." (emphasizes simplicity)
• "No credit card required" (money/risk simplicity)
• Buttons should be verbs: "Post", "Save", "Share" — not "Submit" or "Continue"

Ethical boundary: When you simplify an action, don't strip the cost or consequence with it — a one-tap purchase must still surface the price and the commitment.

See references/product-applications.md when adapting the loop to your context — action and investment patterns for B2B SaaS, e-commerce, health, and productivity tools.

3. Variable Reward

Core concept: The phase that keeps users coming back. Anticipation of reward — not the reward itself — creates dopamine, and rewards must be variable (unpredictable) to sustain engagement.

Why it works: The brain's dopamine system responds most strongly to anticipation of uncertain rewards — the slot machine effect. Three reward types — tribe (social), hunt (resources), self (mastery) — tap fundamental human drives.

Key insights:

• Tribe = social validation; Hunt = search for resources/information; Self = personal mastery
• Predictable rewards lose power; finite variability eventually becomes predictable — aim for infinite variability
• Autonomy is critical: users must feel in control; forced engagement backfires

Product applications:

Copy patterns:

• "See what's new" (implies variability)
• "3 people responded to your post" (tribe reward, variable quantity)
• "You've unlocked a new achievement!" (self reward, unexpected)

Ethical boundary: If users consistently feel worse after engaging (regret, time loss, anxiety), the reward system is extractive — avoid infinite scroll without natural stopping points.

See references/rewards.md when designing a reward — tribe/hunt/self patterns, the four reinforcement schedules, and reward timing. For the dopamine/anticipation mechanism behind variable rewards, see references/neuroscience-foundations.md.

4. Investment

Core concept: Users invest something — time, data, effort, social capital, money — that improves the product for next use, raises switching costs, and loads the next trigger.

Why it works: People value what they put effort into (the IKEA effect). Investment is not about immediate reward — it improves the next cycle, creating a self-reinforcing loop.

Key insights:

• Investment should come after reward, not before — users invest when they feel good
• Each investment should load the next trigger (posting content triggers reply notifications)
• Small investments compound: preferences → better recommendations → more usage; stored value grows over time

Product applications:

Copy patterns:

• "Complete your profile to get better matches" (investment → future value)
• "The more you use it, the smarter it gets" (compound investment)
• "Invite your team to collaborate" (social investment)

Ethical boundary: Investment should genuinely improve the experience — never trap users with artificial switching costs or impossible data export; make staying the better choice through real value.