Hook Model

The Four Phases

        ┌─────────────────────────────────────┐
        │                                     │
        ▼                                     │
   ┌─────────┐   ┌─────────┐   ┌──────────┐  │
   │ Trigger │──▶│ Action  │──▶│ Variable │──┘
   └─────────┘   └─────────┘   │  Reward  │
        ▲                      └────┬─────┘
        │                           │
        │      ┌──────────┐         │
        └──────│Investment│◀────────┘
               └──────────┘

Phase 1: Trigger

Triggers prompt the user to take action. They can be external or internal.

External Triggers

Environmental cues that tell users what to do next:

| Type | Example | Use Case | |------|---------|----------| | Paid | TV ads, SEM | Acquire new users | | Earned | Press mentions, reviews | Build credibility | | Relationship | Word of mouth, referrals | Viral growth | | Owned | App icon, notifications | Re-engage users |

Internal Triggers

Emotions and thoughts that prompt usage:

Emotion → Product Association
─────────────────────────────
Lonely  → Check Facebook
Bored   → Open Instagram
Lost    → Open Maps
Unsure  → Google it
Curious → Check news

Creating internal triggers:

• Associate product with specific emotions
• Build routines around usage
• Create FOMO (fear of missing out)

Trigger Design Principles

✅ Clear call-to-action
✅ Timely (when user needs it)
✅ Contextually relevant
✅ Action-oriented language

❌ Generic triggers
❌ Too frequent (notification fatigue)
❌ Irrelevant to user's current state

Phase 2: Action

The behavior done in anticipation of reward. According to BJ Fogg's Behavior Model:

Behavior = Motivation + Ability + Trigger

Maximizing Action

Increase Motivation:

• Show social proof
• Create scarcity/urgency
• Appeal to core drives (seeking pleasure, avoiding pain)

Increase Ability:

• Reduce friction
• Simplify steps
• Provide smart defaults

Example: One-Click Purchase

Before:  Browse → Cart → Checkout → Shipping → Payment → Review → Confirm
         (7 steps, high friction)

After:   1-Click Purchase
         (1 step, low friction)

Action Requirements

The action must be:

• Simple: Minimal effort required
• Obvious: Clear what to do
• Rewarding: User expects benefit

Phase 3: Variable Reward

The hook's engine—rewards that vary in type and timing create desire.

Types of Variable Rewards

1. Rewards of the Tribe (Social)

• Likes, comments, shares
• Follower counts
• Collaboration features
• Leaderboards

Example: Instagram notifications
"You have 3 new likes!" (variable, unpredictable)

2. Rewards of the Hunt (Material)

• Finding valuable information
• Good deals/discounts
• Rare items in games
• New content

Example: Slot machines, email inbox
"What's in this message?" (uncertainty drives checking)

3. Rewards of the Self (Achievement)

• Leveling up
• Unlocking achievements
• Completing collections
• Streaks

Example: Duolingo streaks
"You're on a 7-day streak!" (mastery, consistency)

Why Variable Rewards Work

Predictable Reward          Variable Reward
     │                            │
     ▼                            ▼
  Habituation                 Novelty
  (get used to it)            (stays exciting)
     │                            │
     ▼                            ▼
  Decreasing               Sustained
  engagement               engagement

The dopamine factor:

• Predictable: Dopamine spikes before reward
• Variable: Dopamine spikes during anticipation

Variable Reward Design

✅ Mix reward types
✅ Create anticipation
✅ Surprise users occasionally
✅ Provide feedback on progress

❌ Completely random (feels unfair)
❌ Always the same (becomes boring)
❌ Too scarce (users give up)

Phase 4: Investment

Users put something into the product, increasing commitment.

Types of Investments

Time:

• Content creation
• Learning curves
• Setting preferences

Data:

• Personal information
• Photos, documents
• Behavioral history

Social Capital:

• Followers/friends
• Reputation scores
• Shared content

Effort:

• Customization
• Skill development
• Content organization

The Stored Value Principle

User Investment → Stored Value → Higher Switching Costs

Examples:
• Spotify playlists (can't transfer to Apple Music)
• Pinterest boards (personal curation)
• LinkedIn profile (professional history)
• Gmail (email archive)

Investment Techniques

1. Personalization:

"Based on your listening history..."
"Recommended for you..."
"Your personalized feed..."

2. Skill Building:

Level 1: Basic features
Level 5: Advanced tools
Level 10: Expert features

Each level requires previous investment

3. Content Creation:

• Photo uploads
• Reviews written
• Playlists created
• Posts shared

Users return to access their content

4. Network Effects:

More friends → More value → More engagement
Each friend added increases product value

Putting It All Together

Example: Instagram

Trigger:
  External: Push notification "John liked your photo"
  Internal: Feeling bored, lonely, curious

Action:
  Open app (simple, one tap)

Variable Reward:
  • New likes/comments (tribe)
  • New posts in feed (hunt)
  • Story views on your content (self)

Investment:
  • Post your own photo
  • Follow new accounts
  • Build your aesthetic
  • Gain followers
  
  ↓
  
Next Trigger: Followers engage with your content

Example: Duolingo

Trigger:
  External: Daily reminder notification
  Internal: Desire to learn, guilt about streak

Action:
  Complete one lesson (5 minutes, gamified)

Variable Reward:
  • XP points earned (varies by performance)
  • Random rewards (gems, chests)
  • Streak maintained (achievement)

Investment:
  • Progress in language tree
  • Friends added
  • Streak days accumulated
  • Skill levels unlocked
  
  ↓
  
Next Trigger: Streak reminder, competitive leaderboard

Ethical Considerations

The Manipulation Matrix

                    Does user benefit?
                    Yes           No
                ┌─────────┬─────────┐
Yes, would use│ Facilitator│ Dealer  │
    product   │  (ethical) │(unethical)│
              ├─────────┼─────────┤
No, wouldn't  │  Peddlar  │ Dealer  │
   use product│ (ethical?) │(unethical)│
                └─────────┴─────────┘

Questions to ask:

1. Would I use this product myself?
2. Does it materially improve users' lives?
3. Am I creating a positive habit?

Healthy vs Unhealthy Hooks

| Healthy Hook | Unhealthy Hook | |--------------|----------------| | Improves user's life | Exploits vulnerabilities | | User in control | Compulsive usage | | Natural stopping points | Infinite scroll, no exit | | Transparent about design | Deceptive patterns | | User feels satisfied | User feels manipulated |

Measuring Hook Effectiveness

Engagement Metrics:

• Daily/Monthly Active Users (DAU/MAU)
• Session frequency
• Session duration
• Feature usage depth

Habit Metrics:

• Retention curves
• Habit formation timeline
• Trigger response rate
• Investment accumulation

Health Metrics:

• User satisfaction
• Net Promoter Score
• Support ticket volume
• Churn rate

Common Mistakes

1. Weak Triggers

❌ Generic notifications
❌ Untimely prompts
❌ No emotional connection

✅ Context-aware triggers
✅ Personal relevance
✅ Clear value proposition

2. High Action Friction

❌ Complex onboarding
❌ Too many steps
❌ Unclear actions

✅ Streamlined flows
✅ Progressive disclosure
✅ Obvious next steps

3. Predictable Rewards

❌ Same reward every time
❌ No surprise elements
❌ Immediate gratification only

✅ Variable reward schedules
✅ Multiple reward types
✅ Delayed gratification opportunities

4. No Investment Phase

❌ No user-generated content
❌ No personalization
❌ No skill progression

✅ Content creation tools
✅ Preference learning
✅ Progress tracking

Implementation Tips

Start Simple

Phase 1: Get one hook working
  → Perfect the trigger
  → Optimize the action
  → Test variable rewards
  → Enable basic investment

Phase 2: Add complexity
  → Multiple trigger types
  → Advanced actions
  → Rich reward systems
  → Deep investment layers

Test and Iterate

A/B test elements:

• Different trigger messages
• Action button placement
• Reward timing
• Investment requirements

User research:

• Interview habitual users
• Analyze drop-off points
• Study successful competitors